How do I find out what AI tools my team is using?

The fastest method: a short anonymous survey asking 'What AI tools do you use in your day-to-day work?' Most employees will be honest, especially if framed as learning rather than policing.

Should I ban tools that weren't approved?

In most cases, no. Banning creates workarounds and resentment. Instead, create a fast-track approval process and default allowlist of common safe tools.

What's the main risk from shadow AI?

Data exposure — employees pasting sensitive client data, code, or PII into consumer AI tools that may use that data for model training or are not covered by your DPA.

How do other small teams handle this?

The most common approach is a lightweight AI register: a shared spreadsheet where team members log tools they use, what data they feed in, and who approved it. Simple and auditable.

Shadow AI

Managing Shadow AI in Small Teams

Shadow AI — employees using AI tools without IT or leadership approval — is now the default, not the exception. Here's how to detect it, address it without heavy-handed policy, and turn it into a governance opportunity.

Start here

Pillar guide

Shadow AI Policy for Small Teams: 2026 Detection and Governance Guide

Shadow AI adds $670K to breach costs, and small teams have the highest exposure. How to detect unsanctioned AI tools and govern them without an IT team.

17 min read

Related guides

Governance · 10 min

AI Adoption Governance: Stop the Quiet Rebellion

80% of employees bypass or avoid company AI tools. How small teams close the governance trust gap and stop shadow AI use without triggering a rebellion.

Governance · 11 min

Shadow AI Governance: 3-Layer Detection and Controls for Tech Teams

CASB misses browser-based personal AI sessions. Shadow AI governance for tech teams: real visibility into unapproved AI use without blocking engineers.

Frequently Asked Questions

How do I find out what AI tools my team is using?: The fastest method: a short anonymous survey asking 'What AI tools do you use in your day-to-day work?' Most employees will be honest, especially if framed as learning rather than policing.
Should I ban tools that weren't approved?: In most cases, no. Banning creates workarounds and resentment. Instead, create a fast-track approval process and default allowlist of common safe tools.
What's the main risk from shadow AI?: Data exposure — employees pasting sensitive client data, code, or PII into consumer AI tools that may use that data for model training or are not covered by your DPA.
How do other small teams handle this?: The most common approach is a lightweight AI register: a shared spreadsheet where team members log tools they use, what data they feed in, and who approved it. Simple and auditable.

Shadow AI

Managing Shadow AI in Small Teams

Start here

Pillar guide

Shadow AI Policy for Small Teams: 2026 Detection and Governance Guide

Shadow AI adds $670K to breach costs, and small teams have the highest exposure. How to detect unsanctioned AI tools and govern them without an IT team.

17 min read

Related guides

Governance · 10 min

AI Adoption Governance: Stop the Quiet Rebellion

80% of employees bypass or avoid company AI tools. How small teams close the governance trust gap and stop shadow AI use without triggering a rebellion.

Governance · 11 min

Shadow AI Governance: 3-Layer Detection and Controls for Tech Teams

CASB misses browser-based personal AI sessions. Shadow AI governance for tech teams: real visibility into unapproved AI use without blocking engineers.

Frequently Asked Questions

How do I find out what AI tools my team is using?: The fastest method: a short anonymous survey asking 'What AI tools do you use in your day-to-day work?' Most employees will be honest, especially if framed as learning rather than policing.
Should I ban tools that weren't approved?: In most cases, no. Banning creates workarounds and resentment. Instead, create a fast-track approval process and default allowlist of common safe tools.
What's the main risk from shadow AI?: Data exposure — employees pasting sensitive client data, code, or PII into consumer AI tools that may use that data for model training or are not covered by your DPA.
How do other small teams handle this?: The most common approach is a lightweight AI register: a shared spreadsheet where team members log tools they use, what data they feed in, and who approved it. Simple and auditable.