There’s a quiet revolution brewing in the spaces where we work. We are moving towards a future where Outlook won’t just be your inbox, and WhatsApp won’t just be where your family groups share daily greetings. Instead, they’ll start talking to each other through a new layer of intelligence, powered by agents that can coordinate, plan, and act on your behalf. Picture this: your calendar assistant not only drafts the minutes of your meeting but also schedules the follow-up and drops a reminder in your project group, all before you’ve taken your second sip of coffee. That is the world of agentic AI.
Industry research suggests that this world is arriving faster than we think. Capgemini estimates that nearly 80% of Indian enterprises will pilot or adopt such cross-app agents by 2025, while the global economic potential could reach US$450 billion by 2028. The promise is irresistible: a seamless digital butler that cuts friction out of our working lives. But that convenience comes with a price. We’ve seen this pattern before: whether it was smartphones, IoT, or the first wave of GenAI tools, innovation has always sprinted ahead while security trailed behind. And the cost of that lag has been steep: when shadow or unvetted AI is involved, breaches can set organizations back by an additional ₹1.79 crore on average. Moreover, Agentic AI risks are a lot more evolved than the ones we’ve come to expect from the usual GenAI-based chatbot. Unlike chatbots that stop at a single response, these systems can link tasks, adjust on the go, and work toward outcomes with surprising autonomy. That flexibility is powerful, but it also introduces risks we haven’t fully grappled with. In simulated environments, ransomware campaigns have been executed in as little as 25 minutes, powered by AI in every stage of the attack chain according to our Unit 42 Incident Response Report. That’s unprecedented for the industry and transformational for attackers.There’s good news in the mix: autonomous defenses are also taking shape. AI-driven security orchestration has already been shown to reduce manual workloads by up to 75% and cut response times by 98%. That’s proof that AI can protect as aggressively as it can be weaponized – provided we build with intent.
The challenge is that organizations aren’t yet equipped or ready to manage this level of autonomy. While leaders are bullish about AI’s potential, trust in fully autonomous agents is slipping amid ethical and accountability concerns. EY research shows that nearly three-quarters of enterprises have adopted AI, yet only a third have responsible controls in place. In India, too, just a third of organizations have AI access controls, and most still lack formal governance – leaving them vulnerable not for lack of ambition, but for want of a stronger foundation.
So where do we go from here? The answer is to approach agentic AI the way you would approach onboarding a new employee. You don’t just hand them access to every database and trust that they’ll make the right judgment calls. You set boundaries, verify identity, review performance, and keep a record of their work. AI agents deserve the same scrutiny. Before deployment, their permissions must be tightly scoped and auditable. Their identity credentials should be refreshed and validated in real time, so misuse is harder to sustain. And critically, every action, whether routine or anomalous, must be logged because transparency turns black-box uncertainty into confidence.
This isn’t just a technical agenda. It is also cultural. Developers need to test agents in controlled environments and learn from adversarial simulations. CISOs need to think of AI as semi-autonomous colleagues rather than lines of code, applying HR-style principles of access and accountability. And everyday users, often the weakest link, need to practice small but meaningful habits: turning on two-factor authentication, reviewing which apps have access to their accounts, and pausing before believing that voice note asking for urgent funds.
What’s often missed in this conversation is that security doesn’t slow us down – it enables trust, and trust is what allows adoption to scale. Research from a report by Capgemini shows that organizations that implement AI responsibly are already seeing gains in employee creativity, engagement, and satisfaction, sometimes as high as 65% in productivity-enhancing tasks. But the flip side is telling too: fewer than two percent of enterprises have scaled AI agents fully, because without trust, the risk outweighs the reward.
With agentic AI, the focus isn’t simply on adoption, but on responsible implementation. Organizations that align ambition with accountability will not just deploy AI safely – they’ll shape how the technology defines the future. And in India, finding this sweetspot is especially consequential: AI is being stitched into banking, public services, and the country’s digital public infrastructure, so choices made here ripple at population scale.
At the end of the day, agentic AI will only be as useful as the trust we build into it. A butler that can fetch your calendar invites and draft your emails is only a blessing if you know it won’t also leave the front door open. That balance between convenience and control isn’t glamorous, but it’s what separates a fleeting experiment from a lasting transformation.
If we do this right, we can let Agentic AI take the small stuff off our plates while still keeping our hands on the wheel. That’s how we move from novelty to necessity: not by chasing the next shiny capability, but by grounding autonomy in security and trust.
The author is Swapna Bapat, Managing Director and Vice President, India and SAARC, Palo Alto Networks.
Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.
