The Hidden Risks of the Agentic Enterprise: Bridging the AI Governance Gap

Software used to wait for permission. It executed specific instructions predictably, transparently, and only when a human initiated a process. Today, AI agents are crowding into IT environments. These autonomous entities can execute complex workflows, access critical systems and sensitive data, and even spawn additional agents to complete tasks. No humans required.

New research from Okta reveals the speed and scale at which enterprises and employees are adopting AI agents. Its global survey found that 92% of executives already report widespread or moderate use of AI agents within their organizations, while 64% of knowledge workers report using AI tools daily.

As autonomous systems become the new operational standard, the corporate security landscape is transforming. While organizations rapidly adopt these powerful tools to drive efficiency and innovation, they are simultaneously—and often inadvertently—opening the door to unprecedented security vulnerabilities. AI agents not only frequently hold access to sensitive data and applications, they also tend to function outside of traditional, human-centric security controls. Building a secure architecture for AI requires total accountability and visibility. Instead, the data shows gaps in how enterprise AI is actually governed.

The Illusion of Control: Executive Confidence vs. Shadow AI

One of the most alarming findings regarding AI security trends is the stark divide between how leadership views their security posture and what is actually happening on the ground: 90% of executives express confidence in their organization's visibility into AI tools, with 95% believing that their employees are using AI responsibly and strictly within established corporate guidelines.

Reality tempers this optimism. Shadow AI, the use of unauthorized or unsanctioned artificial intelligence applications, is widespread. According to the survey, 52% of employees admit to using AI tools without official approval, frequently bypassing enterprise security controls by using personal accounts.

Circumventing approved IT channels impacts visibility. Security teams can’t protect against what they cannot see. The use of unsanctioned tools means thousands of new "black box" entities are continually interacting with corporate environments completely undetected, creating a massive blind spot for security, privacy, and compliance teams.

Real-World Consequences: Security Breaches and Data Exposure

This lack of visibility compounds an already challenging threat environment. According to the survey data, 58% of executives reported that their organization has experienced an AI-related security incident or a close call within the past 12 months.

How employees handle company data also increases AI risk. Large language models (LLMs) and autonomous agents require vast amounts of data to function, and employees are readily providing it. Among workers using unapproved AI tools, 54% say they’ve shared internal messages and emails, 45% handed over sensitive HR-related information, and 39% uploaded confidential company documents. Using unapproved tools takes sensitive data out of the company's control and exposes it to leaks and privacy risks.

Bridging the Disconnect: Clearer Policies and Stronger Identity Controls

If shadow AI is widespread and causing active security incidents, why are governance efforts falling short? The data points to internal communication and policy enforcement as potential factors: 65% of executives believe their organization's AI usage policies are "very clear"; however, 57% of knowledge workers say their company's AI policies are unclear, hard to find, or altogether non-existent.

When employees do not understand the rules—or cannot easily access them—they’ll inevitably create their own workarounds. Organizations must move beyond high-level executive mandates and put clear, actionable AI guidelines directly into daily  workflows. However, clear policies alone aren’t enough. They need technical enforcement to work.

A major technical gap exists in how organizations handle non-human identities. Currently, only 34% of organizations report applying the same rigorous security controls to their agentic labor force as they do to their human labor force. Just as an employee requires strict identity verification, role-based access control, and continuous behavioral monitoring, an AI agent requires the exact same level of scrutiny. Establishing parity between human and non-human identity management is crucial for the future of enterprise security.

Securing the Agentic Future

Regaining control requires a plan, the tools to support it, and a workforce that understands it.

It starts with a blueprint for the agentic enterprise, which helps organizations answer three questions: Where are their AI agents? What can the agents connect to? What can the agents do?

That visibility is then supported by modern tools that continuously assess AI agent architectures and govern the agentic workforce. Finally, those tools must be paired with clear communication so that everyone in the organization is working from the same security-focused playbook. The future of enterprise productivity is agentic, but its long-term success will be defined entirely by its security.

To learn more, read the full report: AI Agents at Work 2026: Securing the agentic enterprise.

Ready to put these insights into practice? Assess your organization's AI readiness with Okta's interactive evaluation tool to safely secure your autonomous workflows.