Why India’s AI evolution is no longer about assistance, it’s about autonomy

There was a time not too long ago when enterprise software releases were like military operations. Planning took weeks; testing meant queues of people mulling over lines of code, and rollout nights were filled with stress and coffee-fueled vigilance. Today, those same tasks are handled by invisible allies AI agents that test, deploy, and even undo changes in real time, all without human intervention.

This is not just about speed or scale. It reflects a deeper shift in how Indian enterprises are embracing the future, not just with AI tools, but with agentic systems that can think, act, and adapt on their own.

Rediscovering control through autonomy

India’s journey with AI began early, with machine learning models being incorporated in critical sectors long before the generative AI boom. Now, a new phase is emerging, one where AI doesn’t just assist but autonomously executes tasks, adapts to real-time scenarios, and delivers outcomes with minimal human oversight. This is the promise and potential of Agentic AI.

Unlike traditional automation tools that follow predetermined rules, Agentic AI does not work on fixed scripts. It analyses environments, learns continuously, and acts accordingly. According to a global report, the AI agent market is expected to grow from $5.29 billion in 2024 to $216.8 billion by 2035, at a CAGR of over 40%.

India’s Agentic AI awakening

Walk through any corridors of a leading Indian enterprise today, and you will find AI agents in action. A Deloitte report shows that over 80 percent of Indian businesses are actively exploring or developing autonomous AI agents.

In the banking sector, SBI is deploying over 150 AI models for fraud detection and risk management, while ICICI and HDFC are enhancing customer experience with conversational AI. Even the RBI is using AI to identify mule accounts and financial anomalies, demonstrating broader institutional adoption. Infosys has rolled out over 200 enterprise AI agents to revolutionize workflows across industries like healthcare, finance, telecom and manufacturing. Companies like Tech Mahindra are implementing AI agents for predictive maintenance and supply chain optimization. In customer service, Air India now uses intelligent agents to automate refund processing, and Zomato’s Nugget platform autonomously handles millions of support interactions monthly.

Each example tells the same story Indian businesses are no longer experimenting. They are implementing, at scale.

The real challenge: Building the AI-ready core

Scaling agentic capabilities is not just a matter of software; it is about building the right digital foundation. For AI agents to function reliably and ethically in complex hybrid ecosystems, the underlying infrastructure must evolve.

To truly unlock the power of Agentic AI, India must rethink how data is stored, accessed, and governed. Traditional systems struggle with data silos, delayed access, and governance limitations challenging that are compounded by legacy systems and India’s complex regulatory environment, including data localization laws.

We need to move toward a Data 4.0 environment, where data is not just stored but is also catalogued, trusted, governed by AI, and made instantly accessible across ecosystems. This leap demands more than upgrades; it requires architectural reinvention.

Equally essential is a resilient backbone that supports real-time APIs, dynamic scaling, and observability across hybrid, cloud, and edge environments. These are not just infrastructure checkboxes; they are the pathways through which agentic intelligence flows.

Securing the age of autonomy 

While Agentic AI promises significant operational efficiencies, it also introduces a new set of substantial risks, especially around security, control, and ethical accountability. As AI agents begin to make decisions that impact customers, revenue, and compliance, ensuring ethical and secure operations becomes non-negotiable.

Security must evolve from perimeter defence to pervasive protection. This means implementing Zero Trust at every layer, including machine identities, APIs, and data flows. It also means enabling continuous authentication, proactive threat detection, and AI-native observability to catch anomalies before they turn into crises.

As AI adoption accelerates, platforms like the Application Delivery Security Platform (ADSP) are becoming essential, providing the scalable infrastructure and robust safeguards needed to deploy AI securely and in compliance with enterprise standards.

Scaling with purpose

India has long been a hotbed of digital experimentation. But what’s unfolding now is more than just transformation; it’s reinvention. Agentic AI promises a future where systems do not just support decisions; they make them. Responsibly. Securely. At scale.

To get there, Indian enterprises must double down on next-gen infrastructure, rethink data strategy, and embed security into the very fabric of their digital operations. Not as an afterthought, but as a design principle.

In today’s AI-driven landscape, innovation will no longer be defined by speed alone, but by intelligence and security guiding every action.

Authored by Pratik Shah, Managing Director of India and SAARC, F5