Podcast

Beyond Automation: Arjun Nagulapally on the Rise of Agentic AI in Enterprises

How Agentic AI Is Transforming Enterprise Operations, AIonOS CTO Arjun Nagulapally Explains

Written By : Market Trends

AI agents are no longer a futuristic concept limited to experimentation. They have rapidly transformed from simple automation tools into intelligent systems that can think, act, and coordinate independently. The AI agents of today are capable of handling enterprise workflows, interacting with external tools, and learning from humans. 

In the latest episode of the Analytics Insight Podcast, host Priya Dialani speaks with Arjun Nagulapally, Chief Technology Officer at AIonOS, to explore why the agentic AI revolution is already at the doorstep of enterprises.

Why Agentic AI Matters Now 

Priya opens the discussion by pointing out a critical reality: while generative AI adoption is widespread, very few organizations are seeing meaningful bottom-line impact. “Agentic impact requires more than just deploying technology,” she notes, “It demands strategic intent, workflow redesign, cross-functional integration, and strong governance.”

Arjun agrees and explains that agentic AI represents a fundamental shift in how humans interact with technology. “For decades, technology required humans to understand systems,” he says, “Now, AI understands human intent.” With natural language interfaces, the barrier to adoption has dropped dramatically; anyone who can communicate can extract value without learning complex software systems.

How AIonOS Is Driving Industry-Specific Transformation

AIonOS (Artificial Intelligence on Operating Systems) is the newest addition to the InterGlobe Enterprises family, a 35-year-old conglomerate best known for Indigo Airlines.

“Our charter is very clear,” Arjun explains, “We focus on travel, transport, logistics, hospitality, and telecom industries where domain nuances matter.” Instead of generic platforms, AIonOS builds solutions aligned with how each industry operates, governed by its processes, customer expectations, and compliance needs.

From Traditional Software to Intelligent Agents

Arjun draws attention to the distinctions between agentic AI and the previous software generations. Traditional systems were primarily limited to data processing. However, agentic AI can decompose complex objectives into smaller steps, use different methods, and execute actions on its own to achieve the desired results.

“An agent isn’t a physical thing,” Arjun explains, “It’s an entity that reasons, plans, and executes toward a goal.” This capability makes industry specialization critical. 

Redefining Enterprise Value Creation

Arjun concludes the discussion, stating that AI is becoming a programming language, driven by intent rather than programming. Companies that consider the shift with wisdom and take it up will be able to solve problems in a very personalized, accurate way, and on a scale not seen before.

“The opportunity is enormous,” he says. “But success depends on understanding the business deeply and designing agentic systems that truly work alongside humans.”

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