Shadow AI is already in your business. What are you doing about it?

Shadow AI is what happens when AI adoption moves faster than organisational visibility. Prompts, documents and copied text can move into unapproved services before teams know which tools are in use, what data has been shared or how that information may be reused.

That makes the risk harder to contain than traditional Shadow IT. AI tools and agents can interpret business context, combine information, generate new outputs and act across connected systems using the data and access they are given.

Organisations need to build a secure AI foundation that gives them visibility of AI use, control over sensitive data and governance for agents before informal adoption becomes embedded risk.

Risk grows when sensitive data leaves your sight

We know that people are embracing and experimenting with AI in enormous volumes. And who can blame them. The tools are everywhere, the benefits are obvious and most users are exploring how these new tools can make their lives easier at work (and probably at home too).

The issue and accompanying risk arises if this usage is going unseen within the organisation. Or to put it another way, if sensitive information is moving into environments your organisation doesn’t control. Client proposals, strategy material and legal documents all become harder to protect once they are copied into an unapproved service.

And to put this risk into context, Tech Radar recently reported as many as two-thirds of workers admit to using AI tools not officially approved by their employers.

To tackle this, governance needs to get specific. Know where your sensitive data lives, classify it properly and apply controls that stop the data leaving unnecessarily. Organisations should also guide users towards approved AI tools like Microsoft Copilot, where enterprise-grade data protection is in place and inputs are not used to train foundation models.

AI agents are identities and need to be governed accordingly

This becomes even more crucial with the rise of Agentic AI.

Now we’re seeing agents being granted access to systems, repositories and workflows.

With such potentially unfiltered access, added to increasing capabilities to take autonomous action, we have to start treating these agents as powerful identities, much as we do with human users. We need to ensure they have a named owner, defined purpose, least-privilege access, approval records, access reviews and audit trails.

People need a safer route that works for them

Whenever new risks materialise, there’s the immediate temptation to bring in a blanket ban or blockage. But in truth, such actions rarely address the reasons people turned to those tools in the first place.

Employees use AI because it helps them move faster, remove friction and get to a better first draft, answer or analysis. If sanctioned services are slow to access, poorly configured or less useful than consumer alternatives, workarounds will continue. The better answer is to give people a trusted route to the benefit: approved AI tools, clear guidance, sensible guardrails and a fast way to assess new use cases.

Good governance should help people use AI safely while avoiding a choice between productivity and policy.

Education has to sit alongside the controls. People need to understand why certain data cannot be used in certain tools. That includes the board, technical teams and everyday users, because Shadow AI is an enterprise behaviour rather than a niche security issue.

Your Microsoft estate may already give you a strong starting point

For Microsoft-led organisations, the starting point is often stronger than it first appears. Microsoft is increasingly connecting AI adoption, agent governance, data protection and identity security across its platform, with the same priorities reflected in product evolution and new licensing models.

Tools across Microsoft Purview, Microsoft Defender and Microsoft Entra, for instance, can support the core work. Working in unity within your estate they enable an understanding of where sensitive data sits, identifying risky or unsanctioned app use, applying access controls and giving security teams a clearer view of how users, applications and agents interact with information.

And, of course, the identity layer should sit at the centre of that approach.

As AI agents become part of business workflows, organisations need to know who owns them, what purpose they serve, what they can access and how that access is reviewed over time. This is where new tools like Microsoft Agent 365 bring increasing value and governance because agents need inventory, ownership, lifecycle management and security oversight as they become a new class of identity in the enterprise.

Bring Shadow AI into the open

Shadow AI is already part of how work gets done. Managing it requires a deliberate response: find what is already happening, protect the data that matters, give users a safer path and govern agents with the same seriousness as any other identity with access.

For Microsoft-led organisations, this is also a chance to get more value from the security, identity and data protection capabilities already available in the platform. Better visibility, clearer ownership and practical controls can turn unsanctioned AI use into safer, more deliberate adoption.

Kocho helps organisations assess AI risk exposure, improve visibility across AI tools and agents, and apply the governance and security controls needed for confident adoption.

If you need to understand what is already in use, where the risk sits and which controls to prioritise, we’d love to hear from you.

Your Shadow AI questions answered