Shadow AI: The Hidden Risk Inside Your Organisation

Artificial intelligence is already changing how people work. Employees are using AI tools to summarise documents, draft content, analyse data and speed up everyday tasks.

This appetite for innovation is positive, but it also creates a challenge many organisations are only beginning to address: Shadow AI. This happens when employees use AI tools, applications or plugins without formal approval, oversight or governance from IT, security or compliance teams.

For business leaders, the concern is not that employees want to use AI. It is that they may already be using it in ways the organisation cannot see, assess or secure.

Why Shadow AI Is Growing

Shadow AI is growing because generative AI is easy to access, easy to use and often genuinely helpful. Employees do not usually set out to create risk. In many cases, they are simply trying to work faster.

A marketing team might use an AI tool to draft campaign copy. A finance employee might upload spreadsheet data to generate a summary. A service agent might use a public chatbot to rewrite a customer response. Each example may seem harmless in isolation, but at scale these behaviours can create significant exposure.

The UK National Cyber Security Centre’s guidance on Shadow IT notes that a healthy cyber security culture makes it more likely for people to report unsanctioned technology use. That principle applies strongly to AI: employees need clear, safe and approved ways to use AI, rather than feeling they have to find workarounds.

The Hidden Risks Behind Everyday AI Use

The most obvious concern with Shadow AI is data leakage. Employees may paste confidential information, customer records, internal documents, financial data or commercially sensitive material into tools that have not been reviewed by the organisation.

But data exposure is only one part of the risk.

Shadow AI can also create problems around accuracy, accountability, intellectual property, regulatory compliance and decision-making. AI-generated outputs can sound confident while being incomplete, biased or incorrect. If those outputs are used in customer communications, reports or operational decisions without review, the organisation may not know where the risk entered the process.

The National Institute of Standards and Technology’s Generative AI Profile highlights several risks associated with generative AI, including confabulation, data privacy, information integrity, intellectual property and cybersecurity. These risks directly affect how organisations use AI in real business workflows.

For example, a team may unknowingly use AI to summarise outdated documents. An employee may rely on an AI-generated answer that has not been validated. A department may start using a plugin that connects to business data without IT oversight.

Shadow AI Is Also a Governance Problem

Many organisations are approaching AI from a technology perspective: which tools should we buy, which licences do we need, and which use cases should we prioritise?

Those questions matter, but Shadow AI is just as much about governance.

Organisations need to know who is using AI, what tools are being used, what data is being shared, how outputs are reviewed, and who is accountable for AI-enabled decisions. Without that visibility, it becomes difficult to manage risk or demonstrate compliance.

The Irish National Cyber Security Centre’s Secure AI guidance for public sector bodies includes practical considerations such as AI literacy training before access is granted, acceptable use, data handling, reporting concerns and the risks of Shadow AI. While the guidance is aimed at public sector adoption, the principles are useful for any organisation seeking to adopt AI securely.

The goal should not be to block AI adoption. The goal should be to create a framework that allows employees to use AI safely, consistently and with confidence.

Why Approved AI Tools Still Need Strong Foundations

Some organisations assume that adopting an enterprise AI platform will solve the problem. In reality, approved tools are only part of the answer.

Even when using enterprise-grade solutions such as Microsoft 365 Copilot, the quality and safety of AI outputs depend heavily on the environment around them. Permissions, data classification, document governance, access controls and information architecture all matter.

Storm’s Microsoft 365 Copilot services help organisations prepare for Copilot adoption by aligning technology, data, governance and user enablement. This is important because Copilot can only be successful when the underlying Microsoft 365 environment is ready to support secure and relevant AI experiences.

SharePoint governance is especially important. If employees have access to too much information, or if sensitive documents are poorly managed, AI tools may surface content that should be restricted. Storm’s SharePoint services support organisations with document management, governance, collaboration and adoption across Microsoft 365.

How to Bring Shadow AI Under Control

Managing Shadow AI starts with visibility. Organisations need to understand where AI is already being used, which teams are experimenting, and what types of data or workflows are involved.

A practical first step is to run an AI usage assessment. This can include employee surveys, application discovery, security reviews and workshops with business teams. The aim is not to punish experimentation, but to understand demand and identify where approved solutions could provide safer alternatives.

From there, organisations can build an AI governance framework that includes:

Clear acceptable use policies
Guidance on what data can and cannot be used with AI tools
Approved AI platforms and tools
Role-based access and permissions
Human review for high-impact outputs
Training for employees and managers
Monitoring, reporting and incident response processes

Storm’s Cyber Services support organisations across areas including Executive Assurance, Security Operations Centre, Microsoft Defender, Compliance Management, Vulnerability Assessment, Managed Detection & Response, Microsoft Sentinel and Virtual CISO services.

For organisations that need strategic cyber leadership without a full-time internal CISO, Storm’s Virtual CISO service can help shape cyber security strategy, policies, processes and controls, supported by cyber defence experts and security professionals.

Creating a Culture of Safe AI Adoption

Technology controls are essential, but they are not enough on their own. Shadow AI often grows when employees feel that official tools are too slow, too restrictive or not aligned to their needs.

That is why AI governance needs to be practical. Employees should understand not only what they cannot do, but what they can do safely.

Training should include real examples: when it is acceptable to use AI for drafting, what data should never be entered into public tools, how to validate AI outputs, when to escalate concerns, and which approved tools should be used for different tasks.

The objective is not to slow innovation down. It is to make AI adoption sustainable.

Looking Ahead

Shadow AI is already present in many organisations. Employees are experimenting because they can see the value, but without clear guardrails, that experimentation can quickly become unmanaged risk.

The organisations that benefit most from AI will be those that combine innovation with governance, cyber security, data protection and employee enablement.

If your organisation is exploring Microsoft 365 Copilot, reviewing AI governance or concerned about unmanaged AI use, Storm can help identify risks and build a safer path to AI adoption.