Research among UK SMB decision-makers found that 31% of businesses are already using AI tools, with a further 15% planning adoption.1
Yet formal AI adoption only tells part of a much bigger story. Shadow AI - the use of AI tools outside approved business processes or IT oversight - is becoming increasingly common. Even businesses with approved AI platforms may find employees using alternative tools, while those that have yet to adopt AI formally often discover employees experimenting independently to improve productivity.
This activity can be a useful signal of where AI is delivering value. The challenge is ensuring those benefits do not come at the expense of visibility, governance or control.
Before businesses can establish AI governance, they need to understand how AI is already being used.
Shadow AI is often viewed as a risk issue, but it can also provide valuable insight into how employees are trying to work more effectively. Left unmanaged, it can make it difficult for businesses to understand where company information is being shared, and which tools employees rely on to complete their work.
This lack of visibility becomes more important as AI adoption grows. The UK Government's Cyber Security Breaches Survey found that while 31% of businesses are using, adopting or considering AI, only 24% have measures in place to manage the associated risks.2
Visibility tells you where AI is being used. The next step is understanding what information is being shared.
Not all AI activity carries the same implications. Writing a social media post is very different from uploading customer information, financial data or commercially sensitive documents into external platforms.
As AI becomes part of everyday workflows, employees can unintentionally expose information that was never intended to leave the business. The challenge is rarely deliberate misuse. More often, people are simply trying to work more efficiently.
Strong data governance helps businesses identify sensitive information, apply appropriate controls and support responsible AI use without limiting productivity.
As businesses begin exploring platforms such as Microsoft Copilot, successful adoption depends less on the technology itself and more on the foundations already in place. If information is difficult to manage or access controls are unclear, those challenges can become more visible as AI use expands.
Preparing for Copilot therefore involves understanding how information is managed across the business and ensuring appropriate controls are in place before wider deployment.
A Copilot Readiness Assessment helps businesses identify governance gaps and establish a practical foundation for AI adoption.
Shadow AI is often seen as a governance challenge, but it is also a reflection of how employees are already engaging with AI in their day-to-day work.
Whether a business has formally adopted AI or not, employees are finding their own ways to use it to improve productivity and efficiency. The challenge is ensuring that innovation happens with the visibility and oversight needed to protect sensitive information and support future growth.
Businesses that gain this visibility now will be better positioned to govern, invest in and scale AI effectively.
Whether your business is already using AI or employees are introducing tools independently, gaining visibility is essential to making informed decisions about governance, security and future investment.
FluidOne can help you understand where AI is delivering value, where risks may exist and what steps will support safe, effective adoption across your organisation.
References
1 https://yougov.com/en-gb/articles/52730-we-polled-uk-sme-leaders-about-ai-adoption-heres-what-they-said
2 https://www.nibusinessinfo.co.uk/content/cyber-security-breaches-survey-202526
