What you need to know about shadow AI

You can’t control what you can’t see. Without visibility of every AI-enabled tool your workforce uses, you could be overlooking shadow AI hidden in your tech stack.

Employees are quietly using AI without their organisations’ knowledge or approval. According to UpGuard, eight in 10 workers report using unauthorised AI tools at work.

Let’s explore shadow AI in greater detail, its implications, and how organisations can bring hidden tools to light.

What is shadow AI?

Shadow AI is the use of unapproved AI systems at work. These tools can evade traditional governance frameworks by operating through personal cloud accounts, via hidden browser extensions, and as add-ons for approved productivity software.

Shadow AI typically happens when business-provided tools fail to meet employee needs. If workplace AI systems lack the features, speed, or seamless user experience that employees require, they may find alternative solutions to help complete their tasks.

According to BlackFog research, six in 10 employees believe using shadow AI is worth the security risk if it helps them meet deadlines.

Consumer AI assistants are a major source of shadow AI. Microsoft highlights that employees often use these tools in the workplace to draft communications, prepare reports and presentations, and handle finance-related admin.

How can shadow AI impact your organisation?

AI delivers clear business benefits. The ServiceNow Enterprise AI Maturity Index 2026 found that organisations leading in AI maturity report outcomes such as 5.6 times higher productivity, 2.7 times greater ability to scale, and 2.6 times better risk reduction. But issues can arise if AI tools aren’t properly governed.

When sensitive information is entered into unvetted tools, it can increase the risk of a data breach. According to Gartner®, “by 2030 more than 40% of enterprises will experience security or compliance incidents linked to unauthorised shadow AI.”¹

Without clear guardrails, shadow AI can turn a competitive advantage into a financial and operational liability. IBM reports that organisations with high shadow AI activity pay approximately £498,000 ($670,000) more per data breach than organisations with low or no shadow AI.

Shadow AI can even undermine an organisation’s approved AI projects. When employees operate their own siloed AI ecosystems, they’re less likely to use centrally procured tools.

This fragmentation leaves leaders struggling to prove AI value and often triggers an overcorrection with bureaucratic manual governance processes. Business AI systems become more difficult to use, employees turn to shadow AI, and the cycle starts all over again.

Shadow AI also surfaces something useful. By building visibility into the tools employees actually use, organisations can identify gaps in their portfolios and make better procurement decisions. Once you understand what your workforce wants from AI, you can build a centrally governed AI stack that delivers high return on investment.

How to audit and govern shadow AI

Effective shadow AI governance requires organisations to identify, document, and assess unvetted AI tools. Start with these security best practices:

• Register every AI agent, model, prompt, and Model Context Protocol (MCP) server employees use in a configuration management database inventory.
• Evaluate the risk profile of each AI system based on its built-in security frameworks and the sensitivity of the data it processes.
• Define clear usage policies that align with your corporate ethics, regulatory frameworks, and security standards.
• Implement integrated controls to monitor how users interact with AI-enabled tools in real time.
• Generate clear, audit-ready dashboards to demonstrate each tool’s compliance with company policies and regulatory frameworks.

An autonomous governance layer is essential for managing AI assets at scale. ServiceNow® AI Control Tower is the control plane for autonomous governance, providing one place to see every AI system across any cloud. It helps discover every in-app asset, catalogue models and AI agents, and enforce governance policies.

Leaders can see which AI tools are deployed, what parts of the business they touch, and how models make decisions. They can monitor what data AI systems have access to in real time. And within AI Control Tower, they can help ensure that assets align with regulatory frameworks such as the EU AI Act.

A proactive approach to AI visibility empowers you to address shadow AI before it becomes a bigger problem. It can also help you govern, secure, and manage compliance while delivering value across your AI estate.

Find out how ServiceNow can help you take control of your AI.

¹ Gartner Press Release, Gartner Identifies Critical GenAI Blind Spots That CIOs Must Urgently Address, November 19, 2025. GARTNER is a trademark of Gartner, Inc. and/or its affiliates.