By Daniel Shone, founder of Apex Computing
Artificial intelligence has, with surprising speed, moved from emerging technology to everyday business tool. Anyone can access it, from enterprise to solopreneur, and it can help in such a variety of ways that it seems almost foolish to overlook its potential. From customer relationship management and automated communications to content creation and workflow optimisation, AI is bringing efficiency, insights, and even scalability. But beneath those advantages a problem is being overlooked: while businesses are accelerating their AI adoption, very few are paying attention to the security and governance implications that come with it.
The problem of AI adoption without oversight
The unusual thing about AI adoption within SMEs is that it seems to be happening organically. Rather than the expected, highly orchestrated digital transformation projects that have always accompanied any form of IT upgrade, AI tools frequently enter businesses through individual experimentation. An employee may begin using generative AI to draft campaign materials. A sales rep might use it to personalise outreach emails. And use grows incrementally over time. But this lack of visibility causes problems. Even for large businesses.
The Logicalis CIO Report found that only 37% of enterprise organisations have complete visibility over the AI tools being used within their business. So, if major corporations with dedicated IT and governance teams face difficulties maintaining oversight, smaller organisations are inevitably going to struggle, leaving them unsure of what information is being shared, where it is being processed, or how it is being stored.
The hidden AI data risks
The fact that AI is so new and has been adopted so quickly accounts for most of these concerns. But it’s also that the risks associated with AI are often less obvious than those linked to traditional software applications. Most users view AI tools as simple productivity platforms, unaware of the fact that information entered into AI systems may be stored, logged, analysed, or transferred across multiple environments. In some circumstances, data may also be retained for monitoring, training, or quality-improvement purposes. And this doesn’t just raise security concerns, but can become a significant compliance problem.
Part of this comes down to employee awareness. Most employees are not intentionally putting their businesses at risk. In fact, the opposite is usually true. They’re looking for ways to work more efficiently, reduce repetitive tasks, and improve their output. AI tools hold the potential to do all of that. But when AI creeps in organically, businesses are unable to put in the groundwork. They don’t think about providing guidance on the appropriate use of AI until AI is already widely in use. And without policies, training, or clear expectations, there is little reason for staff members to question whether certain information should be entered into a platform or whether a particular tool has been approved by the business. And this is where security becomes a concern.
Productivity vs security
There is no denying the value AI can deliver in terms of productivity. Whether it’s faster admin, improved responsiveness, or the automation of the soul-destroying repetitive tasks that all businesses struggle with. But if productivity comes at the expense of security or compliance, a business should be concerned. A single security incident can wipe away the value of all of those efficiency gains. Causing not just penalties, but disruption, reputational damage, and loss of customer trust. So, the goal needs to be to balance the innovations of AI with appropriate security measures.
How SMEs can safely scale AI adoption
Avoiding AI isn’t really an option anymore. If you ignore it, your teams will bring it in through the back door. If you ban in, you’ll be overtaken by your competitors. The best approach is to invest in sustainable AI adoption. And that means focusing on visibility, policy, and governance.
Before you do anything else, you need to know exactly what AI tools are being used across your business, who is using them, and how they are being applied. And that means an internal audit, either conducted in-house or outsourced to professionals.
Once you have a clear picture of what’s being used, you need to develop a formal AI policy that lets your teams know what they can and can’t do. Keep it practical and informative, establishing clear boundaries around sensitive data.
That done, you need to put steps in place to ensure that AI governance is an ongoing process. Regular reviews of AI usage, security controls, and policies help to ensure that your business is properly protected.
AI use is only going to grow in the coming years. For SMEs, this could be a really great thing, potentially levelling the playing field and enabling them to compete with larger competitors. But if that’s going to happen, if AI is going to become the competitive advantage that it has the potential to be, security must be successfully managed. And that process needs to start now.
