Shadow AI is one of the fastest-growing security risks facing organisations today. When employees use unauthorized AI tools — ChatGPT, Midjourney, Copilot alternatives, or dozens of niche GenAI apps — without IT knowledge or approval, sensitive data flows to third-party systems outside your control. But how do you know if your organisation has a shadow AI problem? Here are ten telltale signs, along with practical steps to regain visibility and control.
1. Unexplained Spikes in SaaS Spending
One of the earliest indicators of shadow AI is a creeping increase in software expenses that nobody can account for. When individual teams or employees sign up for AI tools using corporate credit cards — or even personal cards and expense them later — finance teams notice anomalies. If your SaaS spend has grown 15–30% year-over-year without corresponding procurement approvals, AI subscriptions are likely part of the picture.
Look for recurring charges from vendors like OpenAI, Anthropic, Jasper, Copy.ai, Notion AI, or Runway. Many of these start as free trials that quietly convert to paid plans. A thorough SaaS audit is often the fastest way to surface unauthorized AI tools.
2. Employees Reference Tools That Are Not in Your Stack
Listen to how your teams talk. If a marketing manager mentions they ran something through Claude or an engineer says Copilot suggested a refactor, but neither tool is in your approved software catalogue, you have a shadow AI issue. These casual references reveal habitual use — the tool is already embedded in their workflow.
This is not about punishing innovation. It is about awareness. Employees often adopt these tools with the best intentions — they genuinely increase productivity. The problem is that IT and security teams have no visibility into what data is being shared with these services.
3. Unusual Outbound Data Transfers
Your network monitoring tools may reveal large or frequent data transfers to AI provider domains — api.openai.com, api.anthropic.com, or various model hosting endpoints. If your DLP or firewall logs show employees sending substantial payloads to these destinations, that is data leaving your perimeter.
This is particularly concerning because GenAI prompts often contain the exact data you are trying to protect: customer records, proprietary code, financial projections, and strategic documents. Traditional data loss prevention tools may not flag these transfers because the data format does not match traditional exfiltration patterns.
4. Productivity Gains Without Process Changes
When a team suddenly produces content, code, or analysis significantly faster without any visible process improvement, new hires, or tooling changes — AI is almost certainly involved. A content team doubling their output, a developer shipping features at twice the pace, or an analyst producing reports in half the time are all signals worth investigating.
The issue is ungoverned use. If the productivity gains come from pasting proprietary data into unauthorized AI tools, the risk-reward equation flips dramatically.
5. Browser Extensions You Did Not Approve
AI-powered browser extensions are among the stealthiest forms of shadow AI. Tools like Monica, Merlin, MaxAI, or ChatGPT browser extensions can read page content, intercept form data, and send information to external servers — all while appearing as a harmless productivity add-on.
If your endpoint management solution shows unapproved browser extensions with AI capabilities installed across employee devices, treat this as a high-priority finding. These extensions often have broad permissions that give them access to everything the employee sees in their browser, including internal dashboards, customer data, and confidential communications.
6. Inconsistent Output Quality and Style
AI-generated content has a distinctive fingerprint. If you notice that certain employees' written work has suddenly become more polished, more verbose, or stylistically different from their usual output, AI writing assistants are likely in play. Similarly, code that adopts unfamiliar patterns or conventions may have been generated or heavily assisted by AI coding tools.
Watch for telltale signs: overly structured responses, certain phrases that LLMs favour, or a sudden shift from casual to formal tone. These patterns suggest employees are copying AI outputs without significant editing.
7. IT Helpdesk Tickets About AI Tool Access
Ironically, employees sometimes tell you about shadow AI themselves — through helpdesk tickets. Requests like 'Can you whitelist api.openai.com?' or 'ChatGPT is blocked on our network, can you unblock it?' or 'I need a corporate API key for Claude' are direct evidence that employees want to use (or are already using) AI tools.
Track these requests systematically. They represent demand that, if unmet through official channels, will find unofficial workarounds — personal devices, mobile hotspots, or VPNs that bypass your network controls. A formal AI governance framework channels this demand productively.
8. No Formal AI Usage Policy Exists
If your organisation does not have a written AI acceptable use policy, you almost certainly have a shadow AI problem. The absence of policy is not the absence of use — it is the absence of governance. Employees interpret silence as permission.
According to recent surveys, over 70% of knowledge workers have used GenAI tools at work, but fewer than 30% of organisations have formal AI usage policies. This gap is where shadow AI thrives.
Creating an AI policy does not have to be complex. Start with our AI policy templates to establish baseline expectations for responsible AI use across your organisation.
9. Third-Party Risk Assessments Reveal AI Dependencies
During vendor reviews or compliance audits, you may discover that business-critical workflows have quiet dependencies on AI tools. A vendor might mention that your team shared data via an AI-powered integration, or an internal audit might reveal that a key report is generated using an unapproved AI service.
These discoveries are particularly alarming because they reveal not just usage, but dependency. If that AI tool goes down, changes its terms of service, or suffers a data breach, your operations are affected — and you did not even know the dependency existed.
10. Your Competitors Are Talking About AI Governance
If companies in your industry are publicly discussing AI governance, publishing responsible AI frameworks, or investing in AI security tooling — and you are not — your employees are likely using the same AI tools as theirs, just without the guardrails.
Shadow AI is an industry-wide phenomenon. The difference between organisations that manage it well and those that do not is not the presence of AI use — it is the presence of governance.
What to Do About Shadow AI
Recognising the signs is the first step. Here is a practical remediation roadmap:
- Conduct an AI discovery audit — Use network monitoring, SaaS management platforms, and employee surveys to map current AI usage across the organisation.
- Establish an AI acceptable use policy — Define what is permitted, what is restricted, and what data can never be shared with AI tools.
- Deploy AI-aware monitoring — Traditional security tools miss AI data flows. Invest in solutions that understand GenAI interaction patterns and can detect sensitive data in prompts.
- Provide approved alternatives — Blocking AI entirely is a losing strategy. Instead, offer sanctioned AI tools with proper security controls, data handling agreements, and enterprise features.
- Train your workforce — Educate employees on the risks of unauthorized AI use and the organisation's expectations. Make the policy accessible and the reasoning transparent.
- Implement continuous governance — Shadow AI is not a one-time problem. New tools launch weekly. Build ongoing processes to evaluate, approve, and monitor AI tools across the organisation.
Take Control of AI in Your Organisation
Shadow AI does not mean your employees are malicious — it means they are resourceful. The goal is not to eliminate AI use but to bring it under governance. With the right policies, tools, and culture, you can harness the productivity benefits of AI while protecting your organisation's data and reputation.
Aona helps organisations discover, monitor, and govern AI usage across their entire workforce. From detecting shadow AI to enforcing data protection policies, our platform gives security teams complete visibility into how AI is being used — and the controls to manage it safely.
Ready to uncover shadow AI in your organisation? Explore our AI governance guides at /resources/guides or compare AI governance platforms at /resources/comparisons to find the right solution for your team.