Examples of Shadow AI

Real-world examples of how ungoverned AI shows up inside businesses — and how to recognise, contain, and convert it into safe innovation.

Read the AI Governance Guide

What is shadow AI?

Shadow AI is any use of artificial intelligence tools outside official IT oversight or policy. It’s the natural result of employees trying to save time with accessible public tools — from ChatGPT and Gemini to code assistants and document summarizers — without waiting for formal approval.

The intent is usually good. The risk lies in where the data goes, who has access to it, and the absence of an audit trail.

Common examples inside modern organisations

  • Marketing teams use ChatGPT to draft client copy or blog posts containing unpublished campaign data, stored outside company systems.
  • Lawyers and consultants paste client materials into AI tools to summarise or draft clauses, unknowingly breaching confidentiality obligations.
  • Developers use GitHub Copilot or similar tools that may suggest code snippets with embedded proprietary logic or open-source licence risks.
  • Finance staff upload spreadsheets to “AI analysers” to detect trends, not realising the data is processed and retained in third-party clouds.
  • HR teams use AI résumé screeners without ensuring fairness, explainability, or compliance with employment law.
  • Support teams feed customer tickets into chatbots to generate responses, exposing personal data and bypassing approved CRM systems.

Why shadow AI spreads so fast

  • Accessibility: public tools are frictionless — no setup, just an account and a browser.
  • Pressure to deliver: teams need faster output and see AI as a shortcut when official channels lag behind.
  • Lack of awareness: many users don’t understand how prompts or uploaded data may be stored or reused by providers.
  • Missing internal alternatives: when IT hasn’t provided an approved, compliant workspace, people fill the gap themselves.

The risks of unmanaged AI use

  • Data leakage: confidential or regulated information may leave your control and become unrecoverable.
  • No audit trail: decisions or content created through AI cannot be traced or verified later.
  • Reputational damage: clients expect assurance that their data is handled responsibly.
  • Compliance breaches: violations of GDPR, ISO 27001, SRA, or sector-specific rules can trigger fines and loss of accreditation.
  • Model bias and error: unreviewed outputs may include inaccuracies or bias, leading to flawed advice or unfair outcomes.

Turning shadow AI into governed innovation

  • Acknowledge it: don’t punish early adopters; they’re often your most forward-thinking staff.
  • Map the landscape: survey teams to understand which AI tools they already use and for what purposes.
  • Create safe alternatives: provide an approved AI workspace where experimentation is logged, retained, and compliant.
  • Update policies: include generative AI within data-handling, retention, and acceptable-use frameworks.
  • Educate continuously: short awareness sessions and visible examples are more effective than lengthy policy PDFs.

The goal isn’t to eliminate shadow AI — it’s to replace secrecy with transparency and risk with opportunity.

How Satori helps bring AI into the light

  • Satori Cloud gives teams a governed environment to use ChatGPT-5, Claude, or Gemini with full visibility and data control.
  • Prompts and responses stay within your organisation’s boundary — not the provider’s servers.
  • Each interaction is logged, attributed, and retained according to your retention policies.
  • Compliance teams can review AI activity just like any other information system, aligning with ISO 27001, GDPR, and sector standards.