A great deal has been discussed about AI over the last three years. For people who have been closely following the developments, like me, the information now available has been overwhelming. Then here comes the new offspring that has gotten the interest of many organizations: Agentic AI (some refer to it as AI Agents)

The trajectory of artificial intelligence has brought us to a pivotal moment—one where AI agents are no longer just tools but collaborative digital teammates. This new breed, known as Agentic AI, represents a profound shift in how work is defined, distributed, and done. It’s not just evolution—it’s a revolution. We are witnessing the transformation of AI from a sophisticated tool into a powerful partner in problem-solving and innovation. It’s a shift that makes the current Gen AI systems look like basic calculators.

At the beginning of the democratization of AI, it was all about Generative AI; its power and usability. Many of us have now made platforms like ChatGPT, Microsoft Co-Pilot, Perplexity, and Gemini common assistants in various workstreams. So what makes Agentic AI different?

Unlike Gen AI, which only responds when commanded based on patterns in its training data, Agentic AI is proactive and can think, plan, collaborate, and act independently towards goals. Gen AI is used to generate text, images, code, audio, and videos. In each step, a human creator reviews the generated content, refining it and directing the entire process (curating it). Agentic AI, on the other hand, has a life cycle. It can perceive its environment, decide on the actions to take, execute those actions, learn from the output, and then repeat the process, all with minimal human intervention. How does it do it? It also utilizes Gen AI by crafting its own prompts (internal dialogues) through chain-of-thought reasoning.

As an example,you can prompt Gen AI to create an email for you, but Agentic AI can monitor your inbox, identify essential messages, draft responses based on your communication style, and even schedule follow-ups. Agentic AI is also now capable of managing production processes, not by following rigid programs, but by actively optimizing processes and solving unexpected problems in real-time. They can improve workflows by identifying inefficiencies that humans may not have even noticed.

For decades, we have designed our enterprises around hierarchical organizational charts. But Agentic AI challenges that notion. In an environment where intelligent agents can coordinate, execute, and report independently, rigid silos collapse. Work becomes a dynamic, cross-functional flow, not a static reporting structure. Enter the “work chart”—a real-time map of responsibilities, workflows, and collaborations, updated dynamically as human and digital workers respond to evolving needs. This shift has the potential to enable unparalleled flexibility. It allows the instant reallocation of AI agents, the creation of virtual teams based on skills and context, and provides clearer visibility into who (or what) is doing what.

With Agentic AI, it is now possible to create a digital replica of the workforce. Imagine a digital twin of your entire workforce—not just static data in an HR system, but a living ecosystem of skillsets, project histories, communication styles, and task preferences. Agentic AI thrives in this context. It draws from this digital fabric to match the right agents with the right tasks, freeing humans from repetitive labor and amplifying expertise with precision. These digital replicas enable simulations, resource planning, and predictive modeling that were previously impossible. They also serve as the foundation for continuous learning, both for people and machines.

Jensen Huang, the CEO of NVIDIA, recently said,“IT will become the HR of AI agents.” However, I do not see this as a tech question – it is a people question. IT traditionally manages systems and infrastructure, but HR understands people, culture, and the dynamics of change. With Agentic AI, both departments need to collaborate closely. IT ensures technical integrity, security, and scalability; HR ensures trust, transparency, and alignment with human values. A new cross-functional leadership model is emerging—one where AI governance, workforce development, and ethical considerations sit at the center.

Yet, with any leap comes tension. Employees may fear replacement, irrelevance, or loss of autonomy. That’s why empathetic change management is non-negotiable. This includes transparent communication about what Agentic AI is—and what it is not. It includes reskilling programs, opportunities for human-AI collaboration, and clear ethical guidelines.

Most importantly, it requires leaders to listen. Emotions matter in transformation. And trust, once eroded, is hard to regain.

What then could be the best set-up as of today? It will be human-AI teams. The winning formula? Tandem intelligence—not human versus AI, but human with AI. Give AI agents autonomy within guardrails. Embed them in workflows where they can act, not just observe. Equip human teams with control panels to tune, train, and track their digital coworkers.

When humans feel empowered, not replaced, and AI agents are treated as digital colleagues with purpose, that’s when the magic happens.

(The author is an executive member of the National Innovation Council, lead convener of the Alliance for Technology Innovators for the Nation (ATIN), vice president of the Analytics and AI Association of the Philippines, and vice president of UP System Information Technology Foundation. Email: [email protected])