"AI as a Digital Workforce”. Why this Idea Falls Short

The more AI is treated as a “digital workforce,” the more likely it is to amplify the biases and blind spots of its human creators.

At CES 2025, Jensen Huang , CEO of 英伟达 and a prominent voice in AI innovation, shared a bold vision for the future: IT departments transforming into the HR of AI agents—hiring, training, and supervising fleets of digital workers. It is an arresting metaphor, punctuated by applause and investor enthusiasm, but beneath its allure lies a troubling oversimplification of what AI integration truly demands.

The notion of IT professionals as HR for AI risks reducing the complexities of AI adoption to a set of technical processes. But AI doesn’t fit neatly into the familiar paradigms of enterprise management. It operates in a liminal space, challenging traditional structures, and in doing so, exposes the limits of Huang’s vision.

IT Alone Cannot Navigate AI’s Complexity

Hazem Rady , a digital transformation expert, succinctly dismantles the premise:

“AI won’t simplify IT—it will complicate it. Every AI system requires human oversight to prevent bias, ensure security, and address failures.”

Rady’s observation captures the tension at the heart of AI adoption. Unlike servers or networks, AI systems demand more than just technical management; they require contextual understanding, ethical oversight, and strategic alignment. IT teams may be adept at the “how” of technology, but AI demands an equally rigorous focus on the “why.”

In this way, Huang’s metaphor feels like a misstep. IT managing AI agents sounds efficient in theory, but in practice, it reduces AI to a technical tool. But in reality, AI operates within—and often disrupts—the social, cultural, and ethical dynamics of the workplace.

Hence, my view diverges sharply from Huang’s optimism. The idea that IT could, or should, shoulder the responsibility for AI management ignores the broader reality of how organisations function. AI is a force that cuts across silos, requiring input from HR, legal, compliance, and operations—not to mention leadership. Without these voices, AI risks becoming an unchecked experiment, disconnected from the goals and values it is meant to serve.

The Cultural Gap in AI Adoption

Some defenders of Huang’s vision argue that IT is uniquely positioned to standardise AI systems. Jeff Ruhnow , who has long championed the parallels between AI and traditional HR processes, sees a clear path:

“IT departments should build an AI Resources capability templated off HR practices—recruiting, training, performance management—all the complexity buried in underlying systems.”

But this framing assumes that AI agents are analogous to employees, a comparison that falls apart under scrutiny. AI doesn’t learn like humans, doesn’t have the same ethical or psychological dimensions, and crucially, doesn’t participate in organisational culture. The more AI is treated as a “digital workforce,” the more likely it is to amplify the biases and blind spots of its human creators.

To me, this is the core tension. AI systems are neither purely technological nor fully autonomous. They are profoundly shaped by the intentions, decisions, and assumptions of those who design and deploy them. Huang’s framing sidesteps this complexity, offering a compelling but shallow vision.

Massimiliano Turazzini cuts to the heart of the matter:

“Managers who don’t understand both human and AI behaviours won’t be able to lead in the near future. This is not a technical shift; it’s a cultural one.”

Turazzini’s comment resonates because it acknowledges the intertwined nature of technology and culture. AI doesn’t just “fit into” an organisation—it changes the very fabric of how work is done. Leadership in this context isn’t about managing AI as if it were another tool; it’s about understanding how AI transforms relationships, roles, and responsibilities.

The Risks of Misplaced Metaphors

If Huang’s metaphor holds any weight, it is as a provocation rather than a roadmap. Ann-Mary Rajanayagam captures this tension well:

“Holding onto traditional structures—where technology sits solely within IT—will leave companies behind. IT must embed into core business functions, and every function must become more tech-enabled.”

This interplay between technology and business functions highlights the inadequacy of treating AI as a standalone phenomenon. Yet Huang’s framing risks perpetuating a dangerously siloed view of AI, where the responsibility for its governance rests solely with IT.

To me, this approach not only misunderstands AI but also misreads the organisational dynamics of the present moment. AI is not something to be managed; it is something to be navigated collaboratively and iteratively.

The Illusion of Simplicity

There’s a deeper reason Huang’s vision resonates with some—it offers comforting simplicity in the face of AI’s inherent complexity. Framing IT as the HR of AI promises a clear, manageable structure for something that is anything but.

Yet this simplicity is an illusion. As Amir Elion , an AI adoption strategist, observes:

“IT is not equipped to address the challenges of hybrid human and AI teams. HR might be, but only if it understands AI’s capabilities and limitations.”

Elion’s insight underscores a broader truth: AI does not conform to traditional organisational boundaries. It is not just a tool, nor is it a workforce. It is something new, something that challenges the ways we think about work, leadership, and value.

My Reflection

When I reflect on Huang’s keynote, what stands out is not the applause but the missed opportunity. AI is reshaping organisations in ways that demand bold, nuanced thinking—not metaphors that obscure more than they illuminate.

Huang’s vision raised important points, but it left critical questions unanswered. AI’s integration is not just about balancing IT and HR—it’s about redefining how organisations function, how leaders lead, and how we collectively navigate this transformative shift. These challenges demand a depth of thought and action that extends far beyond the surface of technological enthusiasm.

Richard Foster-Fletcher is the Executive Chair at MKAI.org | LinkedIn Top Voice | Professional Speaker, Advisor on; Artificial Intelligence + GenAI + Ethics + Sustainability.

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