In early February 2026, organizations are facing a new evolution of a familiar challenge: the use of technology outside official channels. A decade ago, the issue was shadow IT driven by personal devices. Today, the focus has shifted to Shadow AI—the unauthorized use of artificial intelligence tools within the corporate environment. Cybersecurity analysts and consulting firms agree that this phenomenon is accelerating as AI becomes embedded in everyday work, often without passing through IT oversight.
Employees as architects of unseen automation
The widespread availability of large language models, combined with open-source tools and low-code platforms, has enabled non-technical professionals to design their own automation workflows. These systems no longer just draft emails or summarize documents; they access corporate applications, process sensitive information, and execute actions autonomously.
Recent studies illustrate the scale of the issue. According to an UpGuard report, 68% of security leaders acknowledge that their organizations are experiencing unauthorized use of AI tools, while surveys cited by specialized media indicate that more than half of employees rely on AI solutions outside approved corporate frameworks. Pressure to boost individual productivity appears to be one of the main drivers.
The risk emerges when these initiatives operate outside established governance models. Without passing through corporate security controls or internal policies, data may be exposed, stored on external infrastructure, or used to train public models, creating direct risks to intellectual property and regulatory compliance, including GDPR requirements.
Security risks and loss of data control
The spread of Shadow AI introduces well-documented risk vectors recognized by the cybersecurity community. Among the most significant are:
- Indirect prompt injection, where automated agents execute unintended actions after processing unverified external documents or inputs
- Data persistence outside the corporate perimeter, such as logs or outputs stored in personal accounts or unmanaged services
- Operational misalignment, when automated decisions bypass internal protocols, ethical standards, or compliance requirements
Organizations such as Google, Microsoft, and CrowdStrike warn that the natural evolution of Shadow AI points toward ungoverned autonomous agents capable of chaining tasks and decisions without centralized oversight. The use of multi-agent configurations by end users still requires broader public evidence to assess its true scope.
The gap between official AI and real AI
This trend exposes a growing paradox: while companies work to deploy AI in a centralized and controlled manner, employees are already solving everyday inefficiencies with improvised solutions. The gap between the pace of business and the pace of technology governance continues to widen.
The new role of HR and IT in agent governance
The response cannot rely solely on prohibition—a strategy that historically has driven technology use further underground. The challenge for CIOs and HR leaders is to channel this creative momentum without compromising security.
More organizations are beginning to explore authorized sandbox environments, where employees can experiment with agents and automation within trusted architectures that ensure traceability and auditability. The goal is not to slow down workplace automation, but to make it visible, secure, and aligned with the company’s broader digital strategy.
Managing Shadow AI will be a defining issue in digital governance throughout 2026. This is not simply about controlling a tool, but about leading a transition in which employee technological autonomy and corporate security find a sustainable balance. Transparency and technical education are emerging—more than ever—as the most effective safeguards against the risks of the digital shadows.
