What Is Shadow AI? The Risks and How to Manage Them

Shadow AI is the use of AI tools at work without the knowledge or approval of the organization's IT or security team. It's the AI-era version of shadow IT, and it's spreading faster than shadow IT ever did.

It's also very common. In Microsoft and LinkedIn's 2024 Work Trend Index, which surveyed 31,000 people across 31 countries, 75% of knowledge workers said they use AI at work, and 78% of those AI users said they bring their own AI tools to work.

If you haven't formally rolled out AI, that doesn't mean your organization isn't using it. It means you can't see it.

What shadow AI looks like in practice

Shadow AI is rarely a deliberate attempt to break rules. It usually looks like this:

• A marketer uses a personal ChatGPT account to rewrite campaign copy, including unreleased product details.
• A sales rep pastes a call transcript into a free AI summarizer to write up notes for the CRM.
• A developer asks an AI chatbot to explain an error, pasting in a stack trace that includes an access token.
• A manager uploads a spreadsheet of team salaries to get help building a pay review model.
• Someone installs a browser extension with built-in AI that can read the pages they visit.

Each of these is someone trying to work faster. None of them went through procurement, security review or a data protection assessment.

Why it happens

Understanding the cause matters, because it shapes the fix.

• The tools are genuinely useful. People who find a tool that saves them an hour a day will keep using it.
• They're free and instant. There's no purchase order, no installation, no approval step. Anyone with a browser can start in seconds.
• Official options lag behind. Procurement and security reviews take time. Employees fill the gap with whatever is available.
• Bans push it underground. When AI is blocked outright, usage often moves to personal devices and accounts, where the company has even less visibility.

The risks

Data leaving the organization

The biggest risk is what goes into the prompts: customer records, employee data, source code, credentials, contracts, financial results and strategy documents. Once pasted into a tool you don't have an agreement with, that data is outside your control. You may not know where it's stored, for how long, or who can access it.

Compliance exposure

Data protection laws such as the GDPR require you to know where personal data goes, have a lawful basis for processing it, and keep it secure. Shadow AI makes all three hard to demonstrate. Sector rules in finance, healthcare and legal services add further obligations around confidentiality and record keeping.

No incident response

You can't respond to an incident you don't know about. If sensitive data is shared through an unapproved tool, there's usually no log, no alert and no way to assess the impact.

Unreliable outputs

AI tools can produce confident but wrong answers. When usage is hidden, there's no shared guidance on checking outputs, and errors can end up in customer communications, code or decisions.

How to manage shadow AI

The goal isn't to eliminate AI use. It's to make the safe path the easy path.

1. Get visibility first

Start by finding out which AI tools are being used, by which teams, and for what. Ask people directly (most will tell you if they don't fear being punished), and use technical tools to see AI usage in the browser, where most of it happens.

2. Approve good options quickly

If people are using AI for a task, give them an approved way to do it. A business plan for a mainstream AI tool, with proper data protection terms, removes much of the reason to use personal accounts.

3. Set clear, short rules

Publish a one-page AI acceptable use policy that says which tools are approved, which data must never be shared, and who to ask. Focus on data types, not just tool names.

4. Control data at the point it leaves

Visibility and policy aren't enough on their own. The most effective control checks prompts before they're sent, in the browser, and applies your rules automatically: allowing safe use, warning when context matters, masking personal details, and blocking what should never leave.

5. Keep a record

Log what's detected and what action was taken. It gives you an audit trail for regulators and customers, and it shows you where your policy needs adjusting.

Shadow AI is a signal, not just a threat

Widespread shadow AI tells you something useful: your people want to work this way. Organizations that respond with visibility and sensible guardrails get the productivity benefits while keeping their data under control. Those that respond only with bans tend to get neither.

How Nura helps

Nura is a browser extension that gives you visibility of AI use across ChatGPT, Claude, Gemini, Copilot, Perplexity, DeepSeek and more. It detects sensitive data in prompts as they're written and applies your policy in real time, with a full audit log of what was sent, where, and what action was taken. It deploys in minutes, with no proxy to configure.