Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

At Zenity, we like to say we don't only exist on the bleeding edge; we are the bleeding edge. It's a defensible claim. Zenity Labs consists of multiple teams focused on various technical disciplines within the security industry, and while the Labs moniker sits loosely over the group, the work it produces tells a unified story around AI Agent security.

When the AI Agent Security Summit launched in San Francisco last October, agent-based threats had already escalated from a novel consideration to a predominant blocker for enterprise adoption. The security community was laser-focused on recognizing and minimizing the blast radius posed by agentic vulnerabilities, whether that meant indirect prompt injection, MCP poisoning, or hallucinations.

The security industry hasn’t been wrong about agentic AI risk. It’s been incomplete. There’s no shortage of single-signal solutions for the problem: tools that analyze prompts for malicious content, platforms that monitor data access patterns, capabilities that assess model behavior for signs of manipulation. Each captures something real. None is sufficient on its own.

Gartner named Zenity the Company to Beat in AI Agent Governance on April 17, 2026. That recognition, grounded in technical capabilities, customer implementations, ecosystem breadth, and business model, isn't a marketing award. To us, it's the analyst community confirming that purpose-built architecture for agentic AI is winning. The recognition didn't come in isolation. Gartner's own language captures the stakes.

Every conversation I have with security leaders about enterprise AI security eventually arrives at the same place: a description of what they've extended. Their data loss prevention tool now flags sensitive data going into prompts. Their SIEM is ingesting AI platform logs. Their cloud security team has added model endpoints to their coverage scope. For many teams, this represents real effort and real progress.

Download Beyond Identity: The CISO's Guide to Securing Agentic AI for a 12-month roadmap to comprehensive agent governance, starting with visibility. Some organizations still treat agentic AI as a future problem. Something to plan for. Something on the horizon. That framing is wrong, and the inaction it entails will put you behind.

If there's one idea that shaped RSA 2026, it was identity. Vendor booths, keynotes, conversations. All roads led back to the same instinct: control identity, control access, control risk. That instinct is directionally correct. Identity governance is foundational. But identity answers only part of the question agentic AI is asking. Here's the part it doesn't answer: authorization tells you what an agent was permitted to do. It says nothing about whether what it actually did was appropriate.

A couple of years ago, AI agent security was a niche conversation. The practitioners who took it seriously were a small group of researchers, a handful of forward-looking CISOs, and a few founders who had watched the attack surface forming in real time. The broader market hadn't caught up yet. It has now. Enterprises are deploying AI agents at scale across platforms. The productivity gains are real. The competitive pressure to adopt is real.

When the US Center for AI Standards and Innovation (CAISI) asked for public input on securing agentic AI systems, the response was massive: over 500 detailed submissions from Fortune 500 companies, defense contractors, AI startups, and cybersecurity firms. The result is substantial insight into how industry views the regulatory challenges of autonomous AI agents and what they think policymakers should do about it.

Gartner named Zenity the company to beat in the AI Agent Governance category in its AI Vendor Race: Zenity Is the Company to Beat in AI Agent Governance report as of 17 April 2026. The evaluation covered technical capabilities, customer implementations, business model, and ecosystem strength. That methodology matters because for us, it means the recognition reflects what the platform actually does in production, not just how well a demo lands.