Risk · R-089 · Governance & Accountability
Shadow AI use
Staff use AI tools that have not been approved, placing organisational data and decisions outside any control.
- Severity
- High
- Audience
- Board · Heads-of · Practitioner
- Frameworks
- Principle 5 · Annex A.9 · GOVERN 1 · Article 5
- Responsible AI domain
- Lifecycle stage
- Reviewed
- 2026-11-10
What it is
Capable AI tools are free or cheap, need no installation and are useful at once. Staff adopt them to do their work, through personal accounts, browser extensions or features inside other software. None of it passes assessment. The risk is partly what goes into these tools, which may be confidential or personal, and partly what comes out, which enters work products and decisions with no check on quality or origin.
How it happens
- No approved tool meets a real need, or the approved tool is worse.
- The approval process is slow or unknown.
- Policy prohibits use and provides no alternative.
- AI features appear inside applications staff already use.
Why it matters
Data disclosed to an unapproved provider may be retained, used for training or exposed, with no contract governing it. Outputs relied on in advice, code or analysis carry errors nobody is positioned to catch. The organisation is accountable for both and has sight of neither.
Warning signs
- Network traffic to AI providers with which there is no contract.
- Expense claims for AI subscriptions.
- Work products with the marks of generated text.
- Staff surveys report use well above approved figures.
Who owns it
The owner of the AI policy is accountable for a workable position on permitted use. Security monitors for unapproved tools. Line managers are accountable for their teams' practice.
In practice
A paralegal pastes a draft settlement agreement into a public chatbot to tidy the wording. The firm's duty of confidentiality, its insurer and its data protection officer are all brought into play by an act that took thirty seconds and left no record. The same pattern generalises to any workplace where a useful tool is easier to reach than permission to use it.
Mitigating controls
Primary controls
- AI acceptable use policy Directive
- Defines which tools may be used for what. A policy approved by top management states what AI use is permitted, what is prohibited, what every system must pass through, who is accountable, and where to take a case the policy does not settle.
- Shadow AI discovery Detective
- Finds unapproved tools from network, procurement and expense data. Network, procurement, expense and software records are reviewed on a set cycle to find AI tools and features in use that are absent from the inventory.
Supporting controls
- AI literacy programme Directive
- Staff understand the risk of unapproved tools. Everyone who uses, relies on or makes decisions about AI receives training in what these systems are, how they fail and what the organisation's rules require.
- AI policy exception management Directive
- Gives a controlled, time-limited route to use a tool that is not yet approved. Departures from AI policy are requested in writing, risk-accepted by a named owner at the right level, time-limited, and tracked until they are closed.
- AI use-case intake and approval Preventive
- An accessible approval route reduces the incentive to go around it. Every proposed AI use is registered, screened, tiered and approved by a named authority before build or purchase begins, and again before it goes live.
- Prompt and context data loss prevention Preventive
- Blocks restricted data going to unapproved tools. Prompts, uploads and retrieved context are inspected before they reach a model, and blocked, redacted or flagged where they contain personal or restricted data.
Framework and clause references
| Framework | Clause | Title |
|---|---|---|
| Code of Practice for the Cyber Security of AI | Principle 5 | Identify, track and protect your assets Untracked assets cannot be protected. |
| ISO/IEC 42001:2023 | Annex A.9 | Use of AI systems Use of AI within defined bounds. |
| NIST AI Risk Management Framework (AI RMF 1.0) | GOVERN 1 | Policies, processes and practices for AI risk are in place and effective Policies governing use. |
| UK General Data Protection Regulation | Article 5 | Principles relating to processing of personal data Accountability for the processing involved. |
Sources
- ISO/IEC 42001:2023 – AI management systems ISO/IEC · framework
- NIST AI Risk Management Framework (AI RMF 1.0) NIST · framework
Related terms
How to cite
Axiom Verity (2026). Shadow AI use. Reference Library, R-089. https://axiom-verity.com/risks/shadow-ai-use. Reviewed 2026-11-10.
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