Bringing Shadow AI Into the Light

In offices across the world, the most productive employees are already working with artificial intelligence (AI), and their organizations are just beginning to notice.

According to Gallup, “the percentage of U.S. employees who reported using AI at work at least a few times a year increased from 40% to 45% between the second and third quarters of 2025. Frequent use (a few times a week or more) grew from 19% to 23%, while daily use moved less, ticking up from 8% to 10% during the same period.”

That is either a very good thing or possibly bad.

The quiet spread of generative AI (GenAI) inside companies marks a turning point in how work evolves. This adoption is not driven by executive mandates or formal IT rollouts, but by individuals who discover that AI helps them think faster, write better, analyze more quickly, and complete routine tasks with new efficiency. The movement is organic, practical, and accelerating. It is also largely invisible to leadership, creating a widening gap between how work is actually done and how organizations believe it is done.

The problem is not that employees are using AI. The problem is that most organizations have little idea how much they are using, where data is flowing, or what risks are being created in the process.

What Lurks in the Shadows?

This phenomenon, where employees use AI, but without company sanction, is often labeled “shadow AI.” For decades, organizations have dealt with shadow IT—unsanctioned software, cloud services, and data sharing—that emerged when official systems moved too slowly. GenAI intensifies this dynamic because it is easy to access, powerful by default, and hungry for data. What once involved a few unapproved apps now involves systems that ingest, process, and sometimes retain sensitive information at scale.

The risks are no longer theoretical. Many organizations lack even basic governance frameworks for AI. Sensitive business data is being entered into external tools with little understanding of how it is stored or reused. Breaches tied to unsanctioned AI usage are more expensive and harder to detect than traditional incidents. The arrival of autonomous AI agents raises the stakes further. Unlike human users, agents can move data automatically, act without hesitation, and bypass controls that were designed for slower, manual workflows.

Yet restricting AI is not necessarily the prudent response.

Visibility Is the Answer

Organizations should encourage experimentation while protecting their most critical assets. They should let employees innovate while ensuring that data, compliance, and operational integrity are not compromised. This balance cannot be achieved through policy alone. It requires a shift in how leaders think about visibility, enablement, and education.

Companies cannot govern what they cannot see. Monitoring traffic to AI services, logging data flows, and establishing observability across on-premises and cloud environments are not optional capabilities. They are prerequisites for safe innovation. Without visibility, leaders are forced to choose between blind trust and blanket restriction, both of which fail in practice.

When organizations provide capable, enterprise-grade AI tools, employees naturally gravitate toward them. Shadow usage declines not because it is banned, but because better options exist. This approach reframes governance as support rather than control. Instead of telling employees what not to use, organizations show them what they can use safely and productively.

Not all information carries equal risk. Companies must clearly define what data must never leave the organization and build practical guardrails around it. This may include technical controls, policy restrictions, and automated alerts when sensitive data approaches external systems. In some cases, the safest path may involve developing private, on-premises AI models that deliver capability without exposing confidential information.

Most employees want to use AI responsibly. They simply lack clear guidance. Learning how AI systems store data, how prompts may be retained, and how to evaluate new tools empowers workers to make better decisions on their own. Education turns governance from a policing function into a shared responsibility.

Out of the Shadows and Into the Sunlight of Visibility

The role of IT and security teams is not to suppress innovation, but instead to channel it. Employees will continue to adopt AI because it makes them better at their jobs. The organizations that succeed will be those that replace fear with visibility, prohibition with enablement, and confusion with clarity. AI is amplifying both what organizations can see and what they cannot. The task now is to bring the invisible into view so innovation can move quickly, safely, and sustainably.

Learn more by reading the Forbes article, “Your Best Employees Are Using AI—Visibility Ensures It’s Safe And Sustainable.”