Why employee actions now outpace external threats
While organizations prepare for advanced cyberattacks from outside actors, a more immediate risk is taking shape inside the business. Employees, often with no malicious intent, are increasingly using generative AI platforms like ChatGPT and Gemini for everyday tasks. This behavior is hard to monitor—and can introduce serious threats to sensitive company data and regulatory compliance.
- Unapproved uploads to AI tools may include confidential contracts or customer data.
- Organizations frequently lack visibility into where and when data is transferred to external AI services.
- Regulated industries face higher stakes, with potential for compliance violations and reputational harm from unintended disclosures.
What drives employees to risky Shadow AI behavior
The surge in Shadow AI use is not rooted in disregard for security policies, but rather in urgent productivity demands. When officially approved AI tools are slow, restrictive, or in pilot phases, employees will often turn to faster, public alternatives—regardless of corporate policy. For most, the goal is getting work done better and faster, not evading security for its own sake. This creates an "incentive gap": if approved tools do not match the speed and usability of alternatives, policy alone will not control risky behavior.
Addressing the root cause
- Integrate sanctioned AI tools within existing workflows to reduce friction.
- Continuously improve internal solutions based on user feedback.
- Avoid excessive restrictions that make secure tools impractical to use.
How to gain visibility and accountability
No organization can protect what it cannot see. Next-generation identity security platforms are now key to tracking who is using which AI tools, what data is being shared, and from which devices or locations these actions originate. These solutions provide real-time monitoring and can automatically flag or block risky activities, such as sensitive document uploads to non-sanctioned services.
- Track user-AI interactions at the application and browser level in real time.
- Prompt employees and AI agents to justify data uploads or access to sensitive information.
- Establish an auditable agent ledger that captures every relevant identity—human and machine—across business processes.
Dealing with layered AI agents
The rapid rise of nested or delegated AI agents means your information may move beyond a single service, spreading risk outside your control. Identity security that maps all agent relationships and applies least-privilege access is necessary to mitigate these "hidden icebergs." Approved agents get temporary, tightly scoped access—no broad or persistent permissions should be granted.
Key takeaways for CISOs and security leaders
Employee-initiated security risks, especially through unsanctioned AI tool usage, are now a top concern. The response should focus on:
- Building visibility—know which tools are in use, by whom, for what data and purposes.
- Establishing dynamic, real-time controls at both the user and agent-level, not just static inventories.
- Closing the incentive gap by making secure, company-approved AI options viable and convenient for employees.
Identity security has shifted from a compliance requirement to a driver of safe innovation. Prioritizing adaptive visibility and user-focused design is now essential for managing internal risks posed by Shadow AI.