Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

NEW YORK – March 18, 2026 – Apono, the agentic-forward cloud-native Privileged Access Management platform, today announced the launch of Agent Privilege Guard, a new product that gives enterprises the ability to deploy AI agents at full velocity without creating security risks they cannot control.

The market is flooded with claims. One vendor tops a leaderboard. Another raises nine figures on a pitch deck. Meanwhile, your developers shipped three AI-generated services before lunch. Here's the conversation the industry isn't having, and the one we've been building toward for years. There's a version of this conversation happening inside every Security team right now. Someone demos an AI coding assistant. The speed is undeniable and the team is in awe. Still cautious, sometimes skeptical.

AI is everywhere in vulnerability management right now. Technology vendors in all areas are adding new features and making bold claims about revolutionary capabilities. But here's the reality, especially for vulnerability and exposure management: more AI doesn't automatically mean less risk. The gap between AI's promise and its practical impact in enterprise vulnerability management is wider than most organizations realize.

Microsoft Purview is a powerful platform, but power without expertise can lead to underutilization, misconfiguration, and missed opportunities. Across industries, organizations are grappling with a common set of challenges: The stakes are high. A single compliance incident can cost organizations between $100,000 and $5 million in fines and penalties. And that figure doesn't account for the reputational damage, operational disruption, and remediation costs that follow.

There is a structural shift happening in enterprise environments that most security leaders recognise, but few have fully adapted to. AI is now embedded, decentralised, and operating across core workflows. At the same time, governance models are still largely built on assumptions that no longer hold: that tools are known, data flows are observable, and behaviour follows policy. The result is a widening gap between perceived control and operational reality.