AI adoption is outpacing security in SMEs

Artificial intelligence has moved from being an optional extra to a core business function in a remarkably short time. What was once the domain of large enterprises with deep pockets is now a feature of the infrastructure of the majority of SMEs. Even freelancers are using it, for everything from CRM integrations and chatbot functions to content generation and workflow automation. 

 

It’s enabling businesses to operate with greater efficiency and to scale more quickly and efficiently. All of which can only be viewed as a positive. But it comes with trade-offs that many businesses haven’t yet understood.

 

 

Rapid AI adoption opens unseen risks

AI adoption is happening almost organically in many SMEs. There are no planned or structured programmes, but rather a gradual accumulation. The marketing team use generative AI to run off a quick PR. A salesperson experiments with automated email drafting. Operations teams integrate AI-driven tools into existing systems. The problem is that this incremental uptake comes without oversight.

 

Even at the enterprise level, organisations struggle to track AI usage comprehensively - the Logicalis CIO Report found that only 37% of enterprise organisations have full visibility of AI tool usage. In smaller businesses, where AI creeps in without governance and visibility is often poor, the impact can be damning. Because, unlike the original SaaS platforms, AI systems can introduce risk through the way they process inputs. Data entered into AI tools may be logged, stored, or transmitted depending on configuration, provider policies, and integrations. In some cases, it may be retained for monitoring or improvement purposes, or processed via third-party systems. And the original owner is often completely unaware of this.

 

The issue is not the use of AI itself, but how it is used. When you draft generic content, the risk is minimal. But when that content relies upon the inputting of sensitive customer records, financial data, or proprietary business information, it’s another matter entirely. And without clear oversight, organisations can lose track of where data is flowing. That makes data leakage a very real concern.

 

Adding to the problem is a lack of awareness at the employee level. Most users are not deliberately careless; they are focused on getting their jobs done as effectively as possible. But without clear policies or guidance to follow, most of them have no reason to question how data is handled once they’ve entered it into an AI system. When tools promise speed and simplicity, adoption tends to happen without hesitation.

 

 

Productivity vs security and compliance

Of course, none of this diminishes the genuine value AI can bring. The efficiency gains can be incredible. Essential admin tasks that once took hours can now be completed in minutes, so teams can focus on higher-value work.

 

However, speed isn’t everything. And if productivity comes at the expense of security or regulatory compliance, the overall impact can be negative. Data protection requirements are becoming more stringent, and the complexity of digital security continues to increase. A single error, whether through data exposure or misuse, can be incredibly damaging, both financially and reputationally.

 

 

What SMEs should do before scaling AI

The instinct is to slow AI adoption, but in many respects, that can also slow progress. What’s actually needed is to put controls in place to make sure AI can be used safely. And the starting point for that is visibility.

 

Businesses need a clear understanding of which AI tools are being used, by whom, and for what purpose. Conducting an internal audit is the best way to achieve that. While it is possible to manage this in-house, the majority of companies bring in external support to ensure that nothing is missed. An external team can also provide guidance for the next steps.

 

Then you need to focus on creating an AI policy. Effective AI usage requires clear, accessible guidelines. That means defining which tools are approved, what types of data can be used, and what must never be shared, so that your teams can use AI responsibly.

 

Once you’ve done that, you need to put processes in place to ensure that you regularly review both your policies and the AI tools being used. AI tech is evolving rapidly, and new risks are coming every day. Your security needs to keep pace with that, which means that you need to review policies and change tool use according to both regulations and business needs.

 

AI is not a passing trend. Its role in business operations is only going to develop over time. And for SMEs, that presents an amazing opportunity to be able to compete with larger businesses. But at the same time, it introduces risks that cannot be ignored. The challenge is to find ways to mitigate the risks of AI adoption through the introduction of a supportive ecosystem of control, awareness, and discipline.

 

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Daniel Shone is the founder of  Apex Computing, supporting SMEs with IT, cyber-security and AI solutions and helping organisations drive real value, resilience and growth

 

Main image courtesy of iStockPhoto.com and Shinsei Motions