Agentic AI: Why the Buzz?

What is Agentic AI?

It’s easiest to illustrate with an example—while planning my trip last month, I could have posed three different questions:

• “What’s the weather in Jaipur?”
• “Should I bring an overcoat to Jaipur this week?”
• “Can you create my packing list for Jaipur?”

Each of these questions represents a stage in the evolution of AI capabilities:

The first question relies on machine learning and Natural Language Processing (NLP). It retrieves structured data (weather forecasts) and interprets the query using NLP. This is the AI we’ve long been familiar with—pulling in data and presenting it back to the user.

The second question introduces nuance. “Should I bring an overcoat?” requires Generative AI, which not only references the data (Jaipur’s weather) but also considers context (temperature variations from day to night and possibly even fashion trends). Instead of simply reporting facts, it generates an informed recommendation—something we’ve seen since the launch of ChatGPT.

The third question marks the transition to Agentic AI, an entirely new paradigm. Here’s how it operates: It retrieves the weather forecast and cross-references it with your calendar (business or leisure trip?). It checks your travel history to determine if you usually prefer carry-on or checked luggage. It drafts an initial packing list—but it doesn’t stop there. As the agent compiles your items, it notices they won’t fit in your carry-on. So, it iterates—removing, replacing, and reevaluating weight and volume until the packing list works. If it realizes you’re missing an evening tie, it could initiate another agent to log into your Nordstrom account, find an appropriate tie, and order it to arrive before your departure.

This is Agentic AI in action: moving beyond assisting decisions to making them—autonomously, in context, and with adaptability.

The Rise of Agentic AI Marks a Monumental Leap forward and here are some of the key dynamics at play:

Technology is Advancing at an Exponential Rate

Scale Will Be Massive

We’re entering the era of the Multi-Agentic Workforce, where AI agents will vastly outnumber human employees. During a recent discussion, NVIDIA’s CEO predicted, “We will have 50,000 employees and 100 million agents in two years.” This is not just a 5x or 10x increase over traditional automation tools like RPA—it’s a 100x transformation. Every repetitive task, operational bottleneck, and even intricate decision-making processes will be handled by agents at an unprecedented scale.

Performance Becomes Transformational

Agentic AI isn’t just about speed—it’s about intelligence. These agents engage in “long thinking”, solving complex, multi-step challenges. For instance, rather than simply generating a report, an agent could analyze months of data trends, forecast risks, and propose strategic responses. Agents will also be dynamically adaptive, involving human oversight for decisions requiring creativity or ethical judgment while autonomously handling everything else.

Organizations Will Become Self-Driving

Imagine a company where AI agents don’t merely execute tasks—they manage themselves. Agentic AI enables agents to autonomously spawn, train, deploy, monitor, and retire each other as needed. These agents will create self sustaining ecosystems, adjusting dynamically to new challenges, scaling up for opportunities, or scaling down as priorities shift—all without human micromanagement.

Agentic AI isn’t just about productivity—it’s redefining how organizations function at a fundamental level.

The Future of Work Will Be Radically Transformed Traditional Silos Will Blur

Departments such as sales, service, and operations have historically functioned as distinct units, each with its own teams and processes. In an agentic workforce, these divisions will dissolve. AI agents don’t perceive “departments”—they operate based on end-to-end workflows. As a banking COO in Singapore noted, “Sales and service are two departments for us today but one for an agentic workforce.” Organizations will shift from rigid hierarchies to fluid, interconnected ecosystems, where tasks seamlessly flow between agents and human collaborators.

Talent Will Evolve

As AI agents assume execution and iteration responsibilities, human talent will focus more on creativity, strategy, and decision-making. As a consumer goods CIO and Global Business Services leader in London observed, “Leaders will need to develop hybrid skills that blend technical fluency with business expertise.” IT teams will evolve into HR departments for digital workers, managing agents’ onboarding, identity, entitlements, and performance. The most forward-thinking companies will cultivate a symbiotic relationship between human ingenuity and AI driven efficiency.

Management Will Shift from Command to Coordination

Traditional “command and control” leadership will give way to a coordination-based approach. Rather than micromanaging, leaders will design workflows that incorporate agents into teams while fostering collaboration between humans and AI. At a recent Executive Technology Board meeting, the consensus was clear: “Success will hinge on a new set of management skills”—adaptability, ethical decision-making, and aligning agentic capabilities with business goals.

 Why Does This Matter?

For the first time, AI agents are moving beyond the software category into the realm of digital labor. While the global SaaS market is projected to reach $300 billion by 2030, the global labor market is valued at over $50 trillion. Agentic AI shifts the paradigm—from software as a tool to AI as an autonomous workforce capable of performing iterative, high-value tasks that were once the exclusive domain of human employees.

From the perspective of large enterprises, this isn’t just an incremental advancement in automation—it’s a fundamental reimagining of how companies structure their workforces and allocate resources. Businesses won’t merely deploy AI tools to assist employees; they’ll integrate agents capable of handling complex workflows, scaling operations, and autonomously adapting to new challenges.

What we’re witnessing is the dawn of one of the most profound economic revolutions in history—the Age of Digital Labor.

Disclosures & Industry Perspective

I may materially benefit from the rise of Agentic AI. On the provider side, I am the Chief Digital Strategist at Genpact, which has just launched Service as Agentic Solutions. Additionally, I serve as a venture partner in the AI and Agentic AI space, with startup interests in the emerging technology stack for digital labor. On the consumer side, many of my insights stem from discussions at the Executive Technology Board, an independent non-commercial forum of 130+ CIOs, CTOs, and CDOs, which—while influential—may not fully represent broader industry perspectives.