As the EU AI Act enforcement deadline approaches in late 2027, enterprises face a stark reality: they cannot govern what they cannot see. According to Okta's Global CISO Insights 2026 report, less than half of chief information security officers (CISOs) can identify all the AI agents operating in their systems, yet 81% are concerned about excessive AI access. The problem isn't just visibility; it's accountability. With penalties reaching €35 million or 7% of global annual turnover for non-compliance, businesses are scrambling to understand where their AI agents live, what they can access, and who is responsible for them.

Disclosure: This article is based on content published by Okta, an identity management vendor. Readers should consult independent legal and compliance advisors before implementing any compliance strategy. The source material includes disclaimers that it does not constitute legal, privacy, security, or compliance advice.

What Is Shadow AI, and Why Should Your Company Care?

Shadow AI refers to artificial intelligence systems deployed outside official security controls, often by individual teams or departments without enterprise oversight. Today, anyone can spin up an AI agent, frequently bypassing security protocols entirely. This creates a governance nightmare for compliance officers and security teams. The EU AI Act's transparency rules, which went into effect this month, mandate that organizations disclose when users interact with AI systems. By December 2027, stricter rules will demand that companies design AI systems humans can monitor, interpret, and override, along with the ability to explain how deployed AI systems reach decisions.

The challenge is that most enterprises have spent years standardizing identity governance for human employees but have no equivalent framework for AI agents. This gap leaves organizations vulnerable to both regulatory penalties and operational risks. According to the Okta report, only 31% of CISOs said they are aligned with their boards on AI risk, suggesting that many organizations lack a cohesive strategy for managing autonomous systems.

How to Build a Secure Agentic Enterprise: Four Practical Steps

• Establish Baseline Visibility First: Conduct a comprehensive audit of your active AI footprint. Map the tools in use, identify the data they can reach, and document blind spots. You cannot secure or audit what you cannot see.
• Manage AI with the Same Rigor as Your Workforce: Apply the same identity principles used for human employees to AI agents, including least-privilege access (giving agents only the permissions they need), time-limited entitlements (access that expires automatically), and regular recertification (periodic reviews of what agents can do).
• Keep Humans in the Loop: High-risk autonomous systems should not operate entirely unchecked. Establish clear separation of duties and require human approval before AI agents perform sensitive or high-risk actions.
• Align AI with Existing Business Goals: Running unmonitored shadow AI or disconnected trials increases danger without proving value. Companies that actively question whether their AI programs are driving business metrics reduce exposure to AI-related security risks and ensure technology investments deliver real returns.

These steps form the foundation of what identity and access management experts call a "secure agentic enterprise." The concept treats AI agents as first-class identities, governed with the same rigor as human employees. This approach answers three critical questions: Where are my agents? What can they connect to? What can they do?.

Why Is Identity the Key to EU AI Act Compliance?

The EU AI Act is not the only regulatory framework reshaping the European landscape. It joins a complex wave of regulations including DORA (Digital Operational Resilience Act), NIS2 (Network and Information Security Directive 2), and eIDAS 2.0 (electronic identification and trust services), which interact with a nuanced web of national-level laws. Despite targeting different sectors, these region-wide regulations share a common thread: you cannot secure, audit, or govern what you cannot reliably identify.

For enterprises, meeting EU AI Act regulations should not be viewed as a technical hurdle to clear. Instead, leadership teams should see it as an impetus for understanding how digital systems work and who is responsible for them. Identity governance provides the foundation for this accountability.

"EU regulators demand accountability. It's time to treat AI agents as first-class identities," stated Matt Ellard, Senior Vice President and General Manager at Okta.

Matt Ellard, Senior Vice President and General Manager, EMEA at Okta

The EU AI Act holds any business serving European customers accountable, regardless of where they are based. Securing the digital identities behind every automated action is one part of satisfying compliance requirements. Organizations that begin laying the groundwork for compliance today will be better positioned when full enforcement arrives in late 2027.

By treating AI governance as an identity challenge, organizations can step out of the shadow AI phase, safely deploy the technology, and clear the way for continued growth. The stakes are high, but the path forward is clear: visibility, governance, human oversight, and alignment with business goals. For enterprises navigating the agentic AI era, identity is no longer optional; it is the foundation of responsible AI deployment.