When the Old Operating Model Breaks: It’s Time for an Agentic AI Operating Model

Ling Zhang
3 days ago
4 min read

How Agentic AI Is Redesigning the Future of Work

A Leadership Guide to AI, Automation, and the Reinvention of Work (1)

Why Agentic AI Forces Enterprises to Redesign How Work Gets Done

For years, enterprise transformation followed a familiar rhythm. New technologies arrived. Organizations experimented. Processes were adjusted. Roles evolved—slowly, incrementally, safely.

That rhythm no longer holds.

Agentic AI has crossed a threshold. It is no longer assisting work; it is participating in it—planning, deciding, acting, and optimizing in real time. And as this shift accelerates, something deeper is becoming undeniable:

The challenge is no longer how to deploy AI. It is how to operate an enterprise where intelligence itself is active.

When the Old Operating Model Breaks It’s Time for an Agentic AI Operating Model

According to the 2026 AI and Agentic Automation Trends Report from UiPath, most enterprises now recognize that agent-centric operating models can outperform traditional ones—but only if organizations are willing to reinvent how work itself is structured. This is not a technology problem. It is an operating-model problem.

The Hidden Assumption Holding Enterprises Back

Most operating models today were designed for one core assumption: Humans are the primary decision-makers.

Technology supports. Systems record. Automation executes predefined steps. Governance happens after the fact.

Agentic AI breaks that assumption. Modern AI agents:

Monitor systems continuously
Make judgments within defined boundaries
Coordinate across workflows
Adapt based on feedback

They do not wait for quarterly reviews or human handoffs. They operate at machine speed, across machine scale.

When organizations try to run these systems inside human-centric operating models, the result is friction:

Bottlenecks where speed is essential
Risk where autonomy is unmanaged
Confusion over accountability
ROI that never quite materializes

The old model doesn’t fail because leaders lack intelligence or intent. It fails because it was never designed for this kind of work.

From Human Workflows to Hybrid Intelligence - Agentic AI operating model for enterprises

The UiPath report highlights a profound shift already underway: across a growing share of occupations, AI systems now perform a significant portion of core tasks, not just peripheral ones.

This creates a hybrid workforce:

Humans provide judgment, direction, and values
Agents provide speed, scale, and continuous execution

But hybrid work cannot be governed by outdated structures.

Three reinvention pressures are converging:

1. Work Is Being Redistributed

Tasks are no longer owned exclusively by people or teams. They are shared dynamically between humans and agents.

This requires:

Real-time orchestration
Clear boundaries of authority
Visibility into who (or what) is doing what—and why

2. Agents Are Entering High-Stakes Domains

Agentic AI is moving into decision-heavy areas like compliance, risk, operations, and customer experience.

Here, autonomy without oversight is dangerous—but excessive control destroys value. Enterprises must design for safe autonomy, not blind automation.

3. Change Is Now Continuous

Agents learn. Systems adapt. Optimization never stops.

Static architectures, annual planning cycles, and rigid workflows are no longer sufficient. Enterprises need operating models that are modular, observable, and adaptive by design.

Why Reinvention Is a Leadership Responsibility

This is the moment many leaders feel a quiet tension. They sense the potential of AI. They approve investments. They support pilots. Yet something still feels misaligned.

That tension exists because technology alone cannot reinvent an operating model. Only leadership can.

Reinvention requires leaders to:

Redefine how work is visualized
Decide where autonomy is appropriate
Establish governance as a living system, not a static policy
Shift from managing tasks to designing systems of work

As IBM and other global research institutions have observed, the organizations that succeed with agentic AI are not the ones with the most advanced models—but the ones with the clearest operating logic.

What This Means for Data & AI Leaders

For Data & AI leaders, this shift is both a responsibility and an opportunity. Your role is no longer confined to:

Model performance
Platform selection
Delivery timelines

You are now shaping how intelligence flows through the enterprise. That means asking different questions:

How do humans and agents collaborate by design?
Where must decisions remain human—and why?
What orchestration and governance capabilities are non-negotiable?
How do we evolve from pilots to an operating system for intelligence?

These are leadership questions. Not technical ones.

How This Aligns with the Data & AI Leadership Accelerator

This first trend sits at the foundation of your leadership journey:

🔹 Pillar 1: Envision & Strategize Data & AI

Reinvention begins with vision. Leaders must articulate a future operating model where humans, agents, and automation work together coherently.

🔹 Pillar 3: Build the Flywheel for Lasting Wins

Without redesigning governance, orchestration, and operating structures, early AI wins stall. Sustainable impact requires systems that scale safely and continuously.

This is exactly where many capable leaders get stuck—not for lack of intelligence, but for lack of a clear operating framework.

A Quiet Invitation

If you are sensing that:

Your AI initiatives are advancing faster than your operating model
Your organization is experimenting, but not transforming
Your role is evolving faster than your playbook

You are not alone.

This moment calls for leaders who can see beyond tools and design the future of work itself - agentic AI operating model for enterprises.

If you’d like to explore how to grow into that role—strategically, confidently, and with lasting impact—I invite you to:

👉 Book a private conversation with me to discuss your leadership goals

👉 Or learn more about the Data & AI Leadership Accelerator, designed to help leaders move from execution to enterprise influence

The old operating model is breaking—not as a failure, but as an invitation.

In the next blog, we’ll explore why AI ROI is finally within reach—and why so many organizations still miss it.

Stay tuned for the next blog, and subscribe to the blog and o ur newsletter to receive the latest insights directly in your inbox. Together, let’s make 2025 a year of innovation and success for your organization.

>> Discover the path to achieve sustainable growth with AI and navigate the challenges with confidence through our Data Science & AI Leadership Accelerator program. Tailored to help you craft a compelling data and AI vision and optimize your strategy, it's your key to success in the journey of Generative AI. Reach out for a complimentary orientation on the program and embark on a transformative path to excellence.