• Infrastructure, implementation cost create barriers amidst governance, regulatory risks
• Market to hit $434.4 million by 2026

As adoption of artificial intelligence (AI) spikes in the business sector in Nigeria, especially in agriculture, industry, and the service sectors, stakeholders have warned that without urgent attention to infrastructure, implementation costs, and governance risks, the country may miss out on the full potential of this transformative technology.

These concerns were raised in Abuja at the launch of the 2025 Artificial Intelligence (AI) Report by the Centre for the Study of the Economies of Africa (CSEA), titled AI Adoption and Data Governance in Nigeria: Business Perspectives, Benefits, and Risks in the Digital Era.

The report, which offered insights into how Nigerian businesses are deploying AI, the benefits they are witnessing, and the barriers still in place, brought together representatives from government, academia, industry, and civil society.

Although the stakeholders agreed that AI is growing rapidly in Nigeria, with market projections estimating a value of $434.4 million by 2026, they warned that significant structural and regulatory challenges must be addressed to ensure responsible, equitable, and sustainable adoption.

Representing the Federal Ministry of Communications, Innovation and Digital Economy, Senior System Analyst Emmanuel Udoidoik noted how government interventions are beginning to yield measurable results, particularly in the proliferation of micro and small enterprises applying AI tools.

Udoidoik noted that these gains remain fragile in the face of persistent constraints, especially the high costs of setting up and maintaining AI infrastructure, risks of vandalism to physical facilities, delays in deploying broadband due to right-of-way disputes, and the abandonment of government-donated data centres due to low community awareness and engagement.

He cited initiatives such as the National AI Research Scheme and the establishment of the National Centre for Artificial Intelligence and Robotics, as well as training platforms like the 3 Million Technical Talent (3MTT) programme. These efforts, he said, have helped to seed a growing ecosystem of local AI developers and entrepreneurs, especially in areas like generative AI.

“While the enabling environment is improving, sustainability remains a challenge. The government cannot succeed alone; citizens and local communities must take ownership and actively engage with the infrastructure and programmes available,” he said.

Founder of Robotics and Artificial Intelligence Nigeria (RAIN), Dr Olusola Ayoola, reinforced this view, describing how recent policy and programme shifts have created more structure and cohesion for Nigeria’s AI sector.

He stated that prior to the current administration, innovation largely occurred in isolation, but the introduction of frameworks like the Nigeria Startup Act has improved support for startups and entrepreneurs.

According to Ayoola, one of the most visible changes has been in public awareness. “People now realise that digital and AI skills are critical,” he said, pointing to how the 3MTT programme has triggered interest even among those not selected for formal training. “They’re downloading curricula, seeking mentorship, and turning to local trainers to deepen their skills.”

He also praised the increasing affordability of internet connectivity, with optic fibre gradually replacing unstable satellite connections like Starlink, thereby improving access to cloud-based learning and AI experimentation.

Beyond technical and implementation issues, the report also raises concerns about ethical risks and data governance.

Director of Research at CSEA, Dr Adedeji Adeniran, stressed the growing urgency of managing AI’s unintended consequences, such as data breaches, algorithmic bias, and liability in automated decision-making.

Adeniran said, “Trust is the currency of the digital economy. When data governance is weak, public confidence collapses, and without trust, digital inclusion becomes impossible.”

Adeniran noted that businesses are more concerned about the economic burden of AI adoption than they are about job losses. While job displacement remains a major worry in public discourse, especially among youth, most companies prioritise cost-related issues when assessing AI risks.

This divergence, he argued, shows the need for government to take the lead in regulating AI’s impact on employment, equity, and ethical usage, areas often outside the profit-oriented purview of private firms.

Although Nigeria has introduced laws such as the Data Protection Act and drafted various emerging technology policies, Adeniran pointed out that many of these remain poorly implemented and narrowly focused on national security.

“Without a comprehensive AI governance framework that also promotes innovation and inclusion, we risk stifling the very outcomes we are trying to achieve,” he said.

He further called for the inclusion of non-state actors in regulatory discussions, including startups, large technology companies, and academic institutions. “AI governance is not the same as data governance,” he insisted. “It requires its own architecture and guiding principles, adaptable, inclusive, and forward-looking.”

In his opening address, CSEA Executive Director Dr Chukwuka Onyekwena urged stakeholders to see AI not just as a technology but as a tool for the public good.

“Yes, AI can enhance productivity, optimise business processes, and transform sectors from agriculture to education. But without robust infrastructure, sound policies, ethical safeguards, and a people-centred approach, we risk deepening digital divides and perpetuating inequalities,” he said.

Research Associate, Anthony Okon, also from CSEA, said that to address cost barriers, there is a need for targeted government incentives such as innovation grants and tax relief for AI-related investments.

Firms, on their part, were encouraged to adopt cost-sharing models and pooled procurement to reduce overheads.

Okon further recommended sustained investment in broadband and cloud infrastructure, alongside private sector alignment with evolving ethical and regulatory standards.

He emphasised the need to clarify return on investment through pilot projects and performance benchmarking to convince more businesses to take the AI leap.