The IMF groups more than 150 economies as emerging and developing economies. As someone who originates from one of these “developing” nations, I have noticed a shift. A number of things are happening at the same time that appear to have created a perfect storm for opportunity, and AI may help us harness it.

In my career, I have found myself on the unsexy side of software engineering. My work has mostly been in enterprise systems: building internal tooling and operational solutions that cut overhead and enable growth. As such, I have worked across accounting, insurance, construction, manufacturing, and other sectors. The industries differ, but many of the underlying principles translate across them.

In more developed markets, these kinds of business tools are already well established. In the EU, for example, more than half of enterprises with at least ten people employed were buying cloud services in 2025. Whereas in developing markets, I keep noticing that biggest hurdle is affordability and reliability. More people being online does not necessarily mean that connected services are affordable enough or dependable enough to become the default way of doing business. ITU continues to highlight gaps in connectivity quality and affordability, while GSMA identifies a substantial gap between mobile broadband coverage and actual use in Africa. To me, that means we should be careful about assuming that greater connectivity automatically translates into rapid consumer adoption.

The African continent provides a useful example. Fintech remains particularly prominent: Partech’s 2025 report puts it at 37% of the African tech funding it tracked, including equity and debt. That makes sense to me. The ability to move money meets a core need in any society. However, moving money through these services comes at a cost. It is not like the UK, where everyday personal banking and transactions are often effectively free. Mobile money has a different commercial model: GSMA reports that customer fees remain the main revenue source for more than two-thirds of the providers responding to its global survey. Cash also remains deeply embedded in parts of the economy. Agricultural payments in sub-Saharan Africa are one clear example, even among people who already have financial accounts. Fees are not the whole explanation; the surrounding infrastructure and payment habits matter too.

This is an oversimplification, and the continent is not one uniform market. However, it provides context for the opportunity I see.

Across the markets I know, there are well-established software incumbents serving key sectors. Some of their systems date back to the 2000s; others are newer but still feel remarkably dated in their execution. They do the job, but they can lack polish, convenience, and flexibility. These providers secured business by meeting an acute pain point. That matters. These are validated lanes.

The opportunity, as I see it, is to build world-class platforms around needs that are already understood. I believe AI is lowering the cost of implementing the kinds of capable, polished systems that would previously have been much harder for a small team to attempt. It does not remove the need to understand the industry or build something reliable, but it changes what is within reach.

The goal is not to reinvent the wheel but to refine it.

Once the acute pain point has been met, there is room for convenience. There is room for better workflows, clearer information, and software that people do not have to fight with. My view is that there are businesses willing to pay for those improvements. Their baseline has changed. What was once good enough does not have to remain good enough.

There also appears to be a different relationship between providers and clients around the idea of ownership. In the relationships I am describing, that expectation exists at both the individual and company level. The established culture shows that people and businesses want ownership of their data, and they want control over where it lives.

What’s mine is mine; what’s yours is yours.

You own the platform and the intellectual property, but I must own my data. It must remain within my control and, where that is my requirement, within my own environment. To me, that is not an inconvenience to design around later. It is part of the product.

And when I talk about SMEs, I am not necessarily talking about tiny businesses. You could have a manufacturer with $2 million in revenue running an ERP that is fifteen years old or more. A construction firm with over $10 million in revenue could be managing its day-to-day operations and inventory through Microsoft Office and email.

This is the reality on the ground that I am talking about.

Could these businesses adopt cloud-based systems from established global players? Yes. Would those systems work as reliably as intended within their environments and fit the way they want to operate? Not necessarily.

For the businesses I am describing, the laptops and smartphones are often already there. The people using them are increasingly mobile. What cannot always be taken for granted is the infrastructure around them.

So build platforms whose core work does not stop when the internet does. Build around the conditions these businesses actually operate in, rather than the conditions we would prefer them to have.

These are not the sexiest startups, but they address real business needs and provide an avenue for growth and wealth creation. I expect AI to make its way into these businesses as well, and I am not convinced that the current incumbents are best placed to lead that transition. That is why I believe there has rarely been a better time to build.

Nothing flashy. Nothing sexy. Take the stone wheel and modernise it.