When Everyone’s Work Is “Good Enough,” Sameness Becomes the Real Risk

Something quietly unsettling is happening to creative and strategic work, and the people closest to it have started saying so out loud. In its Spring/Summer 2026 review, the Pantone Color Institute warned of a creeping homogenisation as AI’s influence spread through design. Marketing and brand commentators are making the same point from the other direction: AI will happily hand you a competent prototype, but it cannot hand you a brand. And a widely discussed study of around 300 writers captured the trade-off in miniature. Access to AI-generated ideas lifted the quality and creativity of individual stories, especially for less confident writers, while the collective set of stories became measurably less novel. Everyone got better. Everything got more alike.

That paradox is the heart of it. AI raises the floor for the individual and lowers the ceiling for the field. If your competitive advantage was ever built on being competent, that advantage is thinning in real time.

Competence just stopped being a moat

For most of the modern economy, being good was enough to win. You could differentiate on a cleaner deck, a sharper analysis, a more polished campaign, a tighter strategy document. Competence was scarce, so competence was valuable.

It is not scarce anymore. When every team at every company can produce a serviceable interface, a coherent strategy memo or an on-brief campaign in minutes, the serviceable version stops distinguishing anyone. The work converges. Brand voices blur. Strategy frameworks start to rhyme. Campaigns feel familiar before they have even launched, because they were generated from the same underlying patterns, drawn from the same models, prompted in the same predictable ways.

You can be doing everything right, shipping faster than ever, hitting every quality bar, and becoming less distinctive every quarter. Efficiency and sameness arrive together.

The tool is levelling. The edge is the person on top of it.

Jensen Huang, who runs Nvidia and sits closer to the engine of this shift than almost anyone, has made a version of this point repeatedly through 2026. Speaking at Stanford earlier in the year, he argued that AI itself is unlikely to take your job, but a colleague who uses it well might. At a summit in Mumbai he put the boundary more precisely: AI can do parts of a job a thousand times better, yet it cannot do the whole of any job. Read those two ideas together and the conclusion is hard to avoid. When the same powerful capability is available to everyone, the capability stops being the differentiator. The person applying it becomes the differentiator.

That is the uncomfortable news for organisations that have spent two years congratulating themselves on adoption. Adopting the tool is now table stakes. Everyone has it. What decides who stands out is what a human brings to it that the model cannot: judgement, taste, a point of view, the cultural read, the story that makes someone feel something.

Why the sameness happens, and why it is not really about AI

It is worth understanding the mechanism, because it points to the fix. The homogenisation researchers found that when many people draw on the same model, prompted the same way, the outputs collapse toward a shared middle. The AI is not the problem. Everyone feeding it the same narrow inputs and asking it the same narrow questions is the problem.

Creativity has never been a solo act of generation. It lives in a system: the interaction between an individual, a domain of existing work, and a field of people who decide what counts as new. Novelty emerges from the friction between different perspectives, different inputs, different reference points. Strip the variety out of the inputs and you strip the novelty out of the outputs, however powerful the tool sitting in the middle.

So the sameness problem is not a technology problem. It is an input problem, and input is something leaders control.

What leaders can do about it

• Audit for sameness, not just quality. Your review process almost certainly asks whether the work is good. It rarely asks whether it is yours, whether only your team could have made it. Add the second question. It is now the more important one.
• Diversify the inputs deliberately. If a team’s references all come from the same five sources and the same model, the output will converge. Widen what goes in, across disciplines, industries and perspectives, before expecting anything distinctive to come out.
• Vary how you prompt. Identical prompting produces identical thinking. Teams that approach the same problem from genuinely different angles preserve the variety that distinctiveness depends on.
• Protect the unreasonable idea. The competent middle is now free and infinite. The strange, specific, slightly too bold idea is the scarce asset. Make sure your process does not filter it out in the name of polish.

When competence is everywhere, it is worth very little. The premium has moved to the work that does not look like everyone else’s. The question worth asking of anything your team produces is no longer only whether it is good. It is whether anyone else could have made it.

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