The companies that win with AI will build a better way of working…

In 2026, the next competitive advantage won’t come from adding more AI.

It will come from architecting work.

Because once agentic AI becomes capable, proven, and scalable, it stops being “a tool” you deploy and starts behaving like a workforce you manage. And that shift quietly breaks the operating assumptions most companies still run on.

You can see the direction in two opposing moves that point to the same future.

NVIDIA’s Jensen Huang caused quite the controversy when he predicted that IT will essentially become “HR for AI agents.”

“The IT department of every company is going to be the HR department of AI agents in the future.”

Moderna took the inverse approach, putting agentic AI under the CHRO.

Different org-charts, But the same underlying reality.

As AI agents are onboarded to automate workflows, leadership becomes accountable for how that work is divided between humans and agents.

As agentic AI becomes proven and scalable, agents will require new models to manage software as assets, and as capacity. That means they’ll need to be:

• recruited for outcomes
• onboarded and trained
• measured for performance
• upgraded and governed
• and eventually retired

Organizations will have to unlearn and learn how to design and manage a new and evolving digital workforce.

At some point in the near future, “work planning” becomes a formal discipline. And the first meaningful org-chart change will be a new CIO–CHRO joint mandate to manage human:agent capacity and collaboration,end-to-end , systemically, continuously, and at scale.

This is the moment when the leadership evolves

from…“How and where do we deploy AI?”

to…“How do we architect work?”

That single shift activates conversations that breaks down roles and tasks to redesign how work flows, along with governance, performance standards, and lifecycle management.

That’s when the org chart starts to look more like a work chart: a living map of outcomes and workflows that shows how value actually moves through the enterprise.

It articulates…

Outcomes and objectives

• Workflows and handoffs
• Decisions and approvals
• Knowledge dependencies
• Where humans lead
• Where agents execute
• Where people and AI agents learn together

It’s the next architecture and force multiplier of value creation. And it’s how to make agentic AI scalable while designing a better way of working.

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