The New Era of Workforce Management: Embracing AI as Talent

"Human capital management" is a term that has always been a little uncomfortable. It treats people as assets to be managed — inputs to be optimized. Now, with AI becoming a genuine contributor to business outcomes, the term is becoming obsolete in a different way: the workforce it describes is no longer exclusively human.

Mike Sullivan and Vinay Gidwaney have been thinking about this shift for a while. Their argument is straightforward: AI is now talent. And if you're going to manage it effectively, you need to think about it the way you think about your best people.

What It Means to Treat AI as Talent

When you hire a talented employee, you don't just give them a task and walk away. You onboard them. You give them context. You set expectations. You give them feedback. You invest in their development. You hold them accountable for outcomes.

Most organizations don't do any of this with AI. They deploy a model, give it a prompt, and measure outputs. When the outputs aren't what they expected, they blame the technology.

The organizations that are getting the most out of AI are treating it differently. They're investing in the "onboarding" — the context, the data, the fine-tuning that makes an AI system effective for a specific use case. They're setting clear expectations for what the AI should and shouldn't do. They're building feedback loops that improve performance over time.

That's talent management. It just happens to be applied to a non-human system.

The Implications for Leaders

If AI is talent, then managing AI is a leadership responsibility — not just a technology responsibility.

This has real implications for how organizations are structured. The question of who owns AI performance — IT, operations, the business unit — becomes a governance question, not just a technical one. The question of how AI capabilities are developed and deployed becomes a talent strategy question.

It also has implications for how leaders think about their human workforce. If AI is handling an increasing share of routine cognitive work, what does that mean for the humans who used to do that work? What new skills do they need? What new roles do they move into?

These aren't questions that technology teams can answer alone. They require leadership engagement — the kind of engagement that most organizations are still figuring out how to provide.

The Shift That's Already Happening

The organizations that are ahead of this shift share a common trait: they stopped thinking about AI as a tool and started thinking about it as a capability. A capability that needs to be developed, managed, and held accountable — just like any other organizational capability.

That shift in mindset is harder than it sounds. It requires leaders to engage with AI in ways that feel unfamiliar. But it's the shift that separates the organizations that are genuinely transforming from the ones that are just experimenting.

Human capital management isn't obsolete because humans don't matter. It's obsolete because the workforce has expanded — and the new members of that workforce require a different kind of management.