When the ExCo shifts from prediction to action, and prepares the organization for an AI-hybrid future.

Thursday, 8:30 a.m.
Thirty slides. Six scenarios. Three risk matrices.
Around the table, the Executive Committee (ExCo) has been debating for an hour. Do we launch the project?
Commission further analysis?
Wait for a regulatory signal?Attendre un signal réglementaire ?
By 10:00, the decision is made… to reconvene.
This scene is far from unique.
In many organizations, uncertainty doesn’t block analysis, it blocks decision-making. We produce more options, more data, more meetings. And, paradoxically, we end up with less control.
In turbulent times, the primary cost isn’t making the wrong call. It’s failing to decide. The kind of indecision that drags on, splinters into successive sign-offs, and dissolves into the search for perfect consensus. Not because leaders lack information, but because the decision criteria are no longer explicitly agreed. When direction is unclear, every decision is open to challenge—and therefore political.
The shift isn’t about predicting more. It’s about being prepared. First, by clarifying a simple compass: a few non-negotiable invariants, a clear direction, and prioritized decision criteria. Then, by putting discipline in place: every strategic item must end with Yes, No, or Deferred. And a deferral is not a “we’ll see”: it’s a dated decision, conditional on a specific trigger. Deferring can be rational—provided you know exactly what must happen to decide.
Strategy then becomes a dynamic portfolio: no-regret moves, options funded in stages, and a few bets triggered by explicit thresholds.
This is how you avoid endless pilots and projects that keep keep running on inertia. Above all, it enables rapid reallocation of resources, a prerequisite for resilience.
A new accelerator makes this discipline even more necessary: artificial intelligence. It lowers the cost of producing analyses and expands the range of plausible scenarios. But it can also amplify noise, bias, and information manipulation. The more options the machine generates, the stronger governance must be: who decides, on what criteria, and with what audit trail? As decisions increasingly combine humans and AI agents, these questions become strategic at the highest level.
“In the fog”, competitive advantage doesn’t come from trying to anticipate everything: making calls on what’s reversible, safeguarding what’s irreversible, and course-correcting fast. Not accelerating blindly, but deciding with discipline.
Because in an unstable world, organizations that make progress aren’t the ones that know everything, they’re the ones that don’t wait (too long) to commit.
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