Research suggests that nearly 79% of business leaders expect AI to reshape operations by 2026. I think that feels right: the changes are already visible. Many small businesses I’ve come across are reporting big efficiency gains, significant reductions in manual work, and noticeable improvements in customer engagement. From my perspective, AI is no longer a distant promise. It’s here, and it’s already making SMEs faster, smarter, and more competitive.

Levelling the playing field

What strikes me most is how AI is levelling the playing field. I’ve seen smaller businesses manage development cycles that look very similar to those of far larger organisations, simply because AI allows them to work at speed. Instead of needing big teams or lengthy processes, small groups can now build, test, and launch ideas in weeks.

When I was at THG in the UK, I used AI tools to automate the update of database connection strings across 17 services. Normally, that would have taken days of manual effort. With AI, it was done in under an hour. In my opinion, that’s a perfect example of how a small team can deliver enterprise-level results without enterprise-level resources.

I also worked with THG’s AI team to improve customer email scheduling by region. By letting the system figure out the best time to reach each audience, engagement jumped significantly. To me, that’s the kind of insight SMEs can use straight away – AI lets them be faster and more personal than competitors weighed down by slower processes.

Earlier in my career at Tech Mahindra, I was building service-oriented systems and web applications for clients. Even though the tools back then weren’t branded as AI, I now realise the principle was the same: finding ways to make technology do the heavy lifting so businesses could work more efficiently. I think that mindset is exactly what SMEs need today as they adopt AI.

Integration timelines

A lot of SME owners I speak to assume AI will take years to integrate. From what I’ve seen, the technical side is often surprisingly quick – sometimes just weeks. The real challenge, in my view, is the data. Getting the right data in shape, cleaning it, and making sure it actually supports business goals often takes longer than the coding itself.

One e-commerce company I supported wanted AI-driven personalised emails. We set up the workflows quite quickly, but preparing the customer data – spread across multiple systems – took almost two months. Once it was ready, the results were clear: open rates up 35%, click-throughs up 25%, and sales from email campaigns up 20%.

I’ve noticed the same pattern in bigger projects too. At Tech Mahindra, when we delivered the DocuWare document management system, the installation itself was fairly simple. What consumed time and energy was consolidating and migrating business records securely. For me, it reinforced the lesson: the technology is not the hardest part; the data and planning are.

Why many SMEs hold back

If AI is so effective, why don’t more SMEs dive straight in? In my experience, it usually comes down to cost concerns and cultural hesitation.

I think many owners fear AI is too expensive or overcomplicated. Others worry that staff will resist, seeing it as a threat to their jobs. In practice, though, I rarely find technical skills to be the main issue – most modern AI tools are designed so that non-specialists can use them. The bigger question is whether the team is ready to change how they work.

One business I supported had exactly this issue: the owner wasn’t convinced, and staff were sceptical. So, instead of a grand project, we started small – with a low-cost AI tool for stock management. Once staff saw it cut down repetitive tasks and freed them up to focus on customers, their resistance softened. The owner, meanwhile, noticed fewer stockouts and better cash flow. Step by step, they expanded into marketing and beyond. To me, that shows how powerful a small, low-risk first step can be.

Practical advice

Whenever someone asks me where to begin with AI, I usually suggest three simple steps.

1. Look closely at your workflows – in my opinion, the best place to start is identifying repetitive or costly tasks. That’s where AI usually adds the most immediate value
2. Pick one pilot project – don’t try to transform everything at once. Begin small, with affordable tools, and learn as you go
3. Measure outcomes clearly – set KPIs like time saved, accuracy improved, or revenue increased, so you can actually see the value

When I was working as a solutions architect at Tech Mahindra, I learnt the importance of breaking big initiatives into manageable parts. It builds trust and shows results quickly. I think SMEs adopting AI should take the same approach – prove the value in one area, then expand gradually.

What the future holds

Looking ahead, I believe SMEs will soon be able to deliver services and customer experiences that rival much larger firms – but with leaner teams and budgets. AI will make automation of day-to-day operations the norm, not the exception. I also expect decision-making to become more data-driven, with AI surfacing insights that were once hidden.

Most importantly, I think we’ll see more employees working confidently alongside AI, rather than fearing it. The tools are getting easier, and the mindset is shifting. As that happens, customer expectations will also rise. People will come to expect faster responses, more personalisation, and continuous innovation – even from small businesses.

For SMEs, that’s both an exciting opportunity and a challenge. The question is no longer whether AI will shape the market, but how quickly smaller firms can embrace it.

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