For two years, enterprise AI meant chatbots and copilots. That era is ending. Organizations are now deploying AI agents that don’t just respond to prompts but take action autonomously—managing workflows, executing code, sending emails, all with your credentials and permissions. Traditional security can’t protect against an agent that has authorized access but drifts from your intent. Every action passes the permissions check. The credentials are valid. The behavior, however, may have nothing to do with what you asked the agent to do. Agent Integrity is the framework for addressing this problem, shifting the security question from “can this agent access this resource?” to “should this agent be accessing this resource right now, for this task?”
Policy as Code: Managing Agent Security Across Heterogeneous Deployments
Enterprise AI agent adoption is creating a security challenge that traditional approaches weren’t designed to handle. When five development teams deploy hundreds of agents across different frameworks, clouds, and architectures, security teams lose the ability to maintain consistent oversight. At Acuvity, we use policy as code to solve this problem by treating agent security policies as declarative, version-controlled configuration that operates independently of how developers build their agents.
Trump Signs Executive Order to Curb State AI Laws and Spur Innovation
President Trump’s AI executive order aims to override state AI laws, establish a national AI regulatory framework, and reshape federal vs. state AI governance in the U.S.
The EU AI Act: What It Means for Companies Developing and Using AI
The European Union’s Artificial Intelligence Act (EU AI Act) is a recent regulatory framework set to reshape how AI is developed and deployed in Europe and beyond. Often compared to the GDPR in its scope and impact, the AI Act introduces…
What Is Memory Governance (and Why Is It Important for AI Security)?
TL;DR: Memory governance defines how AI systems retain, use, and expire state across time. Done right, it improves accuracy and efficiency while enforcing privacy, retention, and access controls. Enterprises should implement runtime policy checks, scoped memory tiers, and full audit trails…
Inside Your Haunted Infrastructure: The Hidden Cost of Shadow AI
Shadow AI is creating hidden risk across enterprises as unapproved tools, copilots, and agents handle sensitive data beyond security oversight. Learn how invisible AI endpoints and persistent model memory expose organizations and why visibility and governance are now critical.
Get Complete AI Visibility with Acuvity’s AI Risk Assessment
The number of AI services continues to grow, with more and more tools available to employees every day. It’s becoming harder to keep up with all the new AI applications, much less understand which ones your employees can actually access or…
OpenAI Atlas Security Risks: What Enterprises Need to Know
On October 21, OpenAI launched ChatGPT Atlas, a Chromium-based browser that integrates ChatGPT directly into the browsing experience. Perplexity launched Comet earlier this month, The Browser Company released Dia, and both Chrome and Edge now include embedded AI capabilities. Atlas combines…
What is Shadow AI?
Shadow AI refers to employees using artificial intelligence tools—often generative AI—without approval or oversight from IT, security, or compliance teams. These unsanctioned tools can expose sensitive data, create compliance gaps, and weaken security controls. Understanding what Shadow AI is, why it spreads, and how to manage it is now a critical priority for CIOs, CISOs, and governance leaders.
Why Shadow AI Is a Compliance Problem
Your employees are already using AI tools at work. While you’re still figuring out your company’s AI strategy, they’ve moved ahead without you. And they’re creating serious security and compliance risks in the process. This blog explores the growing threat of…