There is a particular kind of economic trap that is easy to walk into and difficult to name until you are already inside it. It does not announce itself. It arrives dressed as progress, as growth, as the encouraging sight of a country embracing new technology with enthusiasm and speed. Nigeria is currently walking into that trap with artificial intelligence, and the people least likely to notice are the business owners doing the most enthusiastic adopting.
A new review published this week, the Adoption of Artificial Intelligence in Nigeria: A Macro and Micro Economic Review, puts the picture in terms that deserve more attention than they have received. More than 70 per cent of Nigerians have interacted with generative AI tools. Ninety-three percent of surveyed organisations say they have begun adopting AI technologies. Nigeria ranks 38th globally and first in Africa on the Global Index on Responsible AI, a jump of 42 places in two years. By almost every adoption metric available, Nigeria looks like a country sprinting ahead.
The report’s warning sits quietly underneath those figures. Nigeria remains largely a consumer of technologies developed abroad, exposing critical sectors to external control and limiting the country’s ability to capture the full economic value of the AI revolution. In plain terms: Nigerians are using AI enthusiastically and the companies building that AI, almost entirely foreign, are the ones collecting the economic reward.
This is not a new pattern. It is the oldest pattern in the relationship between developing economies and technological revolutions. The country that consumes the technology sends money to the country that built it. The country that built it gets richer. The country that consumes it gets more efficient, temporarily, until the pricing changes, the terms of service shift, or the foreign provider decides that the market is no longer worth serving on the same terms. At that point, the consumer country discovers that it has become dependent on something it does not control and cannot replace quickly.
For Nigerian SME owners reading this, the immediate relevance is not abstract. Every subscription paid to a foreign AI platform is revenue leaving Nigeria. Every piece of business data processed by a foreign AI model is Nigerian data strengthening a foreign company’s technology. The report makes this point directly, noting that valuable Nigerian data is being used to improve foreign-owned AI systems while local institutions remain reliant on those same systems for core operations. The business owner paying monthly for a foreign customer service chatbot, a foreign bookkeeping tool, or a foreign content generation platform is, in a small but real way, contributing to the widening of a gap that will eventually affect the price they pay and the terms on which they can access these tools.
There is a deeper problem that sits closer to the daily operations of a small Nigerian business. The leading AI models in global use were trained predominantly on English language data, with limited representation of Nigerian languages. The report flags this directly, warning that tools built on those models have a reduced ability to accurately interpret Hausa, Yoruba, Igbo, and other languages spoken by the majority of Nigerian consumers. A business owner using a foreign AI tool to communicate with customers who speak primarily in Nigerian languages is using a tool that was not designed for that conversation and will perform less well in it than it would in standard English. The technology gap is not only about who profits. It is also about whether the tool actually works for the people it is supposed to serve.
None of this means Nigerian businesses should stop using AI tools that are currently available and useful. That would be the wrong conclusion entirely. A small business owner who stops using a helpful tool on principle achieves nothing except falling behind competitors who have no such reservations. The argument is not against adoption. It is about what adoption without local investment produces over time.
What it produces is dependency. The report notes that Nigeria’s reliance on foreign cloud providers and frontier AI models raises legitimate concerns about digital sovereignty. When the infrastructure your business depends on is owned and controlled elsewhere, your ability to operate is ultimately subject to decisions made by people who have no particular interest in whether your business survives. That is not a comfortable position for any business to be in, and it is the position that accelerating foreign AI adoption without equivalent local development is steadily creating.
The question worth asking at the business level, not just the national policy level, is whether any of the money currently flowing out of Nigeria into foreign AI subscriptions could be redirected toward Nigerian-built alternatives, even partial ones, even imperfect ones, that keep more of that value inside the economy and inside the business community that generated it. The report points to genuine progress in Nigerian AI research, noting that local scholars have produced more than 11,600 AI-related academic publications. The intellectual capacity to build is present. What is missing is the commercial demand that would make building those local alternatives financially viable.
That commercial demand comes from businesses making deliberate choices about where they spend their technology budgets. It is not a romantic argument about patriotism. It is a practical argument about long-term cost, control, and resilience. A business that builds its operations around tools it cannot influence, cannot replace, and cannot negotiate with on equal terms has introduced a structural vulnerability that will not be visible until the day it suddenly matters.
Nigeria is adopting AI faster than almost anyone. That is genuinely encouraging. The harder question is whether the country is building anything from that adoption that stays, compounds, and strengthens the economy that is doing the adopting. Right now, the honest answer is not enough. And the businesses best positioned to change that are not the government agencies or the large corporations. They are the 39 million small and medium enterprises whose collective purchasing decisions could, if directed differently, begin to shift what gets built and where the value lands.
The choice of which tool to use next week is smaller than it sounds. Multiplied across millions of businesses, it is not small at all.
