The AI Rush Is Self-Inflicted

The AI rush is self-inflicted in most cases. If you work for OpenAI, Anthropic, or Google — yes, the race is real. Your product is the frontier. A model that ships a week late, or a capability a competitor demos first, shows up directly in your numbers. That pressure is earned.

But if you work in a regular product or service organization — a bank, an insurer, a logistics company, a mid-sized software shop — the feeling of being behind and needing to catch up is largely of your own making. It arrives through your feed, not through your P&L. The demo that made your stomach drop was built by someone whose whole job is to build demos that make stomachs drop.

No one and nothing can move you faster than you are allowing yourself. Sit with that for a second, because it cuts against most of what crossed your screen this week.

I should own my part in this. Being a change agent and org consultant for many years, I have spent a good chunk of my career manufacturing urgency — helping organizations feel enough discomfort that a stalled change finally starts moving. I still believe in that work. Meaningful change usually needs a push, and I am happy to be the one pushing. So this is not a plea to slow down for its own sake.

But rushing to apply AI because it is all over your feed is a different animal. That is not urgency in service of a goal — it is anxiety wearing the costume of strategy. And anxiety is a terrible planner. It picks the tool first and goes looking for the problem afterward, which is exactly backwards. I've watched teams stand up an "AI initiative" before anyone in the room could say, in one sentence, what would be better if it worked. Cheap tokens hid the cost of that for a while; they won't for much longer.

So here is how I'd approach it instead. Three steps, and the order is the whole point.

Step 1 — Put AI aside for a moment

Close the tabs. Mute the feed for an afternoon. Not forever — just long enough to think without a countdown clock running in the corner of your mind. The goal is to get back to a state where you are choosing the direction, not the algorithm that decides what you see.

Step 2 — Ask what you actually want to improve

With the tools out of the frame, the real question surfaces: what would you genuinely wish were better in your organization? Name it concretely. Code quality that keeps costing you weekends. A release process that still needs three handoffs and a prayer. Support costs creeping up quarter over quarter. A new offering you've wanted to test but never had the hands for. Onboarding that takes a new hire two months to feel useful.

Write down two or three of these. Not aspirations — the specific frictions you'd fix if a genie showed up. This list is the thing that should be driving you, and it has nothing to do with AI yet.

Step 3 — Now bring AI back

Only here does the tool re-enter the room. Take your list and ask, for each item: could AI ease or accelerate a meaningful step in this direction? Sometimes the answer is an obvious yes. Sometimes it's "a little, at the edges." Sometimes it's "not really — this is a structure problem, not a tooling one," and that answer is just as valuable, because it stops you from bolting a fast engine onto a car that can't steer. (I've written before about that particular trap.)

The difference between this and the panic version is subtle but total. In the panic version, AI is the goal and your organization is the thing you retrofit around it. In this version, your organization's own priorities are the goal, and AI is one of several ways to get there faster.

I'm on this ride too — enjoying these tools most days, genuinely. That's exactly why I'd rather point them at something I actually care about than sprint in a direction someone else's product launch chose for me. The wave is real. You just don't have to let your feed decide when you paddle.