That’s the room I found myself in last week, and it made the case for a different reality than the one the tech headlines describe. Read the coverage of the modern internet and you’d assume it’s run entirely from a handful of boardrooms: Bezos, Musk, whichever executive is dominating this week’s news cycle. That framing misses the actual engine room. The internet that answers your questions, settles your arguments and got you through your dissertation runs on something much less glamorous: volunteers, most of whom you will never hear of, doing unpaid work for decades.

AI has made this easy to forget. Ask a chatbot a question and an answer appears with no visible author and no visible cost, which creates the impression that the digital town square is a vending machine, not a construction site. Somebody had to write the answer before the machine could serve it back to you. Somebody still has to.

You should know Kelly Foster

Kelly Foster has been part of the Wikimedia movement since 2012 and volunteering with Wikimedia UK since 2016. She has been a driving force behind adding content about Black people, historically underrepresented on Wikimedia projects, and in training new editors to do the same. She has served as a trustee of Wikimedia UK and worked as a Wikimedian in Residence on the Making African Connections research project.

What makes Kelly’s work distinctive isn’t just the volume of it. It’s the criticism she brings alongside the enthusiasm. She has consistently pushed the Wikimedia movement to reckon with the legacy of colonialism in shaping the knowledge it works with, arguing that open knowledge should challenge the dominance of Western culture and the best-resourced institutions. On 3 July, that work earned her one of Wikimedia UK’s five Silver Jubilee Awards, presented by Jimmy Wales himself, marking a quarter century of volunteers whose contributions have had a lasting impact on the UK Wikimedia community.

She is one of thousands doing the same unglamorous work: the uncredited source behind an AI-generated answer, the reason a Wikipedia page existed at all when you needed it for a project.

The occasion

Wikimedia UK marked two anniversaries at once at Sea Containers on the South Bank: Wikipedia’s 25th birthday and Wikimedia UK’s 15th year as a registered charity. The room brought together editors with two decades of contributions behind them alongside newer volunteers, partners, funders, policymakers, staff and trustees. Wikipedia’s founding premise sounds faintly ridiculous said aloud: the sum of human knowledge, maintained by whoever shows up. In a room with several hundred of the people who show up, it stops sounding ridiculous and starts sounding like a plan that worked.

Twenty-five years in, Wikipedia runs to more than 300 language editions and a wider network of sister projects, kept current by close to 250,000 volunteer editors, and helps billions of people explore ideas and answer questions every single day. Nobody in that room owns any of it.

Jimmy Wales was guest of honour, presenting Wikimedia UK’s Silver Jubilee Awards to five volunteers whose work has shaped the UK Wikimedia community over the past 25 years: Andy Mabbett, who has been training and building partnerships since 2003 and once got the subject of a Wikipedia article to record their own voice aboard the International Space Station; Kelly Foster; Kirsty Ross, who founded the IDEA Network to make knowledge production more accessible; Lucy Moore, who has written a Wikipedia article for a woman from every country in the world; and Martin Poulter, involved since 2005 and part of the original push to have Wikimedia UK recognised as a charity.

Josie Fraser gave some sharp remarks on the evening’s themes, and it was good to talk to Adrian Beidas, Mohammed Amin, Monica Westin and Belvin Tawuya, among others, across the room. It was also good, as ever, to catch up with Jimmy Wales himself, whom I’d interviewed at Kekst CNC’s offices at the end of last year.

The theory that predicted this room

The evening kept pulling my mind back to Clay Shirky’s Cognitive Surplus. Shirky’s 2010 argument was that the twentieth century left educated societies sitting on a vast reserve of free time and spare cognitive capacity, most of it spent watching television. Connect that surplus to the right tools, he argued, and people would build things like Wikipedia: freely given, collaboratively produced, better than anything a market alone would generate. It was dismissed as naive at the time. Standing in a room full of the people who proved him right, it reads less like naivety and more like an accurate forecast, delivered 15 years early.

There’s an injustice buried in that forecast, though. Shirky imagined a surplus given freely for the pleasure of building something together. Nobody accounted for that surplus being harvested to train the products of the companies now straining the infrastructure it runs on.

What that surplus is now funding, whether it likes it or not

Since January 2024, bandwidth for multimedia downloads from Wikimedia Commons has grown by 50%, and almost none of that growth is human. It’s AI crawlers, scraping the archive to train models, some of them disguising their traffic as ordinary browsers to dodge detection. Bots have generated roughly two-thirds of the Foundation’s most resource-intensive traffic while accounting for barely a third of actual page views.

The arms race hasn’t let up since: as of March 2026, the Foundation was blocking or throttling around 25% of all automated crawler requests hitting its sites, a filtering operation now running into the billions of requests a day. That’s staff time and infrastructure spend going into keeping bots out rather than building anything for readers or editors. All of it sits on donations that average around $11 a head. The content is free. The infrastructure is not.

I’m told the London birthday event itself only happened because of a generous individual donation: a charity funded on £10 gifts throwing itself a party it could barely afford, in the same year the industry extracting value from its archive posted record profits.

Why this should matter to anyone in comms

The people keeping this running aren’t the tech billionaires whose faces dominate the coverage. They’re people like Kelly Foster, giving up evenings for a cause that will never make them rich. If you’ve built a comms career on the back of Wikipedia’s credibility, or you’ve ever had to sort out a client’s page, you’ve been drawing on that unpaid labour without necessarily clocking it.

Consider giving something back. In an information environment this thick with misinformation, Wikipedia and the volunteers behind it are one of the few things left actually worth defending, and they’re currently doing it on donations averaging the price of a coffee.

Read Wikimedia UK’s article here, and whilst you’re at it, please consider donating.

The occasion was the London leg of Nir Eyal’s tour for Beyond Belief: The Science-Backed Way to Stop Limiting Yourself and Achieve Breakthrough Results, an evening Kekst CNC put on in partnership with the tech community Potato (yes, really, Potato). His latest book Beyond Belief is Nir’s attempt to do for conviction what his other books did for habit and attention.

He is the rare author who is exactly as generous and positively caring in person as the words in his book guide. He stayed long after the formal part had ended, working through a queue of readers with no apparent hurry, several of whom had travelled a serious distance to shake his hand, get his views, and have a book signed.

Beliefs are tools, not truths

For readers of this Substack, I know that self-help books are an area of contention - but Beyond Belief is different. It does offer a powerful science-backed argument that the limits you treat as facts about yourself are usually beliefs you have never bothered to question. However, for anyone working in marketing and communications, the book presents useful processes and principles painting what a brand narrative actually is and how they can collapse at precisely the moment they are needed.

Nir explained that we need to separate these three things, which we routinely confuse in our lives:

• A fact is an objective truth that holds whether you accept it or not.

• Faith is a conviction that asks for no evidence.

• So belief sits between the two: a strongly held conviction that remains open to revision when the evidence shifts.

Most of our trouble comes from collapsing the distinction, treating our faith as fact and our beliefs as facts, and then defending all of it as though reality were at stake. For communicators, a great deal of what a company and its stakeholders solemnly call “the facts” are beliefs in disguise, and beliefs, unlike facts, can be worked.

The ‘lie’ inside Belief

The line that drew the loudest murmur of recognition was the simplest. Look, Eyal said, at the word itself. There is a lie sitting in the middle of belief. A belief does not have to be true to be useful. It only has to work.

A purpose statement, a positioning line, a set of values bolted to an office wall: none of these is a fact in any meaningful sense. They are instruments, and the only honest question to ask of them is whether they move people in the direction the business needs.

Nir reached for Amazon as his worked example (based on an ex-Amazonian sitting in the audience). One of the company’s founding internal beliefs is that it is always Day One. This is obviously nonsense. Amazon is a vast, mature, institutionally fortified machine, and it has not been on its first day for decades. As a tool it is close to priceless, because a company that genuinely believes it is still scrappy and still at risk behaves like one, and a company that believes it has arrived may find its energy sapped away.

Reputation is a belief held by other people

Start with what a reputation is. If beliefs filter what an audience notices, feels and does, then a brand reputation is simply the belief a stakeholder already carries about your organisation. That is the asset communicators manage, and it explains why disclosure on its own so rarely repairs trust.

We tend to behave as though the facts, once released, will speak for themselves. They never do. The facts arrive, and the pre-existing belief decides what they are permitted to mean. Nir put a number on the gap between what reaches us and what we register: the brain takes in something like 11 million bits of information a second and consciously attends to roughly 50 of them. We see more of what we already believe and screen out the rest. Pour more facts, more proof points and more content into that system and you change very little, because the belief doing the filtering has not moved. The work is on the filter, not the feed.

The real test is what a brand stands for when it costs something

If a belief is a tool, then the test of it is not whether you can recite it on a good day. The test is whether it holds when it costs you something. Nir’s point aimed at organisations is that companies go wrong at the exact moment they abandon their beliefs. Everyone is a person of conviction when its easy to do so. The interesting question is what gets quietly dropped when a situation becomes challenging: when the regulator calls, when the share price moves the wrong way, when the easy thing and the stated value point in opposite directions.

The gap between the belief a company professes in its annual report and the belief it reveals under pressure is, more or less, the entire territory in which reputations are won and lost. A value that is jettisoned the moment it becomes expensive was never a belief.

We treat a crisis as a contest over facts, a scramble to establish what happened and in what order. It is that, and it is a belief test first. The most common failure I see is the one Nir describes, as learned helplessness: the retreat into a defensive crouch, the decision to go quiet, say nothing and wait for it to pass. It feels protective. It is usually corrosive, because silence is read, fairly or not, as the absence of any belief worth defending.

Why a vague brand narrative is no narrative at all

There is a fashionable counsel of caution abroad at the moment which holds that, in an age of permanent uncertainty, the smart move is to commit to as little as possible. Hold every position lightly. Keep the narrative vague enough that nothing can later be held against you. I have argued before on White Wiki that uncertainty is exactly the condition under which communicators should be saying more, not less, and Beyond Belief sharpens the point.

A belief held so loosely that it survives any circumstance is not flexibility. It is the absence of conviction wearing flexibility’s clothes, and audiences can smell it from a great distance. The organisations that come through a hard year with their reputation intact are not the ones that believed nothing and therefore risked nothing. They are the ones that chose their beliefs deliberately, in advance, knowing what those beliefs might one day cost, and then paid the bill when it came due.

The beliefs worth holding are the ones that make you sweat

Which brings me back to the taxi. Eyal is fond of the line that everything worth having sits on the other side of discomfort, and that the trick is learning to manage the discomfort rather than wait for it to lift. I cannot pretend that an hour in a sweatbox on snail-slow London roads taught me anything profound about the human condition. But it is a serviceable reminder that the beliefs worth holding are precisely the ones that occasionally make you sweat. Perhaps the brands that survive the test of time do the same.

If you found this article thought-provoking, then you can buy Beyond Belief here.

Having now watched the events unfold at the other big tech conferences of the month, an uncomfortable question has been weighing on my mind… If June’s tech agenda was so focused on trust and AI, why was our discipline of strategic communications so hard to find on the stages?

How the tech conferences argued our subject

In London, the dominant human problem was trust. A friend working the events had been dropping the session summaries into a WhatsApp group, hundreds of them across London Tech Week and the London AI Summit, and trust appeared in 154 of the 352, more than any other theme. Around it clustered regulation, governance, the future of work, and the sovereignty question I wrote about last time.

And at SXSW London, a celebrity haunt as much as a tech festival, with Michelle Obama recording her podcast, the tech names on stage included Victor Riparbelli of Synthesia, whose business is synthetic video, and Rose Wang of Bluesky, whose proposition turns on trust and moderation. You can’t help but feel there is something subtly instructive about debating who the public can believe at a festival that is hosting synthetic-video pioneers and a former First Lady. Strip the lanyards off, and you are left with the management of public belief at scale - PR.

At VivaTech in Paris, artificial intelligence had stopped being a topic on the agenda and become the grammar of the whole event. The through-line the organisers kept returning to was sovereignty. A French agency even produced a tracker of the speaker list, which framed the event as a contest for European technological independence against the United States and China. Numerous ministers and regulators were in attendance, a sure sign that Europe is in the final, decisive stretch of writing the rules for how AI meets the public.

The questions on every stage - who is believed, who is trusted, who gets to tell the story - are communications questions. We have spent a century developing the vocabulary for them, but struggle to position ourselves.

We were not holding the microphones

With all those summaries to hand, I counted who was actually standing in the limelight.

Just 2 of 865 speakers at London’s two big AI events came from communications, public relations or corporate affairs. Not one of them was a chief communications officer.

Founders and chief executives took 287 of those 865 seats, technologists another 285. The vocabulary of communications appears nowhere across the 352 summaries. The word reputation itself surfaces twelve times.

Paris repeated the lesson in an even more pointed form. The independent tracker I mentioned earlier sorted VivaTech’s speakers and delegates by function, but did not trouble to give communications a category of its own. It folded the discipline into marketing, and even the combined pair came to just 4% of the room.

And going back to the two occasions in the London transcripts where communications did surface, it appeared first as a risk (”PR or legal issues”) and second as a line on a shopping list, a requirement to be procured alongside market access. We are filed, by the people building these systems, as a cost to be managed and a service to be bought, rather than as the discipline that owns the very problem they spent the month worrying about.

The room we were actually in

During the thick of tech conferences, the AI for PR Conference ran in London. It had a strong line-up: President of the CIPR, Farzana Baduel. Chief Executive of the PRCA, Sarah Waddington CBE. Carolyn Esser, Chief Corporate Affairs Officer at Darktrace, which is to say a communications leader at a listed cybersecurity firm, exactly the sort of person the London stages never thought to ask. Alongside them, much of the measurement community, the people now writing the rules for how a brand stays visible when an AI is the one doing the answering.

I was exploring Norfolk with the family, so unfortunately missed the occasion - a slight irony given what I’m writing about today - but the programme is exactly what our industry needs to care about. Reputation, crisis, governance, the integrity of the function in an automated world.

Yet we’re still talking in a bubble, and in the next 12 months we need to burst through to appear on those stages.

Three uncomfortable questions

It’s disappointing that, as someone who invested time and money in a CIPR-accredited PR degree, has since spent 15 years in the industry, and takes education as a professional responsibility, I feel the very industry I’ve bet on is in a perilous position when it comes to AI.

These are the questions every communications practitioner should be asking themselves:

How do we stop being the people who organise the stage and start being the ones the audience came to hear? There is a huge importance in coming together as an industry to share and learn from one another, but businesses are embedding AI into their operating models, and the integration and rollout of AI are largely communications challenges to navigate.

Have we made ourselves legible to the people setting the rules? Our industry is hugely diverse: representing all sectors and specialisms, with businesses ranging from freelancers to multinational giants. Perhaps our variety as a function creates buyer confusion around the concept of communications, meaning board-level appointments aren’t universally understood?

Are we spending our scarce attention on the right emergency? The tooling, the workflows, the very absorbing question of our own productivity are all real. But the categories that will govern how AI meets the public are being written this year and next, while they are still loose enough to shape, by people who do not think of trust as ours to hold. That, and not the content pipeline, is the thing with a closing window.

So what room are we building?

In the London Tech Week piece I ended on ownership: someone always owns the thing, and someone always tells the story of who owns it, and your only real choice is whether that someone is you. The same logic holds one level up, for the profession itself.

There are always two rooms. The one where we explain ourselves to each other, and the one where everyone else decides what we are for. We have become very good at filling the first. We cannot keep leaving the second half empty and wondering why nobody saved us a seat.

In the next 12 months, it would be good to see the role of strategic communications elevated industrywide, and to see more industry colleagues on those tech stages.

The story of London Tech Week 2026 rested on two themes: capital and sovereignty. Let’s start with the capital…

London Tech Week launched with a fanfare of announcements.

• £2 billion: AMD’s commitment to the UK over the next five years.

• £1.7 billion: Nebius committed to building out AI capacity in the UK.

• £400 million: Sir Keir Starmer used his keynote to set out a national compute strategy, including to buy specialist AI compute, alongside a wider AI hardware plan worth around £1.1 billion across chips, compute and skills announced by the Technology Secretary.

• £45 million: Lord Vallance announced the Engineering Biology Value Chain Growth Fund, on top of larger sums for research and scale-up infrastructure.

• £12 million: Mayor of London, Sadiq Khan announced investment into helping London’s small firms adopt AI, and published a City Hall report warning that requests to connect new data centres to the capital’s grid already run to roughly ten times the power those centres draw today.

An accountant for UK PLC may say these investments build the resilience necessary to cement Blighty in Europe’s so-called “decisive decade”.

Then on sovereignty, this was a full-on informal state occasion. The Prince of Wales joined a panel on using data to spot the risk of homelessness before it arrives, and his Homewards initiative launched a Homelessness Data Lab. The Mayor of London launched a programme of his own. The Prime Minister opened London Tech Week, as he did last year. The Science Minister attended, the Minister for AI, the list was quite endless… even the Director of GCHQ – an eagle-eyed observer would spot discreet security with earpieces.

So the two forces, sovereignty and capital, and what they mean for us humble communications practitioners.

The first force: sovereignty

Digital sovereignty is a grand term for a series of basic questions. Who owns the compute, the energy, the data centres and the data that artificial intelligence runs on? Who sets the terms for everyone else who uses them?

Sovereignty is multidimensional, and every country defines it to suit its own geopolitics, economy and security. The United States, the European Union and China hold three competing philosophies, written into the US CLOUD Act, the GDPR and China’s data security regime, and most other nations arrange themselves somewhere along that spectrum.

The sharpest version on stage came from Judith Dada of Visionaries Club, on a panel with the AI minister Kanishka Narayan, HPE’s Matt Harris and George Osborne, the former UK chancellor who now runs OpenAI’s work with governments. Dada argued that the prize is owning the bottlenecks that confer leverage, and noted that Europe holds a sliver of the world’s AI compute capacity, compared with roughly four-fifths in the US. Osborne made the realist’s case, that trying to own every layer of the stack is a fool’s errand, and that a country should aim to be indispensable rather than self-sufficient.

The consensus, once you strip away the rhetoric, is quietly pragmatic. No country is going to build the entire stack itself. Complete independence is neither affordable nor desirable, and a home-grown system would struggle to keep pace with the frontier. The serious goal is leverage and flexibility: control over the parts that matter, and the freedom to move when the politics or the economics shift. In practice, sovereignty is a negotiated set of options. The fortress was always a fantasy.

And it is not only a question of hardware. A sovereign capability is worth nothing without a workforce that can use it and a public that trusts it. Skills, adoption and public confidence sit alongside compute and data as conditions of the same independence. A nation, or a company, that owns the infrastructure but cannot carry its people with it has bought a tool it cannot lift.

The second force: capital

The second force was quieter on the main stages and more honest in the numbers. Britain is brilliant at building companies and less good at keeping them. The figures in this year’s Tech Nation report are strong. UK AI start-ups raised £8.2 billion in the first half of 2026, the country took close to half of all European tech investment, and the wider tech sector is now valued at around £1.2 trillion.

Read the same report a page later and the catch appears. Roughly fifty-seven pence of every pound made on an AI exit flows back to the US, with only nine pence staying here, and about one in two venture dollars invested in British AI arrives from across the Atlantic. The British Business Bank’s chair, Stephen Welton, spoke about scaling deep tech, which the UK has learned to do well. The harder problem is ownership at the finish line.

The example everyone knows, and few said aloud, is DeepMind. A London company, co-founded by Demis Hassabis, who by his own account wanted to keep it in London, sold to Google in 2014 for a reported £400 million because it needed the capital, the data and the computing power to stay at the frontier. The capital and the bottlenecks were in California, so in time the ownership, and the value, followed them there. The company still sits in King’s Cross; the cheques are signed in Mountain View.

That is the moment the two forces become one.

Whoever owns the compute and writes the cheque tends to end up owning the company, and with it the story of where the value was made. Mayor of London, Sadiq Khan was candid about the gravity… London has reclaimed its place as Europe’s leading tech hub and yet talent is mobile and can leave for Lisbon, Milan or Silicon Valley without much ceremony. AMD’s £2 billion and the growing London offices of OpenAI and Anthropic are welcome, but we’re currently a river that flows west.

The floor told the truth the stages skipped

Like last year’s London Tech Week, the expo floor – which I’ll certainly enjoy not experiencing for another year(!) – was full of conversations that coloured the corporate and state announcements. A good share of the stands belonged to other nations, each pitching itself as the place to incorporate, relocate and start again, their branding aimed at arrivals more than at home-grown firms with traction looking to expand.

The stage said build here. The floor said come and start over there.

Sovereignty at street level is a daily decision taken by founders and capital that can always choose somewhere else, and capital, as we have seen, usually has a view on the matter.

Regulation as a sovereign asset

Regulation itself can be a sovereign asset. British law firms were held up as leading adopters because the UK lets them experiment where the US does not. The medicines regulator may become the first in the world to license a gene therapy whose trial data showed it slowing Huntington’s disease progression by three quarters, data the American regulator has so far declined to accept. Owning your own rules, and using them with nerve, is a form of sovereignty that needs no hyperscaler’s budget. Although I’m not sure I want to be in a country known for rules over innovation – Keir Starmer’s opening speech didn’t help with that.

Sovereignty is a communications challenge

Everything is about communications, especially at a London Tech Week when capital and sovereignty are locking horns with one another. The questions a state now asks about compute and capital are the questions I hear from businesses every week. Here are five communications aspects to consider:

1. Every company needs a position on the sovereignty debate and decide if that needs to be public. For a growing number of companies, the debate is unavoidably public; if you run critical infrastructure, hold sensitive data, sell to government, operate a UK arm of a US parent, or depend on a single foreign platform, your customers, regulators and staff increasingly expect a view on where your technology comes from and who controls it – you must be prepared. This has already moved from reputation into disclosure. AI governance now appears in proxy statements and annual reports, investors expect boards to explain how AI is overseen, we even see this in those lengthy and tedious agency RFP processes. AI risk has joined cyber and supply chain as a standard line in corporate reporting. Of course, silence is a position as well, but you’re only really delaying the inevitable.

2. Know where your data lives, and who can compel access to it. The whole industry is fixated on which model to use. Far fewer leaders can say which jurisdiction holds their data, which sub-processors touch it, whether their providers train on it, and how much contractual freedom they have to move it. The lesson from the sovereignty debate is that location has stopped being the point. A data centre in Paris run by an American operator can still fall under American law. Control is the asset, and geography no longer guarantees it. For a communicator, that is a governance question with sharp reputational and disclosure edges, and the one most likely to surface in a regulator’s letter, an investigative piece, or the answer an AI system gives about your company.

3. Do not promise an independence you cannot deliver. The honest national lesson, that no one builds the whole stack alone, holds for companies too. Trying to engineer your own sovereign capability is expensive, hard to maintain and destined to trail the frontier. The credible story is flexibility: a setup built on solid foundations, with the optionality to change supplier, jurisdiction or model when you need to. Retire the sovereignty theatre and describe the real posture, which is pragmatic dependence held under firm control.

4. Remember that the machine is now a stakeholder. Your reputation runs partly on infrastructure you do not own, and the most important reader of your words may be generative AI. The answers across the prompt lines of Claude, ChatGPT, Perplexity, and so on, describe you to buyers, journalists, investors and regulators. They read what you publish literally, and they repeat their account of you to everyone who asks. Clarity and verifiable evidence are now the price of being described correctly.

5. Make your employees and your broader stakeholders part of the story from the outset. The sovereignty debate keeps returning to skills, adoption and confidence, and so should your communications. The internal narrative, how your people are trained and brought along, and the external one, why the public should trust what you are building, carry as much weight as any infrastructure announcement. Capability that no one understands or trusts is not capability at all.

So what did I learn from London Tech Week 2026?

AI has turned infrastructure into politics, and politics into a capital requirement, and communications now sits where the two meet. Strip the week back and the discipline for any company is three questions. Where do you stand on who controls the technology you depend on, and is that position ready to be public? Where does your data live, and who can compel access to it? And who tells your story when you are not in the room, whether that reader is a regulator, a journalist or a machine?

Someone always owns the thing, and someone always tells the story of who owns it. Your only choice is whether that someone is you.

Each month, the Press Gazette ranks the 50 largest English-language news websites, and I fear for my reporter friends trying to survive in these times.

The mastheads our parents trusted, and our clients still pay us to monitor and appear in, are still struggling to find a business model that rewards perspectives and news.

The Reuters Institute‘s annual Digital News Report explains the migration in prose only slightly less funereal than my own: trust in traditional publications eroding, subscriptions stagnating, audiences drifting from the news brands to individual reporters. It’s these days that the columnist, the commentator, the named human with a discernible point of view, matters to readership.

One media brand is going against the grain: Substack. It’s the media brand that boasts growing traffic levels despite having no copy of its own, no large newsroom of reporters, and existing mainly to email other people’s writing to the people who asked for it. Its traffic has climbed from roughly 95 million visits at the end of 2024 to north of 169 million, very nearly doubling at the precise moment the rest of the industry was learning to do more with less.

This may explain why I’m frequently asked by a brand or an executive, “Should we be on Substack? Should I?”

It is a good question, and here is the answer.

I should declare an interest first: this very publication began life as a LinkedIn newsletter called White Space, and I picked it up, subscriber list and all (yes, there is a method…), and carried it over here. So clearly, I have voted with my feet (or my fingers?).

You’re already on LinkedIn

For most of the past decade, the answer to “where should our executive build a profile?” required no thought at all. LinkedIn. Obviously LinkedIn. It is where the professional audience gathers, the networking is frictionless, and the format forgives a great deal.

Then the foundations changed.

Over the last 12 months, LinkedIn rolled out a recommendation engine its engineers call 360Brew - a large language model, reportedly some 150 billion parameters, now deciding what the feed shows you. It reads your actual words, infers what each individual reader privately cares about, and renders a verdict on your relevance. The consequences have been well documented.

Richard van der Blom’s Algorithm Insights study, drawn from 1.8 million posts, found views down 50%, engagement off 25%, and follower growth slowed by 59%. Company pages fared worst of all: organic reach down somewhere between 60 and 66% since 2024, with the average corporate page now reaching around 1.6% of the followers it worked so hard to acquire. You may recall this is a transition Facebook went through around 2016.

Even LinkedIn’s own stars feel the chill. Simon Sinek, Adam Grant and Steven Bartlett command audiences in the millions there, and all three now work a feed that rations attention more tightly than at any point before. However, keep in mind that it’s a personal profile now that earns several times the reach of a company page sharing the very same words.

Now clearly, investing time in LinkedIn is still important as it remains the largest professional gathering on a social network with the backing of Microsoft. However, building a profile on LinkedIn is like investing in a house on leased land and everything has the potential to quickly change. Keeping this homeowner analogy going, there is nothing quite like owning your own place.

What to consider on Substack

Earlier this year I attended an event with Emma Rowley, Substack’s Head of News and Culture UK, to explore what it takes to be successful on Substack.

The room was full, and the air was distinctly hot with communications people - agency and in-house - every one of them circling the very question I now field. You could watch the penny drop as the room understood that the platform has remarkably little interest in the organisation. It wants a person.

For most executives and brands, Substack won’t be right. Mostly as they’re unwilling to do the one thing Substack rewards, which is an authentic human voice that offers a perspective worth considering. If your internal approvals process includes a dozen people and multiple rounds, we all know that the outcome is a piece of polite airline journalism that doesn’t require thought.

BUT, if you are bold, brave, and belligerent (no, really), Substack could work. Have something to say, be credible with it, and let the institutional glaze of responsibility take a slight breather - be willing to connect with people and exchange ideas in a public forum.

Owning your audience has quietly become one of the very few moves in executive communications where the wind is at your back rather than in your face. The inbox, it turns out, is about the last piece of land you actually own. I would think hard about who, in your organisation, deserves to build on it.

LinkedIn vs Substack, the benchmark

Let’s pit both platforms against each other, but they’re very much bedfellows in reality.

On search, the gap is structural. A LinkedIn post lives behind a login wall and is, to a search engine, very nearly invisible; only LinkedIn’s long-form Articles are reliably crawled and there is a small chance Gen AI responses will surface them. Every Substack post sits on the open web, on a domain you can make your own, indexed and accumulating the topical authority that search rewards.

That second clause is the one most comms teams have yet to price in. When a journalist, an analyst or a prospective client asks ChatGPT or Perplexity “who is the leading voice on X?”, the model answers from what it can retrieve, and it retrieves from the open, indexable, persistent web far more readily than from a walled feed.

The sharpest operators are now building what the Generative Engine Optimisation (GEO) crowd call triangulated authority: a personal site, a LinkedIn presence and a Substack, cross-linked so that an executive resolves, in a machine’s eyes, into a single verifiable expert. An owned, indexable body of work has become a reputational asset in its own right, and a login-walled feed is the wrong place to keep one.

A practical caution while we are here. LinkedIn now suppresses posts carrying external links by something like 40% to 60%, so the old “here’s my newsletter, do click through” play actively backfires. Lead with the idea natively, hold the link back, and route readers across with rather more subtlety than the job used to require.

So… should you, or shouldn’t you?

If the macro case has tempted you, the decision still comes down to a short and unsentimental set of questions. I would not proceed unless your executive clears most of them.

Have they got analysis, or only announcements? Readers subscribe for thinking that sharpens their judgement - a framework, a contrarian-but-defensible view, a lesson from the actual coalface of running something. A press release in a nicer typeface won’t work.

Will they write it, and keep writing it? Cadence is the single best predictor of whether one of these survives. The internet is an ossuary of executive newsletters that launched to fanfare and fell silent by week seven, and a dead Substack speaks louder than no Substack.

Can you let it run free of the sales function? The publications that earn the regard of journalists and analysts read as editorial. The instant yours smells of the pipeline, the credibility that justified the whole exercise evaporates, and you are left with an expensive brochure nobody opens.

Can your sign-off keep pace? Regular publishing needs a review process robust enough to protect the business and quick enough to clear a post within the news cycle it belongs to. Three approvals and a fortnight’s delay will strangle a publication before it draws breath.

Can you live with the comments? A public platform hands your critics a permanent venue, and someone will need to tend it. For an executive with active detractors that is a genuine consideration, though a manageable one if you have planned for it rather than discovered it.

Do you have the time for Substack Notes? It’s widely reported that Substack Notes is the best growth engine for subscribers and views, but it’s akin to managing an old-school Twitter account. You need daily publishing, comment fielding, and open interaction with other authors.

So, what do you think? Ready for Substack?

There is a particular flavour of frustration, familiar to anyone who has ever tried to get a legitimate, properly sourced, conflict-of-interest edit actioned on Wikipedia, that I have come to think of as the encyclopedia’s quiet tell. You do everything by the book. You declare your interest. You assemble your citations like a barrister preparing a brief, reaching for the independent secondary source rather than the convenient primary one. You place the little edit-request template at the foot of the talk page, append your courteous request, sign it with the requisite four tildes, and then you wait. And wait.

Unless you have the rare convenience of an active editor on the page, most COI requests join a centralised queue, patrolled by a small but dedicated band of volunteers. The oldest open requests in that queue tend to hover somewhere between three and four months old. Some have been seen wearing the dust of a year or more. Somewhere around week six, you begin to suspect that the encyclopedia which now functions as the closest thing humanity has to a shared factual substrate is being maintained by roughly the number of people it takes to staff a mid-sized garden centre.

That suspicion is the puzzle this article sets out to solve.

On the one hand, Wikipedia has never mattered more, for reasons I will come to that have everything to do with artificial intelligence and almost nothing to do with its readers. On the other hand, getting a careful and entirely legitimate change made to it has never felt slower. I went in believing the obvious explanation, the one most people believe: that Wikipedia is simply running out of editors, fewer hands at the tiller every year. That turns out to be wrong. What is actually happening is stranger, and rather more alarming, than simple decline. Here are four facts, with four graphs. Take them in order.

PART ONE: THE EVIDENCE

Shift one. It is not, in fact, dying

The popular narrative has a comfortable shape. Wikipedia peaked in its idealistic youth and has been bleeding contributors ever since. There is real history beneath this. The number of active editors on English Wikipedia, defined with bureaucratic precision as registered, non-bot users making five or more edits in a given month, did indeed peak in 2007 at somewhere north of 51,000, and then entered what the researcher Aaron Halfaker memorably christened the decline phase. His widely cited 2013 study traced the cause not to apathy but to the encyclopedia’s own immune system: as Wikipedia armoured itself against vandalism with bots, automated reverts and an ever-thickening hedge of policy, it became markedly less hospitable to newcomers, whose first tentative edits were now liable to be reverted by an efficient and impersonal machine. The newcomers, unsurprisingly, declined to return.

But here the data does something the narrative does not. The decline did not continue to zero. It bottomed out around 2013 to 2014, at roughly 31,000, and then it stabilised. The current figure, the one sitting on the encyclopedia’s own statistics page as I write, is around 37,000 active editors a month. Below the giddy high-water mark of 2007, yes. But comfortably above the trough, and broadly flat for more than a decade.

So the obituaries were premature. English Wikipedia is not dying. The patient is, if anything, eerily stable. Which raises a far more interesting question. If the workforce has held steady at around 37,000 for ten years, why does it feel, to anyone actually trying to get something done, as though there is nobody home?

Shift two. But the house has doubled

The answer is that we have all been watching the wrong number. The headcount is not the problem. The ratio is the problem.

+62% Growth in English Wikipedia articles since 2013, from 4.4 million to over 7.1 million, while the active editor base has stayed broadly flat. The same staff now maintains half as much house again.

In 2013, when the decline narrative was being written, English Wikipedia held about 4.4 million articles. Today it holds over 7.1 million. The encyclopedia has grown by more than half again, nudging towards a doubling, while the body of people maintaining it has not grown at all. Every one of those new articles must be watched, sourced, defended against vandalism and decay, updated as the world turns, and dragged into line with two decades of accreted policy. The house has gained wings, attics and a great many leaking gutters, and the same modest staff is expected to keep all of it weatherproof.

It is worse than even that ratio suggests, because the labour is grotesquely concentrated. The cliche, tiresome but essentially true, is that something close to 1% of editors produce the overwhelming majority of the content. The genuinely heavy lifting falls to the very active cohort, those making a hundred or more edits a month, who number only around 3,000 - 3,500 souls in any given month. When you submit an edit request, you are not appealing to a crowd of 37,000. You are joining the in-tray of a few thousand volunteers, most of them doing this in the evenings, for free, and who were, even a decade ago, described by the Foundation’s own people as feeling beleaguered and overworked.

Shift three. And the officers have all but gone

If the editors are merely overstretched, the administrators are something closer to an endangered species, and this is where the practitioner’s frustration finds its true source. Administrators are the editors entrusted with the heavier tools and, crucially, with the authority that often decides whether a contested edit request lives or dies. They are anointed through a process called Requests for Adminship, and the collapse of that process is one of the more astonishing graphs in the whole of internet governance.

The number of administrators today stands at around 820, a figure that has drifted downward for years and which flatters the reality, since a good share of those accounts are dormant. The process had become so notoriously gruelling, so much like running a gauntlet of strangers entitled to interrogate your every edit from a decade past, that qualified candidates simply stopped putting themselves forward. Matters had grown sufficiently dire that in 2024 the community did something it almost never does: it changed the constitution, introducing secret-ballot administrator elections expressly to spare candidates the public flaying of the old process. That is not the behaviour of a healthy institution casually iterating.

Shift four. While the readers are quietly intercepted

Wikipedia has never mattered more than it does today, and the reason has nothing to do with its readers. It is because of the machines. To a first approximation, every large language model in commercial use has been trained on Wikipedia, and the Wikimedia Foundation admits that its corpus is almost always the single largest source in those models’ diets. It is probably over-represented even relative to its size, because it is mirrored so promiscuously across the web that it ends up baked into the training data several times over. One researcher, reaching for a suitably undignified image, described the whole training corpus as a giant hairball, with Wikipedia threaded all the way through it.

It does not stop at training. Wikipedia underpins Google’s Knowledge Graph, populates the knowledge panels, feeds the AI Overviews and the chatbot answers, and serves as the primary credibility checkpoint against which a Generative AI model decides whether a claim about you, your client or your company is to be trusted. When an AI confidently describes a business to a user, it is very often Wikipedia doing the talking, ventriloquised through a model that will never cite it.

And there is the rub. The machines that depend on Wikipedia are simultaneously starving it.

−23% Fall in daily human visits to Wikipedia since early 2022, from roughly 165 million to under 128 million, with an 8% year-on-year drop in 2025 alone once disguised bot traffic was filtered out. We are all still reading Wikipedia. We have simply stopped visiting it.

The Foundation’s own analysis puts the cause plainly: search engines increasingly answer the question directly, in a tidy package, with no click required. When I interviewed Jimmy Wales at the end of 2025, he put the same figure to me himself, the 8% drop in human visits even as bot traffic climbed, and described the disproportionate hit on a charity’s server costs as AI firms crawl the site around the clock. He was, characteristically, more sanguine than alarmed. For a charity, he argued, lost page views matter less than lost attribution; the real sadness would be a world in which the public no longer knows the knowledge came from Wikipedia at all.

That is the optimistic reading. The pessimistic reading, which the graphs above quietly support, is that readers are not only an audience but a recruitment funnel. The casual visitor who fixes a typo today is the very active editor of 2030; the reader who sees the donation banner is the reason the servers stay on. An AI layer that consumes Wikipedia’s knowledge while intercepting its readers is, in the bracing word now used across the publishing industry, parasitic. It feeds on the host while cutting off the host’s supply of nutrients. The decade of flatness on current trends, is about to get a great deal less flat.

The snake and its tail

In March 2026 the community drew a line. After a Request for Comment that had failed in various forms before, English Wikipedia voted, by a margin of roughly forty to two, to prohibit the use of large language models to generate or rewrite article content outright. The exceptions were narrow and telling: you may use an AI to copyedit your own prose, provided you check it, and to rough out a translation. You may not use it to write the encyclopedia.

The reasoning was not technophobia. It was arithmetic and self-preservation. Generating a plausible, confident, entirely fabricated paragraph now takes a machine seconds. Detecting it, verifying it against sources and cleaning up after it takes a human volunteer hours. In a community where volunteer-hours are precisely the scarce resource, that asymmetry is fatal. Wales sketched the underlying mechanism to me in plainer terms than most policy documents manage: a model simply picks the most probable next word, so the most plausible thing is not the same thing as the most true thing, and what you get, eventually, is hallucination dressed as fact. He was unambiguous that the Foundation should never put AI-written text in front of readers without a human checking it first. The editors went further still, and named the deeper trap: the compounding loop in which hallucinated text slips into an article, is scraped into the next training run, and re-emerges from a future model as apparent fact, complete with a citation trail that loops back, eventually, to the lie. The serpent eating its own tail. The straw that broke the camel’s back, fittingly, was an autonomous agent that had taken to authoring articles on its own initiative.

PART TWO: THE CHALLENGE TO COMMUNICATIONS

So gather the four shifts together, because their sum is the answer to the puzzle I began with.

A flat workforce. Maintaining a doubled encyclopedia. With a collapsed officer class. And a reader funnel now being drained by the very machines that depend on the output.

Your conflict-of-interest edit request does not languish because Wikipedia is hostile to you, nor because you have done it wrong. It languishes because it is the downstream symptom of every one of those graphs at once. It sits near the bottom of a months-long queue tended by an over-stretched few who are also, as of this spring, fighting a war against machine-generated content. That is the whole mystery, solved.

For those of us in the reputation and intelligence trades, this rearranges the problem in three uncomfortable ways.

1. The stakes have inverted and risen. It used to be that an error or an unflattering line on a Wikipedia article cost you one webpage, read by whoever happened to land on it. That is no longer the unit of damage. Because Wikipedia is now the credibility checkpoint for the models, an outdated or wrong article propagates outward into AI Overviews, chatbot answers, voice assistants and knowledge panels, becoming the machine consensus about your client, repeated confidently and without attribution to a public that increasingly never visits the source. The article is no longer a page. It is a seed crystal for everything the machines will say about you next.

2. The legitimate route has narrowed exactly as the stakes have widened. This is the cruel scissors of the whole situation. The proper, disclosed path, the edit request made under the paid-contribution rules, depends entirely on the attention of experienced editors and administrators, which is the one resource every graph above says is shrinking in effective terms. The correct way to do this has never been slower. Meanwhile the improper shortcuts, the undisclosed account, the quiet direct edit, are more dangerous than they have ever been, because the community’s new vigilance against both conflicted editing and AI-generated text means anything that looks engineered is more likely to be caught, reverted and pinned to your client’s name in a place that the models will then dutifully learn from.

3. You cannot simply automate your way around the bottleneck. The obvious temptation, in 2026, is to have a model draft the polished article and submit it. That door has just been bolted. Generating or rewriting article content with an LLM is now against policy and actively policed, and while reviewers have sensibly agreed that prose merely reading like AI is not by itself a hanging offence, the burden of suspicion has shifted. The machine that made your job look easy has made the gatekeepers trust the gate less.

What actually works, then, is unglamorous and worth stating plainly. It is also, more or less, what Wales himself described to me as the approach that succeeds. Do not try to turn an article into a PR puff piece; that, he was frank, is simply not on the menu. Instead, point out where a published fact or the other half of a story has been left out, supply the reliable source, and let the evidence carry it. Arrive with the work finished: a clearly formatted, drop-in change, sourced to independent secondary material rather than the company’s own announcements, and obviously in service of a better encyclopedia rather than a shinier subject. And build a reputation.

On Wikipedia, as Wales put it to me, your pseudonym is your reputation, earned slowly through consistent and visible good behaviour; editors listen to the people they have learned to trust, and revert the ones they have not. The scarce resource is volunteer attention, so the winning move is to spend as little of it per request as possible. There is no growth hack for an under-resourced platform. There is only making the volunteers’ lives easier, and waiting your turn.

The authority of Wikipedia has never been higher. The number of hands holding it up has never been more precarious relative to the weight. Those two lines cannot keep travelling in opposite directions forever.

The lesson for anyone whose work touches Wikipedia is therefore not to treat its remaining editors as obstacles to be routed around, but as the overstretched custodians they actually are, of a thing far more important than the average comms brief allows. It is also, I think, the lesson Wales kept returning to in our conversation: trust is not a static asset but a thing built, slowly, through purpose, evidence and openness, and just as easily lost. The least we owe the people still doing that building, before we ask the machines anything else, is to remember whose answers we are really receiving.

I have spent the time since wading through the sessions and the largely tedious industry reaction. The loud quarrel of the past two weeks, the one pitting evangelists who pronounce Search Engine Optimisation (SEO) dead against purists who dismiss Generative Engine Optimisation (GEO) as a manufactured buzzword sold to the credulous, is the wrong one. Both camps are still arguing about discoverability: how a brand gets found. I/O 2026 was not, at bottom, about how you get found. It was about who now owns the act of discovering and understanding on the public’s behalf, and what that ownership does to the economics and the surveillance of reputation. That is a different conversation, and for our profession a far more uncomfortable one.

Let me start with the facts, because they are better than the rhetoric.

What actually happened

AI Overviews now reaches over 2.5 billion monthly users. AI Mode has crossed one billion monthly users in roughly twelve months, having grown something like tenfold since the previous autumn. Google’s own framing is the part worth dwelling on: queries are more than doubling every quarter, and total search volume reached an all-time high last quarter. People who use the AI features are not searching less. They are searching more, because the friction of composing the perfect keyword string has been abolished.

Around those numbers Google announced four things that matter to anyone who manages a reputation for a living.

1. The search box itself has been rebuilt for the first time in over twenty-five years. It is now multimodal by default, accepting text, images, files, video and even open Chrome tabs, and it reasons across all of them at once. AI Overviews and AI Mode have been merged into a single flow, so a user drifts from a results page into a conversational back-and-forth without ever choosing to. AI Mode has not been made the formal default, but the behaviour is now so close to default that the distinction is largely academic.

2. The model underneath it all is Gemini 3.5 Flash, now the global default in AI Mode, fast and cheap enough to run agentic tasks at the scale of the entire search index.

   

3. Google introduced background information agents. These are autonomous systems that sit inside Search and monitor a topic continuously, looking across blogs, news, social posts and live data, then surfacing changes without anyone having to run a query. I will return to this, because it is the most underrated announcement of the week.

4. Google is extending its SynthID watermarking and C2PA Content Credentials into Search and Chrome. SynthID has now marked more than a hundred billion AI-generated images and videos, and partners including OpenAI and ElevenLabs are adopting it. The provenance check is live in the Gemini app today and is rolling out to Search and Chrome in the coming months, which means the ability to ask of an image or clip, “was this made by AI,” is on its way to becoming a one-tap consumer reflex. For anyone defending an executive against synthetic media, that is good news.

So far, so consistent with what you have already read.

The number that tells the real story

In the same quarter that Google was celebrating record search volume, Alphabet’s Q1 2026 results showed Google Search revenue rising 19 per cent year on year to around $60.4 billion. In the very same results, Google Network revenue, which is the open web of AdSense and Ad Manager publishers, the sites that Google’s index was historically built to send people to, fell by 4 per cent to roughly $6.97 billion.

Read those two figures together and the strategic picture snaps into focus. Google is monetising synthesis on its own surfaces at a remarkable rate, while the open web from which it draws that synthesis is being starved by the very machine it used to feed. The traffic that funded the journalism, the reviews, the forums and the explainer content the models depend upon is declining even as the value extracted from that content rises. The single synthesised answer has become the destination, and when Generative UI can spin up a bespoke calculator, comparison table or dashboard inside the results page using the Antigravity engine, the user has no remaining reason to click through to your site at all.

This is why I find the SEO-versus-GEO row so beside the point. Both sides assume the game is still about earning a visit. The visit is the thing that is being eliminated. The optimisers are busy polishing the brass on a door that no longer opens. The question for a communications leader is no longer how to win the click. It is how to shape a judgment that is formed, delivered and acted upon entirely inside a system you cannot see into, cannot query and cannot appeal.

Why this is a category error for communications

There is a comforting consensus circulating among practitioners that AI visibility is “still eighty per cent good, fundamental SEO,” on the logic that large language models retrieve from the same authoritative indexes that traditional ranking rewards. As a technical observation about retrieval mechanics, that is true enough, and worth knowing. As a strategic posture for reputation management, it is a trap, because it flatters us into optimising outputs long after the leverage has migrated to inputs.

The deterministic web we grew up managing rewarded a recognisable set of outputs: a page that ranked, a link that was earned, a placement that could be screenshotted and reported. The probabilistic web rewards something stranger. A model does not care a great deal about your backlink profile. It cares whether your brand name is consistently associated with a particular claim across many independent and trusted nodes at once. It is, in effect, taking a weighted average of what the internet believes about you and serving that average back as fact, in the confident, citation-light register of a well-briefed colleague who has not quite done the reading.

That changes the unit of work. Page-one ranking is a legacy metric. The metric that now matters is share of citation: whether the model extracts, trusts and names you when it answers a question in your category. And share of citation is not won by volume. It is won by consistency and by source quality. A single, well-placed narrative in a tier-one title, a heavily cited industry report or an authoritative forum thread now outweighs fifty earnest posts on your own newsroom that nobody else troubles to corroborate. The strategy shifts from broadcasting to seeding: from producing content for audiences to curating the corpus the machine reads on the audience’s behalf.

The announcement nobody is frightened of yet

For as long as I have worked in intelligence, monitoring has been expensive and therefore rationed. A short seller, an activist investor, a regulator or a competitor who wanted to watch your every move had to commission people or platforms to do it. I/O 2026 democratised that capability and made it continuous and free. Anyone can now instruct a background agent to watch your sector under precise, nuanced parameters, to track every change, synthesise it and report back, around the clock, at effectively no cost.

The implication for crisis communications is structural. The weekly media-clippings model, retrospective by design, assumes that you and your adversaries watch at roughly the same cadence. That assumption is now false. Your critics are running always-on instruments while a good many comms functions are still reading yesterday’s coverage over this morning’s coffee. Worse, a misleading claim that takes hold in the sources a model trusts does not merely circulate; it risks being baked into the synthesised answer that two and a half billion people receive, repeated with machine confidence. The job is no longer to respond to a narrative. It is to detect and intercept one before it sets.

What I would actually do

If you accept that reputation is now mediated by a model before any human reaches your front door, the work reorganises itself around two verbs that have nothing to do with traffic: shaping the inputs, and shortening the time to detection.

On inputs, audit your entity footprint rather than your keywords. Test directly how Gemini, ChatGPT and Perplexity describe your company, your leadership and your contested issues, and find the gaps and the competitors being cited in your stead. Then build your owned assets, the newsrooms, investor pages and executive biographies, for extraction rather than persuasion: unambiguous, structurally clean, factually declarative, the kind of material a model can chunk and verify rather than skim and hallucinate around. And concentrate your earned-media effort on the narrow set of high-authority nodes that genuinely anchor a model’s answers, on the understanding that corroboration across trusted sources now beats volume on your own channels.

The bottom line

Google Search has not died, it has evolved and changed the web. The era of ten blue links offered a clean and frankly honest transaction: you optimised a page, the user clicked, and you controlled the room they walked into. You knew where you stood, even when you stood low.

In the agentic era that I/O 2026 confirmed rather than launched, that transaction is gone. Google is no longer the concierge in the lobby, pointing politely towards your door. Google is the host, standing on the threshold and summarising your entire story to the guest before they have decided whether to come in. The accounts tell us the host is keeping more of the takings while the suppliers who stock the kitchen are likely receiving less.

So stop managing the links. Start managing the story that feeds the machine, and watch that machine at least as closely as your critics already do. That is the real work the keynote handed us, and it began the moment the applause died down.

I used to find that question flattering. Now I find it unsettling. Because every time someone asks it, I’m not thinking about the person sitting across from me. I’m thinking about Michael White in 2008 - the version of me who was considering entering this industry, who had no idea what he was walking into, who thought communications was about the communications and not about the person doing the communicating.

So I decided to answer them properly. Not with platitudes. Not with motivational LinkedIn rhetoric. In total, these are the eight things I wish someone had told me when I was in their position. Things that have become obvious only because I’ve spent fifteen years in this industry and now find myself on the management team of a global consultancy, contributing to how this entire firm thinks about communications in an age of AI transformation.

If you’re considering joining this industry, or if you’ve just joined and you’re wondering whether you’ve made a terrible mistake(!), read on.

1. You’re only as good as your last piece of work

This is the hardest lesson and the most important. It is the lesson that keeps people honest. In communications, you can speak brilliantly about strategy in a conference room. You can command a meeting. You can have won a dozen awards for work that isn’t yours. And none of it matters the moment you deliver something mediocre, late, or half-baked.

This business doesn’t traffic in potential. It doesn’t care about your university degree, your internships, your connections - though all of those things help you get in the door. What matters is the email you sent yesterday, the deck you built last week, the brief you answered correctly when nobody else could see the angle. Your reputation in this industry is not a personal brand. It’s a work product. Get that wrong, and you’re starting from zero every time.

2. Understand people and their relationships

The industry will tell you it’s about media relations, project management, good writing skills, data analytics - and it is, sort of. But what it’s actually about is watching how people relate to each other and understanding why they do what they do.

You need to know what your client’s CFO wants from the CEO. You need to know why your team’s smartest strategist suddenly becomes quiet in meetings. You need to understand that the journalist who asks a brutal question in the first meeting might become one of your most valuable allies if you treat them with respect. You need to grasp that your colleague who seems invisible has actually watched three senior people fail at the same task and knows exactly where the trap is.

You cannot manage a narrative if you don’t understand the people telling it. You cannot manage a crisis if you don’t understand the psychology of the room trying to solve it.

3. Lean into people’s experience to innovate

You’ll arrive with fresh ideas. They won’t be new. Someone in the room has seen the version of this problem that you’re proposing to solve - maybe not exactly, but close enough.

The temptation is to ignore that. To present your idea as revolutionary. To treat experience like institutional resistance rather than institutional knowledge.

Don’t. Ask the person who’s been here longest what they’ve tried. Ask what failed and why. Then take that and push it further. That’s where innovation lives - not in the blank canvas, but in the willingness to stand on the shoulders of people who’ve already fallen trying.

At the same time, maintain a healthy scepticism of a broad consensus of an idea – if mankind’s ideas required to be agreed upon each time democratically, then our evolutionary desire for safety likely would have stopped progress. Henry Ford put it simply as this, “If I had asked my customers what they wanted, they would have said a faster horse.”

4. We’re all struggling with something. Don’t hide it.

A few years ago, I was not delivering my best work. I was forgetting things. I couldn’t process information the way I normally could. I’d sit in a meeting and feel present and completely absent at the same time.

I had just started taking medication for anxiety - connected to depression – and my brain felt like it was re-wiring itself. For a few weeks, I was in a fog.

Very few people knew. I certainly didn’t broadcast it. But looking back, I wish I had said something to the people who needed to know. Because they were probably wondering why I wasn’t myself. And I was probably wondering why they seemed frustrated with me. The gap between us grew because I thought strength meant silence.

It doesn’t. In a fast-paced environment where your intellectual performance is constantly measured, it is essential to recognize that all of us are humans. All of us are struggling with something. That might be anxiety. It might be grief. It might be a health crisis, a relationship falling apart, a mortgage that’s strangling you, a parent in decline, a secret that’s eating you alive.

You can’t build a functional team on the fiction that everyone is fine. You can’t build a client relationship on pretense. The moment someone on your team says, “I’m not okay,” you have a choice: you can pretend you didn’t hear, or you can actually listen.

Choose to listen.

5. This isn’t a job. It’s a way of life.

Strategic communications doesn’t have office hours. A crisis doesn’t wait for your holiday to end. A journalist doesn’t file at 9 a.m. and then call it a day. The news cycle, the social media pulse, the client emergency - none of it respects the boundary between your work and your life.

You need to go into this with your eyes open. This is a way of life. You’ll miss dinners. You’ll check your phone at midnight. You’ll be thinking about a client problem while you’re supposed to be present with your family. You’ll feel like you’re never quite off.

The flip side is this: if you’re the sort of person who loves the work, who genuinely enjoys solving problems under pressure, who gets energy from the chaos - there is almost no better place to be. But you have to know what you’re signing up for. You can’t do this half-heartedly. You can’t view it as a stepping stone and expect to be taken seriously.

6. Treat people as you want to be treated

This sounds like a platitude. It isn’t. It’s a survival strategy.

In communications, you will have power over people - over how they’re perceived, over their stories, over their reputation. You’ll have junior colleagues who want your approval. You’ll have vendors who need your business. You’ll have clients who depend on your competence. You’ll have journalists who might feature you or bury you.

The temptation to use that power loosely is constant. It’s easy to be brief with someone who isn’t useful to you. It’s easy to take credit for work you didn’t do. It’s easy to pretend to listen while you’re already thinking about the next meeting. It’s easy to be kind when someone can help you and distant when they can’t.

Don’t.

7. Rotten people spread amongst rotten people

This is the corollary. It matters because it’s true. Cultures don’t change slowly. They change through contagion.

If you work in an environment where corners are cut, where people take credit that isn’t theirs, where kindness is seen as weakness - you will become that version of yourself. Not because you’re weak. But because proximity to rot is corrosive. You’ll start small. You’ll justify it. You’ll convince yourself it’s necessary. And before you know it, you’re the person you said you’d never be.

During my career, I’ve seen this clash of cultures and values on the frontline. Sometimes it’s working with a client whose own internal way of working clashes with the values of your own team. In the past, it’s also been present when people join your consultancy directly from another, exhibiting behaviours that go against the grain.

This is why choosing where you work matters more than you think. This is why your first consultancy, your first team, your first boss - these are not trivial choices. They’re the choices that shape who you become.

8. Prioritize experience over pay, at least in the beginning

I can say this now because I’ve had the privilege of being paid well. But I came to it honestly. When I entered this industry, I didn’t negotiate for salary. I negotiated for exposure, for variety, for the chance to sit next to people who were better than me.

I was also in a privileged position. My family lived just outside London. I paid nominal rent. I didn’t have a mortgage. I wasn’t supporting anyone. I know that conditions aren’t the same for everyone, and that’s exactly why I support organizations like the Taylor Bennett Foundation - they exist because the path I took isn’t available to everyone, and it shouldn’t have to be.

But if you can afford to choose experience over salary in your early years, do it. Join the firm that’s working on the most interesting problems. Join the team where you’ll learn the most. Join the client where you’ll be pushed to your limits. The connections you make, the skills you develop, the reputation you build - these are currency in this industry. They’re worth infinitely more than a ten percent salary increase at the start of your career.

Because - and this is the thing nobody tells you - the pay comes. Not always fast, not always fairly, not always as much as you deserve. But it comes. It comes as a natural outcome of your experience, your reputation, and your relationships. The people who made different choices early, who prioritized salary over learning? Some of them are fine. Some of them are stuck. The ones who thrived were almost always the ones who understood that the first five years are an investment in themselves, not a paycheque.

The thing you actually need to understand

These eight points matter. But there’s something deeper that matters more.

This industry is transforming faster than any of us can keep up with. AI is rewriting what comms professionals actually do. The media landscape is fragmenting in real time. The relationship between journalists and PRs, between brands and audiences, between truth and narrative - it’s all in flux.

The candidates I interviewed who will thrive aren’t the ones with the cleverest prompts or the sharpest understanding of the latest platform. They’re the ones who understand that in an industry being rebuilt by machines, the only thing that can’t be automated is human judgment, human integrity, and human connection.

Come in with your eyes open. Work harder than anyone else. Be kind, even when it costs you. Build relationships like your career depends on it, because it does. And remember that the people who matter in this industry aren’t the ones shouting the loudest. They’re the ones who’ve kept their word, shown up for their team, and somehow managed to stay human while the whole world was going mad.

Good luck. And then you’re going to need something more than luck: you’re going to need judgment, resilience, and the kind of integrity that makes you someone worth working for.

The industry needs that. You can be that.

Christmas approaches, and I’m now managing a new demanding junior stakeholder, my beautiful son, who arrived on Sunday. With mum and baby doing well, my paternity leave has begun, and it is time to wave a thankful, if slightly exhausted, goodbye to 2025.

Before signing off for the year, however, I wanted to reflect on what I think 2026 may hold.

Intelligence to drive trust

Data-led insights continue to transform strategic communications into a function not just defined by media relationships but also elevate the roles of communications professionals to C-Suite decision makers; we protect and build a firm’s most important aspect, trust.

At the start of 2025, my focus began by naval gazing on the more polluted parts of the internet: misinformation and disinformation. I joined the firm Securitas for a talk in Stockholm, addressing the critical issues of narrative warfare and the communications landscape.

It was an apt narrative continuum following Mark Zuckerberg’s 7^th January 2025 announcement that Meta is abandoning the use of independent fact checkers on Facebook and Instagram, replacing them with community notes. You can read my independent thoughts on this subject by clicking here.

This thought leadership was reinforced at the end of the year by the privilege of interviewing Wikipedia Founder, Jimmy Wales, at a packed London event focusing on the fundamental concept of Trust. For a long time, I’ve been a supporter of the Wikimedia Foundation, and speaking about optimistically building trust beats focusing on the darker corners of the internet.

In between, I’ve been fortunate to speak and advise multiple companies facing challenges relating to their online profile. In particular, the ongoing impact of Generative AI. It’s clear that building trust in a zero-trust communications environment – accentuated by so-called AI slop and political polarisation – will continue to be a corporate challenge in 2026.

Zero-trust on social media is driving fragmentation

Social media continues to go through a catalyst of change. A data partner I work closely with, Pulsar, recently published their report ‘The Great Fragmentation: Navigating the Splintered Web’, showing how audiences, platforms, and behaviours are pulling in new directions. But you could call this phenomenon what it truly is: a mass secession from the truth, propelled by the failure of trust.

Pulsar starts the report by saying,

“We’ve been here before. In the middle of the 20th century, particularly in the US, markets and audiences were concentrated in the hands of a few major players across telecoms, automobiles and personal computing – until they weren’t. Today, the same fragmentation that took place within these industries is happening to social media.”

This ‘fragmentation’ could easily be seen as a visible symptom of ideological distrust. When institutions, governments, newspapers, and the very platforms that host them are viewed with a healthy scepticism, the result is predictable: a retreat. Platform choice is now a form of identity signalling. People are no longer merely choosing a medium; they are choosing a tribe, a belief, and a preferred version of reality.

Take Substack, for example. Pulsar highlights that Substack’s growth has been 65% this year – based on conversations here, this is in part due to a philosophical known that Substack rewards engagement and free speech.

The biggest user growth also comes from Bluesky and Truth Social – two other social platforms with strongly positioned purposes. In contrast, the user base for goliaths such as TikTok and Twitch are falling; Facebook and LinkedIn seem flat. It could be perceived that the masses, refusing to be informed by a single, purportedly objective source, now seek refuge in niche outlets and specialized channels where their existing prejudices are not challenged but celebrated.

Communications professionals with deep audience understanding will need to face how to manage narratives across these splintered grounds; additionally, where to focus shrinking budgets to make the most impact.

Get ready for 2026

If I had to summarise what 2026 will mean for strategic communicators, then it is to witness a paradox: we are more internet-connected than at any point in our lives, yet we are drowning in misinformation, polarisation, and isolation.

Social media has resulted in a society that is neither social nor particularly expert (thanks, AI). Having been burned by the cold, algorithmic indifference of the major platforms, where outrage is the currency, people now crave something that the corporate world, in its infinite clumsiness, struggles to provide: authenticity.

The fragmented communications landscape has curdled the professional tone of voice, which is likely suspected as PR-managed deception. Instead, people crave the personal. People do not want to hear from a “brand”; they wish to hear from a human being, flaws and all. It’s like the social media of 2008 has come full circle for 2026.

This means moving away from the vanity of “broadcasting content” and towards the essential work of community building. Trust is no longer a top-down endowment; it is a bottom-up achievement. It is built in the small –the Discords, the Substack comments, Facebook private groups – where the noise of the mob is replaced by the voice of the person.

The irony is delicious: to be successful in the professional world of 2026, one must become decisively less “professional.” One must be prepared to be personal, to be eccentric, and to be present. We are no longer managing reputations; we are tending to small fires of human fellowship in a very cold, very dark, and very splintered woods. If we cannot provide that warmth, we are merely adding to the chill.

Like many intentions of parents, they are quickly influenced by the actions of their children. In my case, another nappy change is now due. You could say I like to get my hands dirty, both professionally and in my role as dad. Clearly, part of my 2026 challenge will be balancing ‘corp dad’ with ‘dad, dad’.

Merry Christmas.

“… an abnormal and unstable situation that threatens an organization’s strategic objectives, reputation or viability”

Among client conversations and internal team discussions, I can tell you that the initial reaction to the financial violence isn’t fear, but a profound sense of offense. Without divulging the details of my first taste of short seller attack, often an organisation’s first reaction is the desire to drag the accuser into the public square and flay them with facts. For short sellers though, this is a mistake and a misjudgement of their character; they rely on narratives that drive a belief that a stock’s price is destined to fall.

Giving oxygen to this flame, say through an in-depth rebuttal, only acts to fuel the initial accusations. The objective is to lower the stock and then buy back shares at a lower price – a process known as “covering” – to profit from the difference. A short seller does not seek a debate; they seek a profit. Beyond financial value to reputational value, it only takes 10 seconds to smear a reputation, and 10 months to scrub the wall clean.

This is a grim theatre that began playing out last week when Grizzly Research, a short seller led by Siegfried Eggert, released a report accusing the FTSE 100 firm Trustpilot of operating a “mafia-style extortion campaign”. My own principles refrain me from directly linking to the report from this humble Substack, as arguments made are a classic of this short seller genre.

The assault on Trustpilot

The report was conspiratorial, laced with the sort of hyperbolic adjectives that usually signal a weak argument, collecting a small number of examples to claim Trustpilot actively courts fake negative reviews to bully businesses into paying for subscriptions; a “pay-to-play” racket. The examples provided weren’t representative of Trustpilot’s size: 330 million active reviewers and 60 million monthly active users.

Trustpilot responded within hours,

“The Report presents a series of claims that are selective, misleading and framed to support a predetermined narrative. It omits key context and publicly available facts, creating a false impression and exhibits a lack of understanding of how Trustpilot works. Trust is our guiding principle and is central to everything we do.”

More importantly, the directors put their own capital on the line. CEO Adrian Blair, Chair Zillah Byng-Thorne, and CFO Hanno Damm all bought shares in the immediate aftermath. This further signalled confidence in the business.

The Trustpilot response offers a textbook study in strategic communications during a crisis of confidence. The temptation, when accused of being a “mafia” operation, is to shout. As I wrote earlier, one wants to issue a 50-page line-by-line rebuttal. But the strategic communicator knows that to do so is to grant the aggressor the status of a peer. By responding to every point, you legitimise the claims. You accept the premise that you are on trial.

Trustpilot avoided this trap. They denied the central thesis with brevity and then went back to work. The share purchases were the real communication.

In my own experience, the most vital lesson is to distinguish between the noise of the market and the signal of the business. The short seller relies on the “short and distort” tactic: take a kernel of complexity (e.g. Trustpilot’s open platform allows anyone to post, which naturally includes some bad actors), strip it of context, and present it as a systemic fraud.

The antidote is not to argue the complexity, but to demonstrate the simplicity of the value. Trustpilot is the standard for online trust; if it were truly a criminal enterprise, one suspects its millions of users and the scrutiny of the London Stock Exchange might have noticed before Grizzly Research arrived.

Trust is reputation, especially when it’s in your name

The Trustpilot share price has already begun to rebound, suggesting that the market’s immune system is functioning. Trustpilot plays a significant role in portraying the perceived reputations of companies in Google Search and in Generative AI results – so this crisis strikes at the heart of their business model.

The long-term imperative for Trustpilot is to further shed light on how they operate, work to correct bad actors seeking to manipulate the platform, and demonstrate that businesses that pay receive support but not manipulation. Trustpilot is a business well-positioned for sustainable growth, even more so given how Generative AI is changing online journeys.

… and in case you’re wondering, Trustpilot is not a client. Well done to their communications team and any agency that may have been supporting.

The report (found in full here) is based on surveys conducted between August 2024 – November 2024, across a representative sample of 1,004 journalists. It would be fair to assume that these numbers have only increased 12+ months later, and this may be an indication of global usage as well.

I’ve read through the report and pulled out the main bits that struck me as a communications professional.

A quiet revolution

AI’s integration into journalism is not just about flashy headlines or deepfakes. The most common uses are surprisingly practical: transcription, translation, grammar checking, and copy-editing. Nearly half of UK journalists use AI for transcription or captioning at least monthly, a third for translation, and 30% for grammar checking. But the technology is also creeping into more substantive areas such as story research, idea generation, headline writing, and even fact-checking.

This means that Gen AI is responsible for shaping the reputations of the entities we represent. It’s a profound shift, as typical online communication is about searching for information and making a human assessment. Now that the assessment is being made by Gen AI.

It’s a double-edged sword

Newsrooms have never faced such pressure: the relentless news cycle, consolidation of media titles, redundancies, changing news behaviours, and so on. Therefore, the promise of AI in journalism is clear: faster turnaround, broader coverage, and the ability to handle vast amounts of data.

But speed comes with risk. The Reuters Institute finds that journalists who use AI more frequently are not more satisfied with the time they spend on complex, creative tasks. Instead, they report spending more time on low-level tasks, such as cleaning data and checking AI output. In other words, AI hasn’t yet delivered the creative liberation some hoped for; instead, it’s introduced new layers of technical diligence.

This means that errors, whether factual inaccuracies or misinterpretations, can propagate quickly. The margin for error is slimmer, and the window for response is shorter.

This appears generational

The research reveals that younger journalists and those with higher levels of management responsibility are more frequent users of AI. Business journalists, in particular, are leading the charge: 43% use AI professionally at least weekly, compared to just 21% of lifestyle journalists.

This generational slant matters. Senior journalists who are often the ones making editorial decisions are more likely to see AI as an opportunity, while rank-and-file reporters remain sceptical. This means that the decision-makers shaping coverage of your organisation are increasingly comfortable with AI-driven processes. Understanding their workflows and concerns is now a strategic imperative.

Trust and transparency

Despite widespread adoption, UK journalists remain deeply pessimistic about AI’s impact on their profession. A striking 62% see AI as a “large” or “very large” threat to journalism, while only 15% see it as a significant opportunity. The top concerns? The potential negative impact on public trust, the value of accuracy, and the originality of journalistic content.

Journalists’ scepticism means they may scrutinise AI-generated content more closely, raising the bar for transparency and accountability. Whether a journalist or a communications professional, there is common ground to be found in advocating for responsible AI use, clear labelling, and robust fact-checking.

AI policy and procedures

Most UK journalists report that their main news publication has established some rules or guidelines around AI involving human oversight, data privacy, and transparency. However, only 27% say their publication has guidelines around bias and fairness. Training is also patchy: around a third of journalists say their organisation provides AI training.

This means that the standards governing AI use in newsrooms are still evolving.

This is an AI future but with increased scrutiny

Journalists overwhelmingly expect their main publication’s use of AI to increase in the future. The stance of most newsrooms is supportive, with internet-native titles particularly bullish. This means that AI-driven journalism is not a fad but a behavioral shift that will transform the profession.

With greater adoption comes greater scrutiny. Reuters Institute highlights that journalists with higher levels of AI knowledge are more concerned about ethical consequences, while daily users are less so. This divergence suggests that as AI becomes more embedded, expect debates about its ethical use to intensify.

It’s time to navigate the new normal

The adoption of AI by UK journalists is reshaping the media landscape in ways that are both subtle and profound. In the past, a company’s presence in Google Search used to matter but now you need to care about how your organisation and executives are appearing across a plethora of AI platforms.

The future of reputation management is being written, quite literally, by algorithms.

I analysed all 500+ sources Grokipedia uses to build the pages of FTSE 100 and discovered:

• 36% from institutional and regulatory websites such as academic journals, governments, and legal websites. It’s these sources that contribute extensive depth to articles and are responsible for flagging disputes and other historical issues.

• 35% from official company websites and investor relations pages. These are clearly the most reliable sources and show the importance of an updated and optimised website presence.

• 29% are earned media, ranging from specialized trade press, newswire-based reporting (such as a financial update in Reuters), and international media. Notably, 99% of the sources are in English and the content referenced is publicly accessible (no paywalls).

There was no evidence of social media references or sources from paid media sources. This was a surprise to our team, given news coverage about the supposedly equal weighting given to social media sources Vs reliable mainstream.

Where there are challenges

• Attribution dilution: For FTSE 100s, the sources are blended, which can blur the line between official facts and third-party commentary (e.g. an academic or legal text may come from a detractor, but is equally weighted with a corporate or government source).

• Data decay: It’s not clear how frequently links are verified, checked for bias or if they’re still live. Like other AI platforms, Grokipedia often links deep within websites to pages that can either be out of date or removed.

• Secondary interpretation: For key metrics, Grokipedia sometimes relies on financial aggregators rather than primary filings. This introduces the risk of minor inaccuracies or misinterpretations being amplified.

• No neutral point of view: Especially for companies in geopolitically sensitive sectors, Grokipedia’s penchant for deep historical context means that old controversies are permanently embedded in the corporate profile.

What this means for communications professionals

The first step is to understand how you’re being reflected and the sources being used to inform that image. Do everything you can to manage the sources Grokipedia relies upon, such as your website and media profile, which means taking an integrated approach to communications.

Grokipedia is new, likely to grow given its financial backing and brand, but this version will never replace Wikipedia’s authority as the ‘database of the internet’. It’s an aggregator, and truth be told, one that relies on Wikipedia for its content.

It’s a godly reminder of the significance of Jimmy Wales’ achievement in founding Wikipedia and the enormous effort of volunteers to build the internet’s largest freely accessible bank of knowledge. He is one of the original internet entrepreneurs, and after the inventor of the World Wide Web, Tim Berners-Lee, I would argue the most important. After all, it was Socrates who said, “Knowledge will make you be free”.

Jimmy’s contemporaries include the likes of Jeff Bezos, Elon Musk, and Larry Page – but the philosophical mission of the Wikimedia Foundation that “open access to knowledge is a fundamental right, and a driver for social and economic development” means becoming a billionaire ‘tech bro’ was never part of the objective for Jimmy. As we now find ourselves in a world full of volatility and violence, the efforts of Wikimedia and Wikipedia have never been more important.

Trust is the currency of the internet. Especially in an online environment that has been dominated by rampant ‘AI slop’ across social media, profound misinformation and disinformation, and other traditional communications sources are at an all-time trust low… even the BBC. It can be difficult to know where to turn, but the reassuring words of Jimmy is a good start.

His new book, The Seven Rules of Trust, reveals the key principles that led to Wikipedia’s success. He kindly agreed that I could interview him at Kekst CNC to explore what building Wikipedia can teach us about managing the trust of our organisations.

Purpose, process, and people

When Wikipedia launched, it was a revolutionary idea – an open wiki that anyone could edit. It succeeded only because of a clear purpose and a consistent process.

“With Wikipedia, one of the things that’s been very helpful… is that we have a very simple purpose: to create a free, high-quality, neutral encyclopedia. And that purpose defines everything we do, and defines the work, and defines the rules, and defines everything.”

This clarity of mission is not just a branding exercise. It’s the backbone of Wikipedia’s community management, guiding decisions about what behaviour is acceptable and what is not. “Have a good purpose. That central purpose has really helped a lot, and a lot flows from that,” Jimmy explains.

But purpose alone is not enough. The process matters too. Wikipedia’s rules, such as “no personal attacks”, are designed to foster civility and constructive disagreement.

“Unlike in social media, where personal attacks are kind of, like, what most people think it’s for, right? We said, no, no, no, you shouldn’t… we shouldn’t be attacking each other, you shouldn’t be attacking even people we’re writing about… it’s just not what we’re here for.”

This approach is not without its challenges. Jimmy is candid about the difficulties of managing a large, diverse community.

“The hard part is the person who is a really good contributor in terms of contributing good quality content, and they’re being massively rude to a bunch of people… At some point, you just have to say, yeah, look, sorry, if you can’t stop attacking people, you have to leave.”

Forgiveness and second chances are part of the culture, but so is accountability. “You shouldn’t get blocked or banned from the website for your first transgression, so there’s a lot of forgiveness… but there’s also a social expectation… if you’ve been horrible, you should apologise.”

Evidence and neutrality

If trust begins with purpose and process, it is sustained by evidence and neutrality. Jimmy is a stickler for reliable sources and balanced presentation.

“Read up on what counts as a reliable source… how you can manage to say, actually, this is an error, or this is not the full story… the typical kind of case would be, like… this is a criticism that’s out there, but you haven’t mentioned the company’s response, which was published here. That needs to be incorporated, and usually that gets pretty good results.”

He is clear-eyed about the limits of reputation management though.

“It’s not somewhere I’m going to be able to turn this into a PR puff piece, but I can make sure that if there’s facts, they’re presented correctly, there’s two sides of the story, we’ve got both sides, all that kind of stuff. That’s kind of the best you can do...”

This commitment to neutrality extends beyond Wikipedia to the wider media landscape. With large amounts of polarisation, Jimmy argues, the restoration of trust depends on a return to “old-fashioned journalistic neutrality, objectivity.”

AI tokens, hallucinations, and attribution

No conversation about trust in 2025 is complete without a discussion of AI. Jimmy is both fascinated and wary of the technology’s impact on knowledge and credibility.

He offers a technical critique of how Generative AI works:

“The way that it works is it’s always choosing the next token or the next word to be the most probable word, with a little randomness thrown in, which is why it gives different answers at the right time. And so, writing the most plausible thing isn’t the same thing as writing the most true thing, and so what you get is hallucinations. It goes down a path, and then it just keeps making stuff up because it sounds plausible and great, and it’s just completely wrong.”

He is adamant that AI is not yet ready to replace human editors. Whilst AI can write text that sounds convincing, it’s not the same as writing factually correct articles. The immediate opportunity for AI is to support but not supplant human judgment.

“I’ve written a little program… I feed in a short article, and I feed in the five sources, and I ask the question, is there anything in the sources that isn’t in Wikipedia, but should be? Or is there anything in the Wikipedia entry that is not supported by the sources? And it’s actually kind of okay… If a human could check it, like, that could be quite interesting, and it could help our community be more productive and so forth.”

But the risks are real. “The Wikimedia Foundation shouldn’t be using AI to produce content that’s shown directly to readers without humans checking it first. Because the risk is so high, because we’re quite particular about how things are done.”

Economics of trust

The rise of AI has not just changed how information is produced, but also how it is consumed. Jimmy is frank about the impact on Wikipedia’s traffic and infrastructure. “... there was a blog post recently that we’ve seen an 8% decline in visits from humans. That doesn’t mean a decline in traffic... we’ve seen an increase in visits from bots. So that’s concerning, but not, like, a panic case.”

The proliferation of bots crawling Wikipedia has real costs.

“The AI companies are crawling Wikipedia quite heavily, and it’s not just the big ones, but all kinds of startups and things like that. And they’re hammering our servers… So it turns out it’s a disproportionate hit on our costs, and because we’re a charity…”

For Jimmy, the key is attribution. “Our business model, we’re a charity business model, is not page views or ads. So losing page views doesn’t really matter. What matters is, as long as the public knows the information comes from us. In cases where they don’t know, you know, like, that would be a sad outcome.”

Anonymity and pseudonymity

Jimmy’s views on identity in online communities are nuanced and practical.

“In Wikipedia, when you go to sign off in Wikipedia to create a username, username can be anything. JoeBob123 or whatever, and people go by that. There’s a really very well-known Wikipedian called New York Brad. He’s one of the most respected Wikipedians. I happen to know he’s a partner in a law firm in New York, and his name is not Brad. But he’s a great guy. And people don’t know his real name… But the point is, he edits under the same identity. And so, in Wikipedia, your pseudonym is your reputation.”

Reputation is earned through consistent behaviour. “People do want to build a good reputation, because if you don’t have a good reputation, people don’t listen to you, and they get reverted, and so on and so forth.”

He distinguishes between pseudonymity and anonymity. “In some contexts, I think a real names policy is super important. So one of the examples, the case study in the book, is Airbnb… That’s an area where real names and real identity really matters. In other contexts, pseudonymathy is enough, as long as you’ve got a reputation that builds over time.”

He is critical of true anonymity, especially on platforms like Twitter (now X).

“Most of the times, if I go on… I post, it doesn’t matter what you post, so if I look, here’s my recipe for chocolate cake, you know, somebody’s gonna yell at you. Typically, I’ve never heard from them before, I’ll never hear from them again… When somebody’s behind an anonymous shield. They can be a juror for whatever reasons motivate them, and that’s that. And you’re never going to see them again, and it’s toxic.”

Trust as a collective endeavour

Jimmy’s reflections remind us that trust is not a static asset, but a dynamic process - built through purpose, process, evidence, and engagement. With the growth of AI and increase polarisation, the challenge is not just to find trustworthy sources, but to become trustworthy ourselves. Whether you’re a journalist, a communications professional, a business leader, the lessons from Wikipedia’s journey are clear: clarity, civility, evidence, and openness are the pillars on which trust is built. The rest is up to us.

They recognised that effective online communications is achieved by engaging online content and community discussion. This drew criticism from Lawrence Lessig, an internet theorist who criticised this closed model as a threat to the open nature of the internet. Although AOL’s 14,000+ network of volunteer editors and moderators could be seen as akin to an open-source movement, this was 5 years before Wikipedia launched in 2001.

It wasn’t until the late 2000s – 2010 that AOL began hiring hundreds of journalists, editors, and videographers to support its “content-first” business model, using data-led strategies to inform editorial decisions. The insights, strategies, content approaches, and measurement have arguably influenced how firms run their online marketing and communications to this day.

Gen AI and bots are changing the internet

It’s a strange coincidence that at the same time AOL closes its dial-up service next month, we’re seeing the online communications formula it started also reaching a transformative phase, caused by bots and changing search behaviours.

There are now an alarming number of bots on the internet. The cybersecurity company Thales latest report shows that bot traffic has now surpassed human traffic. Many of these bots are useful, enabling reputable services to run by crawling, monitoring, and scraping online content. Generative AI platforms deploy the likes of AppleBot and ClaudeBot to source references for responses. It’s part of a growing Bots-As-A-Service (BaaS) commercialisation of the internet.

Parallel to the bot boom is a behavioural shift in human search behaviour. According to Bain & Company, 60% of Google searches now end without a click, and 80% of people rely on “zero-click” results in at least 40% of searches. Since the publication of this report, Google has also launched AI Mode that will further drive behavioural change. Pew Research states that a worrying 26% of people end their browsing session entirely after viewing an AI summary.

This commercial impact feels like a betrayal by Google

The impact is being felt by business, especially when it comes to shaping online reputations. Only one company I’ve spoken to in the last 6 months has claimed ChatGPT is an important referral source for their business, but I do wonder if this has been filtered for bot activity.

Google will argue that traffic is being redistributed to high-quality online sources like forums and videos. For companies, this redistribution can feel more like erosion, and means shaping narratives and pushing marketing requires a revised approach. Online publishers have reported traffic declines of 70% or more, and behind the scenes, corporates are trying to understand how to best adapt to this new search landscape.

Ironically, companies that have well-optimised ‘traditional’ traffic model websites may be feeling the pain the most. A successful content strategy will likely lead to bots crawling the website effectively and serving results to Gen AI. Whilst this may mean messages are still reaching audiences, companies that need this website traffic for conversion may see a loss of visibility, engagement and revenue (which is why publishers have been so vocal).

Transform or be left behind

It means your online communications strategy needs reviewing fast, as the progression of Gen AI will correlate with how companies and executives are profiled online. In the short term identify how bots could be distorting your analytics, what your latest audience preferences and journeys are showing, and use insights to inform your active communications strategy.

AOL’s transition from a tech utility provider to a content hub was a masterclass in engineering the internet for human experiences. In these times of change, it’s worth considering what AI can’t offer. Perhaps that’s an experience…

The post More bots and fewer clicks: why your communications strategy needs rethinking appeared first on White PR.

It has meant that the first page of Google is no longer the only space where reputational perceptions are shaped. Gen AI means that editor discrepancy and choice is not accounted for as responses come without human oversight. Information is bundled together from a variety of online sources – sometimes even confidently hallucinated – to shape narratives to audiences actively seeking information. Gen AI’s influence on reputation management cannot be ignored.

If you want to manage how your brand, executives, or products are being perceived in Gen AI responses, then here is some guidance:

Reputation management is multichannel

If the link is public and crawlable, then Gen AI can see it. Google Search’s index still matters, but unlike the first page of Google’s results, Gen AI digs deep into websites to reveal potentially relevant information. Think Wikipedia, Reddit, corporate websites, international, local and trade media, niche blogs, YouTube, TikTok – the list feels endless. It means reputation management in 2025 must be multichannel as the days of addressing one Financial Times article (for example) are over.

Source diversity will dig up the past

The diversity of sources is both a blessing and a curse. It means that well-structured, up-to-date owned content such as FAQs and thought leadership can surface in Gen AI responses. However, it also means that negative or inaccurate information, even if a historic issue, is resurfaced for the world to see long after it has faded from the news cycle. Watch out for how divisive issues are referenced in diverse sources as this may be impacting audience perceptions.

Daily volatility impacts source weighting

Managing how Gen AI responds to prompts has required the development of a reputation management framework. It recognises that whilst there is a weighting behind the sources used (like a page rank), the volatility is driven by the dynamic nature of Gen AI sourcing. For instance, the prevalence of a negative news article can be de-weighted as a source but can be replaced by another even if from a social platform like Reddit. There isn’t a journalist or editor you can phone about this issue, only a data-led strategy can rectify.

Silence isn’t a strategy

“Let’s wait and see if this goes away” doesn’t apply to Gen AI. Certain reputational issues may require a direct response, with attempts to ignore or bury controversies unlikely to be successful. Fact-based, well-structured responses, published strategically, will often lead to a balance to topics rich in reputational significance. Arguably, this is why audiences like Gen AI, because of its ability to search through the noise of traditional search results to reveal. However, it does completely change the considerations behind reputation management decisions. Good practice means reputation should be handled transparently and directly, offering Gen AI useful content to inform responses.

Volatile responses require daily monitoring

Over the last 12 months, there has been a rush by global communications tool providers to offer accurate and reliable monitoring across Gen AI platforms. History shows us that communications professionals were slow to adopt Search Engine Optimisation (SEO) techniques in comparison to marketing disciplines. However, the same can’t be said in 2025, as tracking Gen AI in turn requires an AI-powered solution to track.

For all of Gen AI’s technical sophistication, our underlying lesson is a human one. Reputation is not only shaped by public opinion, but by what Gen AI chooses to surface. The most successful communicators will be those who understand the science behind Gen AI, the art of storytelling, and have the empathy to understand what is really impacting audience perceptions and behaviours.

The post Gen AI’s influence on reputation management shouldn’t be underestimated appeared first on White PR.

The research includes 4,164 business leaders across eight markets (France, Germany, UK, Sweden, Japan, Saudi Arabia, UAE, and US) and reveals how senior decision makers prefer to consume their news, use social media, and engage broadly with digital communications channels. It confirms anecdotal feedback from professional communicators that the online landscape continues to shift and that communications strategies must adjust accordingly.

Whilst 74% of business leaders still read physical newspapers and magazines, 80% confirm daily reading of online news and 88% use social media daily. The top used social networks during 2024 were:

When comparing the growing use of TikTok with LinkedIn, the expected generational differences between higher usage by millennials VS Gen X is true for both platforms. Data shows that TikTok usage is highest in Saudi Arabia, US, and UK, whereas LinkedIn usage is high across all countries especially France, Germany, and the UK.

This aligns with a growing preference for video content as 89% watch videos on mobile devices and 46% prefer short videos (defined as under 10 minutes). This is a mobile-first audience.

What does this mean for communicators?

• Refresh your audience research: If this hasn’t been done over the last 12 months, this needs sense-checking based on the quickly evolving digital landscape.

• Adjust your strategy: Especially to make sure your communications work in a mobile- first world, consider growing social networks, and using different content formats.

• Be personal and professional: LinkedIn still holds an important place as a professional social network, but don’t be limited by it – senior business leaders are more active on personal social networks.

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What are community notes?

This moderation used on X was designed in 2020 to emulate professional fact-checking. It relies upon social media engagement around content to invite everyday users to check whether a claim is factual. Practically, tweets on X often appear with a fact box underneath to provide a summary showing the credibility of the content.

Despite its launch on X five years ago, there is nothing new about using the power of communities on social media to assess the credibility of content. It’s akin to a ‘Web 2.0’ peer-review process, and Wikipedia is the best-known crowd-sourcing project that relies on this type of collaborative truth searching.

Do community notes work?

Off the back of Meta’s announcement in January 2025 that it would replace professional fact-checkers with Community Notes, The London School of Economics published an article about the accuracy of this crowd-sourced approach. It referenced research that verified:

1.     Community notes are found to have a 97% accuracy rating.

2.     This form of fact-checking system does work on X, leading to an 80% chance that the perpetrating author deletes their original tweet.

3.     … unfortunately, community notes are slow to verify information and often aren’t used.

In practice…

Modern social media algorithms are designed to show us what we want to see and engage with, leading to tribes connected by common ideologies. The best social networks do this effectively, often driving tension and conflict between communities. In practice, this means that community notes can be ineffective due to the lack of different perspectives.

For example, during the Los Angeles wildfires, a conspiracy-oriented X account baselessly claimed that authorities started the fires to destroy evidence of underground child-trafficking tunnels. The tweet posted on 9th January 2025 has 4.3 million views but still doesn’t have a community note.

What does this mean for professional communicators?

The role of the corporate website has re-emerged as your source of truth – invest here to ensure your story is heard without manipulation or influence.

It’s never been more important to track mentions of your brand and executives across multiple communications channels to protect your reputation.

The partisan leanings and nature of social networks should be considered before any engagements, especially as independent fact-checking is decommissioned.

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Organisations have never been more focused on developing a model of resilience to navigate the complexities and dangers of this fast-turning ‘zero trust’ media landscape – why should anyone trust anything?

In 2022, the risks presented by misinformation and disinformation were not understood in the mainstream. The narrative quickly shifted this year as the World Economic Forum (WEF) included these threats for the first time in its annual risk report. They’re a top 10 risk and are considered the biggest threat facing the world in a landmark election year.

The public availability of Artificial Intelligence (AI) technologies has certainly informed WEF’s risk ranking. In recent months we’ve seen an AI-generated video impact Zara, ‘leaked’ fake audio footage of London Mayor Sadiq Khan claiming that Armistice Day events should be postponed for a pro-Palestinian march, and fake harmful images of Taylor Swift lead to global condemnation.

If I ask you to think of a social network at the heart of misinformation spread, then you’ll probably think X/Twitter following the business’ turbulent transformation and the likes of Foreign Policy magazine calling the network “… a sewer of disinformation”. Contrary to this, the journalist investigators at NewsGuard have recently identified YouTube as a Russian disinformation incubator.

In just six months, NewsGuard identified seven viral false claims about Ukraine that were seeded on anonymous YouTube channels before spreading further. Claims included that Ukraine had assassinated a journalist and false narratives connected to President Zelensky. These are not harmless online narratives but instead details that have been referenced as truth by members of U.S. Congress before.

Typically businesses have been slow to respond to risk and instead react once a crisis hits, although perhaps even this is changing. Rebecca Pardon in Communicate Magazine evidences the collapse of Silicon Valley Bank – so-called the “first Twitter-fuelled bank run” – to show many organisations are still ill-equipped to deal with social crisis and misinformation spread. Detecting manipulated content is fast becoming a hygiene requirement of managing communications.

As the timeliness of this new article suggests, the bulging deluge of harmful content created and shared online is keeping us busy at Kekst CNC. To remain at the forefront takes serious time and investment, which is partly why our parent company Publicis has announced its €300mn AI strategy investment. We’re on the same journey.

The post Misinformation recognised as a major threat to governments, businesses, and society in 2024 appeared first on White PR.

If you look a bit deeper though, an estimated 214 of these profiles were part of a bot network. Together, they were responsible for 169,000 posts on X – that’s a whopping average of 789 posts per profile.

Beyond social media, NewsGuard ratings reveal that 1,537 websites mentioned COP28 are known for publishing false information in the past or not fully disclosing ownership or advertising.

Combined, X and online news analysis reveal the following damaging narratives were circulating during COP28 and the subsequent negotiations:

1. Criticism of COP28 itself. Many tweets and articles suggest that the conference is dominated by oil producers and does not adequately address the climate emergency. It’s a mainstream concern, given the COP28 President is Al Jaber who is the CEO of UAE’s National Oil Company Adnoc, and an issue very publicly flagged by Al Gore this year. However, it’s important to note that the conference is also attended by representatives from a wide range of countries and industries, including renewable energy companies and environmental organizations. Fundamentally, it’s an event that must focus on an energy transition. To dismiss the entire event as a “Cabal of Oil Producers” is to oversimplify a complex and nuanced issue.

2. A prevalence of conspiracy theories and globalist agendas. Headlines suggest hidden motives or agendas behind the conference, such as globalist control and manipulation. This kind of thinking can lead to mistrust and polarization, contributing towards a zero-trust environment that makes it challenging for anyone to believe anything and for companies to communicate their efforts.

3. Misrepresentation or distortion of facts. With certain publications presenting misleading or inaccurate information related to climate change such as “climate change is not threatening human health”, despite overwhelming evidence to the contrary and the inclusion of the topic in the COP agenda for the first time in recognition of this fact. This kind of misinformation can be harmful, as it undermines efforts to address the very real and pressing issue of climate change. It also calls into question the motives for such an article to appear and whether it was state or corporately-backed.

4. Biased or one-sided reporting has appeared. For example, an article titled “Fossil Fuel/COP28: Where Fossil Fuel Industries Go to Gloat” clearly has an agenda against the energy industry and doesn’t present a balanced view of the conference.

5. Attacks on credibility and authority has been another damaging trend. Headlines that undermine the legitimacy of individuals, organizations, or events associated with the conference can be damaging and counterproductive. For example, one article criticises UN Secretary General Antonio Guterres for declaring that fossil fuels must stop being burned because it would “destroy the lives of billions of people” and is “anti-human, anti-progress, and extremely disturbing…”. This kind of rhetoric only serves to further polarize the conversation and distract from the real issues at hand.

The role of bots on X acted to increase the spread of such articles and like-minded content. The online discourse around COP28 reveals a troubling trend of misinformation, mistrust, and polarization. For businesses, COP28 further shows that misinformation is a mainstrea

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Predicting the twists of human affairs, much like AI itself, is no straightforward endeavor. The recent spectacle at the UK’s AI Safety Summit held at the historic Bletchley Park epitomizes this unpredictability. The US proclaimed an executive order on AI regulation and the establishment of its very own AI safety institute right on the inaugural day of the UK’s summit. This audacious move boldly reaffirms the US’ commitment to self-regulation, as it reaffirms its dominance as a leader.

During the summit, the US Vice President, Kamala Harris asserted in London,

“… when it comes to AI, America is a global leader… it is America that can catalyse global action and build global consensus in a way that no other country can.”

The domain of AI has become a fierce battleground of political and economic dominion. In comparison, the UK’s summit did something that no leader has done before – traverse geopolitical tensions to bring a diverse group of leaders from countries, companies, and academic institutions, to agree an international pledge to manage AI harms.

This momentous gathering culminated in the signing of ‘The Bletchley Declaration,’ gathering support from 28 countries and the European Union, and, remarkably, even China. Nevertheless, skeptics remained, dismissing the declaration as a symbolic gesture bereft of tangible enforcement mechanisms.

Deep-seated challenges of AI regulation persist, spanning the realms of genuine international collaboration, the compilation of a comprehensive global inventory of recognized harms, the synchronization of regulation with the relentless march of technological innovation, and, not the least, crafting economic solutions to address the transformation of the labor market. The catalogue of obstacles is vast, and for a more in-depth analysis, check out my previous blog post.

The Financial Times’ Stephen Bush described the summit’s outcome as,

“… any prospect that the UK can be a world leader in that field and not a mere convener of talking shops is a bit of a fantasy, so: failure…”

Nations and corporations shared their opinions and positions. From the doomsday prophecies of Elon Musk, foretelling an AI-driven job apocalypse, to the slightly more optimistic musings of Nick Clegg, who believes that existential fears were being exaggerated – the spectrum of views was wide. Musk’s presence, for some attendees, bordered on the distracting, with his cataclysmic warnings often drowning out nuanced discussions, thus contributing to a sensationalized narrative.

Meanwhile, as the world’s elites grapple with the profound implications of cutting-edge AI technologies, companies continue to confront the daily challenges posed by AI’s relentless march.

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