What Stayed Expensive

AI made analysis cheap.

You can generate competitive research in minutes. Market analysis before lunch. Customer segmentation by afternoon. Strategic options before dinner.

Insight generation costs pennies now.

But five things stayed expensive.

Knowing which insights actually matter given real constraints.

AI generates forty recommendations. Your budget funds three. Your political capital covers one. Your team has bandwidth for half of one.

Which insight do you bet on?

That's not analysis. That's judgment under constraint.

Building conviction that a recommendation is right despite uncertainty.

The data says maybe. The model says probably. The stakeholders want guarantees.

You need to say "we should do this" without perfect information.

Conviction isn't certainty. It's calibrated confidence despite gaps.

Navigating organizational politics to get things implemented.

The insight is brilliant. The deck is polished. The logic is airtight.

And the VP who controls the budget thinks it threatens his org.

Implementation isn't about correctness. It's about alignment, timing, and coalition building.

Being present for the messy work of change.

AI can write the change management plan. It can't sit in the room when the team pushes back. It can't read the silence when the new process fails. It can't adjust in real-time when reality diverges from the plan.

Presence requires context that only humans carry.

Taking responsibility when things go wrong.

AI can generate the recommendation. It can't be accountable for the outcome.

When the bet fails, someone's name is on it. That's not a capability problem. That's a consequence problem.

These five things didn't get cheaper.

They got more valuable.