AI in comms has moved past the prompt box. So why is the tool market still selling us the old model?
What decides who wins from here isn't the model. It's the data, the workflow, and who trains the next generation.
Six months ago, if you’d asked most communications teams how they actually used AI day to day, the honest answer was narrow: to help draft something. A media release, an email, a first pass at a line for a chief executive's LinkedIn profile. Useful, but it was a text box.
Then something changed. Communications professionals realised that the ability to speak with computers as a human opened up new possibilities. Whilst enjoying my pint of Badger ale with a tech founder of a successful synthetic audience scale-up last night, he explained the transition in the tool provider landscape simply: “The value is no longer in the software licensing; it’s the resulting advisory”.
Barriers to software creation have lowered, as my own launch of my iOS app Inkline showed. An idea to create an app to help people who work in the media cut through the noise of news, coupled with my knowledge of technology and coding, turbo-charged an Apple-approved app. Yes, it has value; usage numbers show this, but the barrier to entry is lowered.
The view from the foothills
But the speed of innovation varies, as evidenced in The European Communication Monitor, the discipline’s largest annual survey of senior practitioners. The last report found that chief communications officers at Europe’s biggest companies describe their own organisations as being, in their words, in the “foothills” of AI adoption. Use is cautious and fragmented, driven from the bottom up by a handful of enthusiasts while the people at the top watch.
So what I’ve been feeling firsthand is the front edge of a shift rather than the shift itself.
What the research does confirm is the shape of the problem. Stephen Waddington’s review of the sector points to a Communication Management Radar in which three of the five biggest emerging issues in the field this year are AI issues:
How much of what we read online was written by a person at all. Up to 60% of web traffic is now machine-generated.
Who carries accountability when an agent, rather than a person, acts on an organisation’s behalf.
Whether relying on these tools is costing practitioners their own judgement without them noticing.
None of that is a prompting problem. These are governance problems, and the PRCA’s AI Green Paper has landed on human oversight as the one principle the industry can currently agree on, which tells you how early we still are.
What that does to the tool market
Assume the front edge keeps moving. If a well-resourced team can build and run its own monitoring and alerting, scheduled and tuned to exactly what it needs, that is a different negotiation with vendors who have spent two decades selling exactly that as a subscription.
From what I can see, the market is splitting three ways.
The established tool providers are layering AI capabilities to the data and dashboards they already own. At the same time, trying to make that useful and economically viable given the climbing token costs.
A newer category of AI-native platforms has grown since 2024, built around autonomous agents rather than a dashboard with AI attached. They are finding their place in an established market where investment scale and networks win- most of the time- over innovative ideas.
Then you have a third category - goliath brands who have attempted AI integration, but their slowness to respond to changing markets is impacting their bottom line. Perhaps the newer category of AI-native platforms will take their place? Or perhaps the market share being lost will be allocated to the communications teams’ builders who know exactly what they need.
Data is the moat, not the model
Underneath the tooling argument sits a bigger question about data, and it’s worth looking at what the AI companies themselves have been paying for this year. OpenAI’s deal with News Corp, reported at $250 million over five years, remains the largest known content licensing agreement in the market. It has been followed by a steady run of others: Meta signed with Le Figaro, Prisa and Süddeutsche Zeitung in March, OpenAI added its first Brazilian media partnerships in May, and OpenAI alone now holds roughly two dozen publisher and data agreements.
When the best-funded companies on the planet pay hundreds of millions for licensed access to particular archives, that tells you where the scarce resource sits. Models get cheaper and more interchangeable by the month. Verified, licensed access to good source material does not.
It’s the same with communications agencies. On LinkedIn, the smaller players will perhaps publish interesting studies, but ultimately, it’s only the well-funded big brands that have the scale to license, build and maintain a depth of source access useful for reputation management.
Scale was always an advantage in this industry. AI hasn’t touched it, and has arguably made the depth of what you are legitimately allowed to see the whole game.
The talent tension
As the relationship between tool providers and communications teams shifts, so do the expectations of talent.
Again, I find myself indebted to Stephen Waddington’s mid-year review for pulling the evidence together. He points to a systematic review of 28 studies on the European public relations workforce which found entry-level and mid-level roles being hollowed out. Set against that, he cites the European Communication Monitor finding the opposite happening one level up: AI raising the value of experienced practitioners specifically, as their work moves from production to judgement.
Both are true simultaneously. The skill that matters most is becoming scarcer at exactly the moment the traditional route into acquiring it, doing the mechanical entry-level version of the job, is automated away first.
My own place in this industry puts me at a strange juncture. I started programming around 2005 and seriously considered reading computer science before I found my way into communications instead. Since 2008, those technical skills have been a natural part of the advice I give clients and the work I actually do for them. Now that everyone can talk to computers, they have never been more useful. The good news is that you no longer need to work through books on PHP or C++ before bed. You can learn it while coworking alongside your agents.
However, if the industry reacts too quickly by reducing the amount of junior talent they take on without plans for future succession management, they will lose more than just their budget on AI tokens.
Where I’ll leave it
Most of the industry is still in the foothills. The direction of travel isn’t in serious doubt: we’re moving from renting tools to owning the workflow, and, slowly, from paying for headcount to paying for licensed access instead. Whether your own organisation is near the front of that queue or still lacing up its boots is worth finding out before somebody else answers it for you.