Why Fortune 500s Build 18,000 AI Agents And Keep Almost None

You would be hard pressed to find a Fortune 500 executive who will publicly admit that their company is struggling to scale AI. Privately, under Chatham House rules, that turns out to be roughly where most of them are.

I recently spoke to Ed Nelson, co-founder and strategy director of the AI Infra Summit, which, prior to their flagship event this month, convened a closed gathering of Fortune 500 executives. The participants were at executive management committee level or one level below. The purpose of the gathering was to discuss what the money being spent on AI was actually buying and how to scale AI implementation.

What struck Nelson was that which was not of interest to this group. Almost nobody wanted to argue about which model was best, or whether the technology could do what was being asked of it. The conversations were about absorption. The real constraint, as he puts it, is “organizational metabolism.”

Implementing AI at scale remains an obstacle.

A number of enterprises had successful AI projects. For example, Nelson describes an enterprise software company that replaced around 250 sales dashboards, used by 4,000 sales people, with a single agent now handling up to 30,000 prompts a week. One dashboard it retired had been costing $3 million a year. Another company implemented an agent to optimise tax payments, this created savings of hundreds of millions of dollars.

A third, in the health sector, used generative AI to summarize tens of millions of customer service calls and identify which messages actually persuaded people to move to a lower-cost treatment. According to Nelson, that produced a margin improvement of $170 million in one part of the business, alongside $200 million in savings passed to customers. In my own company, we recently put agents to work on understanding data compliance across every country in the world, it was only afterwards we realised the time savings and capability uplift.

So why is AI not being used more in live operating models?