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AI divide: It's not technology but learning capacity

The real divide of the AI era will not be technological but a gap in collective learning capacity, defined as an organization's or society's ability to adjust behavior faster than a changing environment outpaces it. This capacity varies widely between groups, as a team of brilliant individuals can exist within an organization that learns nothing, and intelligent citizens can produce institutions incapable of adapting. As AI accelerates environmental change, this variation in collective learning capacity will become decisive.

read1 min publishedMay 31, 2026

In the previous column, I argued that artificial intelligence (AI) will not so much replace humans as expose the systems we have built. The real divide of the AI era, I suggested, will not be technological. Instead, it will be a divide in what I called “collective learning capacity.” There are questions that remained unanswered. What is that capacity? Why does it vary so widely between organizations and societies? And finally, why is AI about to make those variations decisive. Learning capacity, in the sense I mean it here, is not the ability of an individual to absorb new information. It is something collective. A team of brilliant individuals can sit inside an organization that learns nothing. A society of intelligent citizens can produce institutions incapable of adapting. The intelligence of the parts does not determine the intelligence of the whole. What I mean by learning capacity is the ability of an organization, an institution or a society to adjust its behavior to a changing environment, faster than the environment outpaces it. Every adaptive system — biological, organiza

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