Waiting for AI to settle is not a plan
Waiting for AI to "settle" is a plan. It is a bad one.
Most execs know the tools are moving fast. Fewer have a way to plan around that. The default is to wait for the dust to drop, then commit. That wait has a cost.
A single forecast breaks when the ground moves. A few written futures bend. OpenAI and Oracle breaking ground on a $7 billion data center in Michigan is one data point. Infrastructure spend is changing price, capability, and who your vendors even are. If your plan assumes one of those stays put, it is already stale.
Four futures, not a 40-page model
Pick the uncertainties that actually bite: tool pricing, regulation, whether people will use the thing, whether the vendor will still be there. Use a model to list outside forces, then split what you control from what you do not.
Take the two variables your team fights about. Build four short stories from the combinations. "Write 150 words on a 50-person services firm if tool costs double and data rules tighten" is enough to start. You are not predicting. You are making people think while they are still calm.
Rehearse the ugly versions
For each story, ask what you would have to decide, and whether you could decide it this week. A vendor goes dark next quarter. A rule lands that makes a current workflow illegal. Costs jump and you have to run on free tiers. Those are rehearsals, not forecasts.
Then name two or three signals that would tell you a given story is coming true. Observable. On a calendar. Someone checks them quarterly or they die in a deck.
The risk is lopsided
Prepare for a future that never arrives and you wasted a meeting. Miss one that does and you eat operational and legal cost. Over 1,000 AI bills have been introduced in U.S. states. The EU AI Act is in force, full compliance by August 2027, penalties that get into the hundreds of millions. If you touch Europe, this is not a later problem.
You do not need a foresight department. You need two hours, a leadership group, and an honest list of what you do not know. Ask a model for the top outside forces on your industry over three years. Pick the two people disagree on. Build the stories. Then ask: which decisions on the table right now assume one of those is guaranteed?
That question usually finds more risk than the annual plan did.