Mental Model #02 · Mental Models for the AI Era

Thinking is abundant now. The scarcest input in business, a good mind applied to a hard question, just became plentiful.

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Most companies are about to handle that badly, and the reason is 160 years old.

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Every AI business case I have read has hours in it. Fewer analysts, faster answers, shorter weeks. That is the promise every board was sold.

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It is never what happens, and it was never going to be.

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In 1865 William Jevons watched Britain’s steam engines get more efficient and expected the country’s coal consumption to fall. It rose. A better engine made coal worth burning in a thousand places it had never been burned before.

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Cheaper fuel never emptied the roads. It filled them. Cheaper light did the same to the night, and cheaper computing did the same to your pocket.

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Make a resource cheaper and you do not use less of it. You find a hundred new uses for it.

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Thinking just joined the list. The analysis your team could run five times a week now runs five hundred. Every scenario nobody had time to model gets modelled. Every question that was not worth two days of an analyst’s time is suddenly worth asking.

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None of it arrives as saved hours. It arrives as more.

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The pitfall is the obvious one. More, left unharnessed, is just noise.

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Every desk gets an assistant. Reports multiply, dashboards multiply, opinions multiply, and nothing structures any of it. The business does not become better informed. It becomes inundated: more charts to read, more analyses to reconcile, more confident answers pointing in different directions.

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The company gets louder, not smarter.

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Nobody designed for plenty. Every process you run, the weekly review, the approval chain, the board pack, was designed when good thinking was scarce and slow. A process built for scarcity has one reflex: take everything it is given, because there was never enough.

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None of them knows what to do with a surplus. That world closed this year.

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The reframe is simple to state and hard to run: direction and quality beat volume.

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Abundance is not the problem. Unaimed abundance is. Give the extra thinking a direction, the questions the business actually needs answered this quarter, and hold it to a standard: rigorous analysis underneath, one clear synthesis on top.

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Synthesis is not a shortcut around analysis. It is what strong analysis is for. Run this way, more thinking reduces the noise instead of adding to it.

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More thinking in. Faster, sharper answers out.

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The executive job changes with it. It used to be procuring thinking: hiring it, buying it, scheduling it. Now the thinking is there, at every desk, at any hour. The job becomes aiming it. Deciding what deserves it, setting the standard the answer has to meet, and refusing the output that meets neither.

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That is a smaller job than it sounds and a harder one than most leadership teams are set up for.

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Aim the abundance. Turn more thinking into fewer, sharper decisions.

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One note before the next model in this series: the companies that aim their abundance and the companies that pour it do not drift apart slowly. The gap compounds.

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That is where Compounding comes in, as Mental Model for the AI Era #3.

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This is the second of 10 mental models for running a business in the AI era, published every Wednesday.

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If you want to know whether your company is aiming its new thinking or drowning in it, this AI Readiness Diagnostic will tell you in a few minutes.