Every serious organisation is using AI for strategy. That is precisely the problem.
If you are a senior executive or expert who has invested in AI capability over the past two years, the expectation was reasonable. Access to faster analysis. Better informed decisions. Strategic insight at a fraction of the previous cost. A genuine edge over competitors who had not yet moved as quickly.
That expectation deserves a direct challenge.
The analysis AI provides is not proprietary. The frameworks it applies are not original. The strategic options it surfaces are not exclusive. Every serious competitor in your market has access to the same capability, at the same cost, producing substantially the same output.
What felt like an edge is rapidly becoming the baseline. And baseline is another word for no advantage at all. Unless organisations respond in a very specific way.
This is not a criticism of AI. It is a structural observation about what happens when a powerful analytical tool becomes universally available simultaneously across an entire competitive landscape. The tool does not create advantage. It equalises the floor.
This observation applies specifically to the large language models currently driving most strategic AI adoption. More ambitious developments are in progress and the landscape is moving fast. But the tools most organisations are deploying for strategy and analysis right now are, by design and by architecture, consensus machines. They produce output consistent with the weight of existing published thought. Powerful, fast, and extraordinarily capable within that constraint. But consensus nonetheless
The pattern has been here before
This dynamic is not new. It has played out before at significant cost to the organisations that did not see it clearly enough in time.
For decades, the major strategy consultancies sold analytical frameworks and strategic recommendations to the largest organisations in every major sector. The fees were substantial. The process was rigorous. The advice was prestigious. And it was, simultaneously, being delivered in substantially similar form to every significant competitor in the same market.
The organisations at the top of major sectors were all receiving the same strategic thinking at the same time. The result was not competitive advantage. It was sector-wide conformity dressed as strategy. The playing field was not levelled. It was frozen. And the organisations that disrupted those sectors almost never came from the top of the market. They came from the edges, from smaller players who could not afford the consensus and were therefore forced to think originally.
That is the pattern worth understanding right now. Because AI is replicating it at a different scale and at a fraction of the cost.
What smaller organisations are missing
For a senior leader in a smaller or mid-sized organisation, AI represents something genuinely exciting. Access to the kind of analytical horsepower that was previously available only to the largest players with the largest budgets. A chance to compete on more equal terms.
That excitement is understandable. It is also pointing in the wrong direction.
What smaller organisations are gaining access to is not the thinking that gave large organisations advantage. It is the thinking that gave large organisations the illusion of advantage while their sectors were being disrupted by people who could not access it. The shortcut leads to the same destination as the long road. A crowded consensus position with a smaller market share and no meaningful differentiation.
The large incumbents had at least one additional constraint that smaller organisations are not fully accounting for. Being radical risked destroying the market position they had already built. The more they had to lose the less they could afford to think originally. Success itself became a barrier. They were trapped by their own dominance as much as by the homogenised advice they were receiving.
Smaller organisations do not have that constraint. They have nothing to lose by thinking originally. That freedom is their genuine advantage. And the risk right now is that they are voluntarily surrendering it in exchange for the same analytical conformity the large players paid fortunes for and gained nothing from.
What advantage actually looks like now
If every competitor in your market is using AI to analyse the same data, apply the same frameworks, and surface the same strategic options, the question worth asking is not how to use AI better. It is what AI cannot do.
AI cannot generate the thinking that would fundamentally challenge the system it is operating within. It produces output consistent with the weight of existing published thought. It is, by design and by architecture, a consensus machine. Powerful, fast, and extraordinarily capable within that constraint. But a consensus machine nonetheless.
The senior professional or executive who understands this is not disadvantaged by AI. They are freed by it. Freed to focus on the one thing current AI cannot replicate and every competitor is currently undervaluing. The capacity to see what the system cannot see and to sustain that thinking against the structural resistance that every system deploys against ideas it did not generate.
That capacity is rare. What makes it rarer still is that most organisations do not yet know how to develop it deliberately. Those that find that specific way first will not be following the consensus. They will be ahead of it.
See also: The Galileo Dilemma: a system condition that threatens radical transformation.
Colin Gautrey, May 2026
Colin Gautrey works privately with senior professionals who have recognised this flaw and are determined not to follow the consensus