In 2023, researchers at MIT and Stanford published findings that should have restructured how every communications leader thinks about their function. Across a series of controlled studies examining AI-generated versus human-written content, readers consistently failed to identify which was which. By standard quality metrics — clarity, structure, readability, grammatical precision — the machine had arrived. The communications industry’s response was divided between alarm and dismissal. Both responses missed the point.
The point is this: writing and communicating are not the same activity. Writing is the arrangement of words into coherent sequences on a given topic. Communication is the deliberate construction of specific meaning in the mind of a specific audience. AI has mastered the first. It cannot approach the second. And the reason this distinction is now existentially important for every organisation with a brand to build and an audience to reach is that most organisations have spent decades optimising for writing when the asset they actually needed was communication
The evidence for this was accumulating long before generative AI entered the conversation. The Edelman Trust Barometer, which has tracked public trust across 28 countries annually since 2001, found in its 2024 edition that 57 percent of respondents globally reported difficulty distinguishing reliable from unreliable information. That figure has risen every year since 2017. The flood of AI-generated content that entered the internet from late 2022 onward has accelerated this trajectory significantly. The conclusion is not that there is too little content in the world. The conclusion is that content, as a strategy for building credibility and earning trust, is broken. The more content that exists, the less any individual piece of it means.
Seth Godin identified the structural limit of content-as-communications a full decade before it became urgent.
Seth Godin identified the structural limit of content-as-communications a full decade before it became urgent. In Tribes, published in 2008, he argued that the scarcest resource in an attention economy is not information but meaning. “People don’t believe what you tell them,” he wrote. “They rarely believe what you show them. They often believe what their friends tell them. They always believe what they tell themselves.” What Godin was describing, writing before generative AI was a household term, was the fundamental ceiling of content as a strategic approach. Content can reach people. It cannot move them. Movement requires meaning. Meaning requires something that production cannot generate: clarity about what you stand for, arrived at through genuine strategic thinking, and expressed in language that is specific enough to resonate rather than broad enough to be forgotten.
The psychological dimension of this problem is even more challenging than the strategic one. Rory Sutherland, Vice Chairman of Ogilvy and author of Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business and Life, makes an argument that cuts directly at the failure mode of most communications strategy. Sutherland contends that organisations consistently optimise for rational persuasion — presenting evidence, articulating features, explaining logic — when the actual mechanism through which humans form trust and develop preference is not rational at all. “The problem with logic,” he writes, “is that it misses what makes things meaningful to people.” The implication for communications in an AI-saturated environment is direct: a world full of logically coherent, well-structured content does not produce engaged audiences. It produces audiences who have become expert at scanning content and immediately sensing whether it has genuine conviction behind it or whether it is, as one researcher described AI-generated text, “statistically plausible but experientially hollow.”
McKinsey’s 2023 research on the relationship between brand positioning and business performance found that companies with clear, internally aligned positioning outperformed their sector peers on revenue growth by an average of 20 percent over a five-year period. The research did not attribute this to communications spend, campaign sophistication, or social media reach. It attributed it to what McKinsey called positioning clarity: the degree to which an organisation could articulate, in precise and distinctive terms, the specific value it offered and for whom it existed. The commercial conclusion is uncomfortable for organisations that have treated positioning as a marketing exercise: clarity is a measurable business asset, not a communications preference.
What this means in practice is that the question most organisations are asking about AI and communications is the wrong question. “How do we use AI to produce better content more efficiently?” is a production question. The strategic question is different: “What do our target audiences currently understand about us, and what do we need them to understand?” The distance between those two answers is the communications problem. No AI tool is designed to measure that distance, understand why it exists, or close it. That requires human diagnostic work: the kind of structured inquiry into how an organisation is perceived versus how it needs to be perceived that most organisations have never undertaken with genuine rigour.
The test worth running on any communications programme is this. Stop it for sixty days. Go quiet. Then ask: if our most important potential client or partner encountered only our publicly available communications over the past year, would they understand precisely what we believe, precisely what makes us different, and precisely why working with us serves their most important strategic objectives? If the honest answer is no, the problem is not content volume. It is not production quality. It is the absence of positioning clarity, and that is a problem that cannot be solved by generating more content, however sophisticated the tool generating it.
This is not an argument against using AI in communications. Used correctly — to synthesise research, test messaging variants, analyse competitor positioning, and produce first drafts for strategic refinement — AI tools are genuinely valuable. The point is the sequence. The organisations winning in this environment use AI for execution after they have done the strategic thinking that gives execution meaning. The ones losing use AI to produce more output before that thinking has been done. In an environment already suffering from a crisis of information trust, more output without more strategic clarity is not a solution. It is an acceleration of the problem.
The organisations that will define the next decade of communications are not the ones with the most sophisticated tools. They are the ones that treated the arrival of AI as a forcing function for strategic clarity. They recognised that when execution becomes a commodity, the only remaining competitive advantage is knowing with precision what to execute and why. They invested in building meaning infrastructure — the articulation of what they stand for, for whom, and why that matters — before investing in the channels through which that meaning travels. AI can write your content. What it cannot do is know why your content should exist. That knowledge belongs to the people who built the organisation, understand its purpose, and have done the work of translating that purpose into language that moves the people who need to be moved by it. In 2025, that knowledge is not one advantage among several. It is the whole game.
The organisations that are genuinely pulling ahead on this dimension share a set of practices that are instructive. They do not begin communications planning with a content calendar. They begin with what strategists at the brand consultancy Wolff Olins have called a “meaning audit”: a structured inquiry into what the organisation currently stands for in the minds of the audiences that determine its success, compared to what it actually needs to stand for to achieve its strategic objectives. The gap that exercise reveals is rarely comfortable. It is always useful. It transforms the communications brief from “produce more content” to “shift specific perceptions, in specific audiences, over a specific timeframe.” That is a brief that AI can help execute. It is not a brief that AI can generate.
Apple, under Steve Jobs, offers the most frequently cited example of an organisation that understood the primacy of meaning over content. Apple’s “Think Different” campaign of 1997, which Jobs personally championed on his return to the company, was not, on any conventional measure, a product communications campaign. It made no product claims. It cited no specifications. It showed no computers. What it did was articulate a meaning: Apple is for the people who believe that a single individual with a bold idea can change the world. Every product launch, every store design, every keynote address for the following fifteen years was an expression of that meaning. When Apple introduced the iPod, the iPhone, and the iPad, they did not need to explain who Apple was. The meaning was already established in the minds of the people who mattered. The product was simply the latest proof point of a story already believed.
The practical implication for any organisation building communications infrastructure today is that the first investment is not in a tool, a platform, or a hire. It is in the clarity work: the precise articulation of what the organisation stands for, who it stands for it with, and why that position is both genuinely true and genuinely distinctive. This work takes weeks, not months. It produces a document that is typically no longer than four pages. And it is worth more to the organisation’s communications programme than any campaign budget, because every subsequent communications decision, from the website copy to the investor pitch to the media strategy, flows from it with coherence rather than being decided in isolation.
The AI revolution in communications is not, ultimately, a story about technology. It is a story about what happens when execution becomes abundant. When execution is scarce, organisations compete on who can produce the most. When execution is abundant, organisations compete on who can think the clearest. The communications profession is at the inflection point between those two competitive eras. The organisations that recognise this, and invest accordingly in the thinking that technology cannot replicate, will not merely survive the transition. They will define the standards that everyone else spends the following decade trying to reach.
