Artificial Intelligence is rapidly becoming part of everyday work.
According to Microsoft’s Work Trend Index, employees are increasingly turning to AI tools to help improve productivity, reduce repetitive tasks, and access information quicker. However, as AI adoption accelerates, many employees are beginning to use AI tools without formal approval, governance, or oversight from their organisation.
This growing trend, often referred to as Shadow AI, presents a new challenge for businesses. Whilst it is highly likely employees have good intentions, the use of unapproved AI tools can create security, compliance, and data governance risks that their organisations may not be aware of.
As AI becomes increasingly embedded into day-to-day operations, understanding and managing Shadow AI is becoming a critical priority for IT leaders, business owners, and security teams alike.
This article forms part of our The Dark Side of AI series, exploring the emerging security, governance and operational risks organisations should consider as AI adoption accelerates.
Generative AI – The Most Common Case of Shadow AI
One of the most common forms of Shadow AI involves employees using generative AI tools such as ChatGPT, Claude, Gemini, or other publicly available AI platforms without formal approval from their organisation. These tools are often adopted to improve productivity, accelerate research, generate content, or automate routine tasks. However, when AI tools are used outside of established governance and security controls, organisations may have little visibility into how data is being shared, creating potential risks relating to data protection, compliance, intellectual property, and reputational damage.
Why Employees Use Shadow AI
In many cases, employees are not intentionally bypassing security controls. They are often looking for faster ways to complete tasks, improve productivity, analyse information, create content, or automate repetitive parts of their day-to-day roles. The challenge for organisations is that AI adoption is frequently occurring faster than governance frameworks, policies, and approved tools can be implemented.
The Risks of Shadow AI
The use of unapproved AI tools presents threats for organisations of a financial, operational and regulatory nature. Risks include including data leakage, compliance breaches, intellectual property exposure, and inaccurate AI-generated outputs. Employees may unknowingly share confidential business information, customer data, financial records, or commercially sensitive information with third-party AI providers.
Data Privacy and Compliance Concerns
Many organisations operate in highly regulated environments where there are rigorous data handling requirements. If employees upload sensitive information into public AI tools, organisations may face challenges relating to GDPR compliance, data residency, retention policies, and contractual obligations.
Why Shadow AI Is Difficult to Detect
Shadow AI is difficult to detect because it requires content-level visibility rather than simple network tracking.
Unlike traditional software deployments, AI tools are often accessible through a web browser and can be adopted without any involvement from IT teams. This creates a lack of visibility around which tools are being used, what information is being shared, and how AI-generated outputs are influencing business decisions.
