Zenity

Gartner named Zenity the Company to Beat in AI Agent Governance on April 17, 2026. 🏁 In our opinion, here's what that recognition is really about. AI agent governance has evolved. Static, policy-based controls aren't enough. Agents reason, act autonomously, invoke tools across sensitive systems, and operate at a pace and scale that makes manual oversight impossible. Zenity's purpose-built agentic-centric architecture, intent-aware detection, and full-lifecycle observability across SaaS, cloud, and endpoint environments put it at the forefront of the AI agent governance race. That means: 🔍 Comprehensive visibility from build time to runtime 🛡️ Intent-aware runtime defense that catches what prompt filters miss 📋 Shadow AI discovery and posture management across every environment Static, policy-based controls have proven insufficient. Security teams need continuous visibility, runtime enforcement, and the ability to distinguish between legitimate and malicious agent behavior at scale. That's what purpose-built architecture delivers. 👉 Read the full blog: https://lnkd.in/dWVPDAg8 #AISecurity #AgenticAI #AIAgentSecurity #Cybersecurity #EnterpriseAI

AI has moved beyond answering questions. It's now taking action. Agentic AI refers to autonomous systems that don't wait for instructions. They perceive context, set goals, plan multi-step tasks, and execute across your enterprise systems with minimal human oversight. That means AI agents are: → Accessing live CRM data to draft proposals → Reviewing personnel records and updating performance notes → Chaining tool calls across platforms, often without a human in the loop This is a fundamental shift from generative AI. And it changes everything about how security and governance must work. The challenge? Most organizations are still securing AI at the prompt layer, filtering inputs, and monitoring outputs. But agentic AI risks emerge during execution: through memory, orchestration, inherited permissions, and autonomous decision-making. We wrote a primer on exactly what agentic AI is, how it works, and why it demands a new security model. 📖 Read it on the Zenity Academy: https://lnkd.in/dstgfrJK #AgenticAI #AIAgents #AIGovernance #EnterpriseSecurity #CyberSecurity #AIRisk

Identity doesn't tell you enough. 🔐 Most security teams securing AI agents are focused on access: who the agent is, what it's provisioned to do, whether its credentials are clean. That's necessary. It's not sufficient. An authorized agent can still exfiltrate data, drift from its intended behavior, or get manipulated mid-execution, and your IAM layer won't catch it. Closing the gap between permitted and appropriate requires five converging signals: 🪪 Identity: Is the active identity consistent with the agent's declared purpose? 📂 Data: What did the agent actually touch, and was access proportionate? 🧠 Model behavior: Is there evidence of prompt injection or manipulation? ⚙️ Agent posture: Has configuration drifted from the known-good baseline? 🌐 Environment: Are there infrastructure conditions that change the risk? No single signal is enough. Together, they answer the question authorization alone can't. 👉 https://lnkd.in/dvz8WuDm #AISecurity #AgenticAI #AIAgentSecurity #Cybersecurity #AgenticSecurity

Foundations of AI Security kicks off next Tuesday, June 9. Register now to save your spot, and attend all 3 sessions live to receive your certification. In session one, Chris Hughes breaks down: - What AI agents actually are (and aren’t), beyond the buzzwords. - How autonomous and semi-autonomous agents create value across leading enterprises. - Why AI agents behave more like “digital teammates” than tools. - Where AI agents are already showing up in modern enterprises. A clear, no-fluff foundation for security leaders and practitioners. Save your spot ➡️ https://lnkd.in/eHX4MEh8

Gartner® named Zenity the Company to Beat in the 2026 AI Vendor Race research for AI Agent Governance as of April 17, 2026. 🏁 Gartner defines this designation by six criteria: technical capabilities, customer implementations, potential customer base, business model, key partnerships, and the broader ecosystem. We built Zenity to secure AI agents from build time to runtime across SaaS-managed, homegrown, and device-based environments. Turns out, that's the architecture the market needed. 👉 See what the report found: https://lnkd.in/eUSJEGE3 #AISecurity #AgenticAI #Cybersecurity #AIAgentSecurity

“How do we secure AI agents at enterprise scale?” That question has been at the center of nearly every conversation we’ve had this week at Gartner Security & Risk Management Summit. As organizations rapidly deploy AI agents across the enterprise, traditional security models weren’t built to address autonomous AI identities, permissions, and actions. At Zenity, we’re helping security teams gain the visibility, governance, and control they need to securely adopt AI, without slowing innovation. A huge thank you to the customers, partners, analysts, and security leaders who stopped by Booth 851 to share insights, challenges, and perspectives. The conversations have reinforced what we’re seeing across the market: AI Security and Governance has quickly become a top priority for enterprise organizations. AI agents are no longer a future discussion. They’re here now and securing them is mission-critical. #GartnerSRM #AISecurity #AgenticAI #Cybersecurity #SecurityLeadership #AIGovernance #Zenity

Generative AI and agentic AI are often used interchangeably. They shouldn't be. Generative AI responds. You prompt it, it produces an output, and the interaction resets. It's a powerful creative tool, but it stops at generation. Agentic AI acts. It maintains goals across steps, retrieves from knowledge sources, invokes tools, and executes decisions, autonomously, and often across multiple systems, without waiting to be prompted again at each stage. The distinction matters enormously for the people building and deploying these systems. Because the security model, the governance requirements, and the risk surface are completely different. We put together a clear breakdown in the Zenity Academy for anyone who wants to get grounded in the difference, whether you're a practitioner, a leader evaluating AI adoption, or just trying to cut through the noise. https://lnkd.in/drFGrGaG #AgenticAI #GenerativeAI #AILiteracy #AISecurity #EnterpriseAI #AIGovernance

Not all AI agents carry the same risk. So why are we securing them like they do? A copilot that drafts emails has a very different threat surface than an autonomous agent that invokes tools and modifies systems on its own. One-size-fits-all security doesn't work here. Archetype-aware security means understanding what type of agent you're dealing with, and applying controls that match its actual risk profile. We laid out the framework in our latest blog. Worth a read if you're responsible for securing AI in your enterprise. https://lnkd.in/dK3T5xHi #AIAgentSecurity #AISecurity #EnterpriseAI #AIGovernance #CyberSecurity #CISO

Most AI security conversations still center on the model layer. But models are only one piece of a much larger picture. When an AI agent makes a decision, it's drawing on memory, retrieving from knowledge sources, invoking tools, and triggering downstream actions, all in a single workflow. A prompt firewall at the edge can't see any of that. That's the core argument in our latest blog: why AI agent security requires a purpose-built, agent-centric architecture. Not model-level controls or I/O filters retrofitted for a problem they weren't designed to solve. We break down the three common vendor approaches, where each runs out of runway, and what it looks like to govern agents across the full execution path, from build time configuration to runtime enforcement. If your team is evaluating how to secure AI agents at scale, this is worth a read. https://lnkd.in/d6uh6rZ8 #AIAgentSecurity #AISecurity #EnterpriseAI #AgentSecurity #CyberSecurity #AIGovernance

AI agents are now embedded in enterprise workflows. Most organizations have more agents in production than they realize. Many were built without a security review and are operating without guardrails. That's not an AI problem. It's a governance problem. AI agent governance isn't just a security concept. It's the structured approach that defines how autonomous systems operate, what they can access, and how their actions are monitored and controlled. For CISOs, that means five things: 🔍 Autonomous oversight and defined decision boundaries 🔒 Safety, data protection, and secure tool access 📋 Transparency, full agent inventory, and compliance readiness 📡 Real-time behavior monitoring and risk management 🔄 Lifecycle governance from deployment through retirement When governance is done right, autonomous agents shift from unmanaged operational exposure to accountable, policy-aligned enterprise assets. 👉 Read the full CISO checklist: https://lnkd.in/dPwgD2yp #AISecurity #AgenticAI #AIAgentSecurity #Cybersecurity #EnterpriseAI