AI catch-up is a loser's game

If you are reacting to every new AI release, every competitor announcement, every board member forwarding you an article at midnight, you are playing AI catch-up, and catch-up is a loser's game. Not because you are slow, but because the finish line moves faster than anyone can run. The way out is to change the race you are running.

I learned this racing cars in my youth. I kept getting left behind in the corners and could not work out why. It turned out the other drivers were left-foot braking (keeping the right foot on the accelerator while braking with the left, so the car never fully unloads its speed). Seconds, over a lap. But seconds were the difference between winning and losing. You have the commercial pedigree. What is usually missing is the technique to take the corners a little faster.

What does playing AI catch-up actually look like?

It looks like doing yesterday's homework today. You are always a step behind, patching the last tool while the next one ships, chasing a competitor's feature, justifying a pilot that already feels dated. I described this in my book as the PE beep test (the school fitness drill where a recorded beep sets your pace and the gaps between beeps keep shrinking): the beeps start at walking pace, then quicken, until you are flat out just reaching the other side with no breath to recover. The beeps of AI change are getting faster. You cannot out-run them on effort.

And here is the trap: most of your competitors are playing catch-up too, so it feels survivable. It is not. While you argue about which tool to buy, someone is changing what the game even is.

Why do AI-retrofitted businesses always feel awkward?

Because intelligence bolted on sits at odd angles, like electricity retrofitted to a house built before the grid: sockets in strange places, extension leads trailing between rooms. There are now two kinds of business: AI-native, built with intelligence woven through the fabric, and AI-retrofitted, where AI is added to the original proposition. Customers cannot always name the difference, but they feel it. The retrofitted experience is just a bit icky.

Why doesn't buying more tools fix it?

Because the constraint was never the tool. The most-cited number in enterprise AI right now is the finding from MIT NANDA (a research initiative at the Massachusetts Institute of Technology studying how organisations actually deploy AI) that roughly 95% of AI pilots deliver no measurable financial impact, and the research is consistent that the failures come from the choices organisations make in using AI, not the technology itself. The pattern repeats wherever you look.

Read those together and the pattern is unmistakable: the technology works in the demo and dies in the organisation. More tools poured into a business that thinks in catch-up just buys more expensive ways to stay behind.

How do you leapfrog instead?

You change your position, not your pace. Three moves to start:

1. Be honest about where you are. Not where the press release says you are, where you actually are. There is a telling gap here: in a Columbia Business School and Boston Consulting Group survey of 1,400 US employees, 76% of executives believed their people felt enthusiastic about AI, while only 31% of those people actually did. Most leaders are further behind on adoption, and further ahead on anxiety, than they admit.
2. Decide where you intend to go. What is the position you want to hold in three years, when this generation of tools is ordinary? Set that, rather than the next quarter's tool list.
3. Name what is holding you back. It is rarely budget or technology. It is usually the thinking: the assumptions built for a world that no longer exists.

It helps to see where this sits. Phase One, the Age of Effort: work hard, get a little more, linear growth. Phase Two, the Age of Scale: build once, sell to millions, exponential growth. Phase Three, the Age of Acceleration: output decoupled from human effort almost entirely, the phase AI unlocks. Phase One industrialised muscle. Phase Two industrialised repeatable mental work. Phase Three industrialises intellect itself, and you cannot meet that with a procurement decision. The leaders who win the next decade are not the ones who chase the fastest. They are the ones who upgrade their thinking first, and let everyone else keep running yesterday's race.

About the author

Thomas Green

British technology futurist, AI keynote speaker and advisor. Thirty years across enterprise technology and AI strategy, helping leaders navigate the future of work. The futurist who died.