With all the discussion about AI agents lately, you might be wondering: how exactly do you count them? If multiple agents collaborate to resolve a customer issue or approve a loan application, does that represent one digital worker or many? The question may sound trivial, but it will soon matter a great deal. Organizations will eventually track digital headcount the same way they track human employees today.

For the last year, the debate around AI at work has split into two unhelpful extremes. On one side, we have breathless talk of “AI coworkers,” complete with onboarding rituals, performance reviews, and soft-focus imagery of humans and machines collaborating happily at their desks. On the other, we have an anxious counter-reaction that insists this language is dangerous, misleading, and fundamentally wrong, because AI systems are not people and should never be spoken of as if they were. Both camps miss the point. The real question is not whether machines deserve human metaphors, but whether leaders understand what kind of economic force they are unleashing, and what kind of organization that force demands.

In 2013, a quiet software developer known to his colleagues as "Bob" became briefly infamous when investigators discovered that he had secretly outsourced his entire job to a contractor in China. He had mailed his security credentials overseas, paid the contractor a fraction of his six-figure salary, and spent his own workdays browsing Reddit and watching cat videos. Yet his performance reviews were stellar. Bob was, by every visible metric, one of the company’s best engineers. When his secret arrangement was uncovered, he was fired. But a decade later, his story looks less like a strange aberration and more like a preview of work in the age of AI.

We can be so focused on robots replacing humans, that we miss the essential problem of preserving organizational knowledge. The future of work is more than just automation. One of the most significant opportunities for AI in the enterprise is using it to understand the heuristics, practices, and tacit knowledge exhibited by our best people - before they leave or retire. Especially now. Given the current crisis, finding better ways to define and retain talent patterns has never been more critical.