Over 170 million Nigerians access the internet mainly through their mobile phones. For most, fintech, ride-hailing, and health apps are essential tools for survival.
Yet these apps rarely use AI beyond basic automation, meaning millions miss out on smarter services that could transform their financial, health, and daily lives.
But these apps remain largely transactional, not intelligent. They help users complete tasks, but they don’t learn, adapt, or personalise experiences in meaningful ways.
Artificial intelligence, when mentioned in Nigeria, is still too often confined to policy papers, academic conferences, or high-level discussions, not embedded into the apps that everyday people rely on.
This disconnect means we are missing the opportunity to make technology truly responsive to local needs.
Globally, the story is different. The AI in mobile apps market is projected to reach nearly $85 billion by 2030, up from $19.4 billion in 2024, according to Grand View Research. Countries and companies worldwide are embedding intelligence into everything from financial tools to healthcare assistants.
Nigeria risks being left behind if our apps remain stuck in the “digital clerk” phase. And yet, the talent exists locally: communities like Andela, Decagon, and Google Developer Groups have trained thousands of developers.
What’s missing is targeted support in the form of AI-focused training, open datasets, and real-world application opportunities to help developers bring intelligence to the apps Nigerians already trust.
As a mobile app developer with over three years of experience building fintech solutions, I’ve seen both the power and the limits of Nigeria’s app ecosystem.
On one hand, mobile apps have enabled millions of people to send money instantly, pay bills, and even access credit all from their smartphones. On the other hand, too many of these apps are still designed to complete basic transactions rather than to understand or anticipate user needs.
For example, most fintech apps rely on rigid rules for fraud detection or credit approval. This often excludes people who don’t have traditional financial histories, even though alternative data (such as transaction patterns, smartphone usage, or even social signals) could provide more inclusive insights. AI could help bridge this gap by powering personalised credit scoring models that bring financial access to the unbanked and underbanked.
Similarly, in my own work, I’ve noticed how customer support in apps is often a major pain point.
Many users are stuck waiting for responses to simple queries that could be automated. An AI-powered assistant, integrated directly into the app, could provide real-time support in local languages, something especially valuable in a diverse country like Nigeria.
These are not abstract possibilities. They are practical improvements that developers like me could implement if we had better access to AI training, datasets, and cloud infrastructure. The barrier isn’t imagination; it’s ecosystem support.
Suppose Nigeria is to shift from being a mobile-first economy to becoming an AI-driven digital economy. In that case, two things must happen: our apps must evolve beyond transactions, and AI must move out of policy papers into the hands of everyday users. This requires both ecosystem reform and intentional investment in developers.
The first step is to democratise AI skills for those already building the apps Nigerians use every day. Mobile app developers cannot embed intelligence into mobile platforms without access to the right training and exposure.
Government agencies, universities, and private companies need to work together to create AI-focused bootcamps, hackathons, and accelerator programs specifically designed for mobile developers.
By equipping this group with the tools and skills to integrate AI, we increase the chances that ordinary Nigerians will encounter AI not in a conference room, but in the apps they rely on for payments, healthcare, or education.
Equally important is access to open and localised data. AI models are only as good as the data they learn from, and today, Nigerian developers struggle with the lack of high-quality,
context-specific datasets.
Imagine the possibilities if health institutions, financial bodies, and even agricultural agencies released anonymised datasets under secure and ethical guidelines.
Developers could then build AI solutions that reflect the realities of Nigeria’s people, economy, and languages, rather than importing foreign models that don’t always fit.
Nigeria must move from abstract discussions about AI strategy to real-world pilots in critical sectors. Fintech apps could integrate AI to make credit scoring more inclusive. Health apps could deploy AI-driven chatbots to offer instant consultations in local languages. Agricultural platforms could harness predictive AI to guide farmers on yields and weather patterns. These are not futuristic scenarios; they are achievable outcomes if policy and industry leaders deliberately encourage AI integration where it matters most.
Nigeria has the talent and the mobile-first market to lead Africa’s AI revolution. What’s missing is urgency.
If we continue building apps that only transact but never learn, we’ll remain users of other people’s technology.
But if we empower developers with skills, data, and infrastructure, we can turn everyday apps into intelligent tools that solve Nigeria’s biggest challenges. The future of AI here won’t be decided in policy documents; it will be built into the apps millions of Nigerians already hold in their hands.
*The Author: Orafu Charles Tochukwu, is a Software Engineer with over three years of experience building mobile and web solutions for fintech companies.
