Nigerian small and medium enterprises (SMEs) are increasingly aware of artificial intelligence (AI), yet adoption remains minimal across key sectors.
This was revealed in a new report on ‘Readiness of Nigerian SMEs’ released by eTranzact International PLC last week, in partnership with the Enterprise Development Centre (EDC) of Pan-Atlantic University.
The report, which launched in Lagos, called for urgent policy interventions, including AI-friendly regulations, tax incentives, and data privacy frameworks to accelerate integration.
It also cited the need for the development of indigenous, culturally and linguistically relevant AI solutions to make the technology more accessible to grassroots businesses.
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“The research is intended to give entrepreneurs, policymakers and financiers a fact-based assessment of where SMEs stand today and a roadmap to compete locally and globally,” Niyi Toluwalope, CEO of eTranzact, said.
Olawale Anifowose, director of Programmes and Partnerships at EDC, noted that adoption appears higher in ICT and creative sectors and lower in agriculture and fashion, which points to the need for sector-specific interventions
The report was based on a nationwide survey covering 5,290 SME respondents and 212 focus group participants in Enugu, Kano, Lagos, Abuja, and Port Harcourt.
According to the survey, AI uptake is strongest in ICT and creative industries but lags in agriculture, fashion, and traditional manufacturing.
Nigeria’s 39 million SMEs, which account for a significant share of GDP and employment, risk missing out on the productivity gains AI offers unless awareness translates into practical adoption, the report warns.
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The aim of this study is to benchmark how small and medium-sized enterprises are adopting artificial intelligence and what it will take to scale usage across the economy.
The study was conducted over several months across key hubs, which include Lagos, Abuja, Port Harcourt, Kano and Enugu by capturing both enthusiasm among business owners and persistent gaps in awareness, access to affordable tools and tailored solutions.
This is with the goal to turn findings into practical guidance for investment and capacity building.
Early recommendations highlighted include promoting indigenous, culturally and linguistically relevant AI tools; developing AI-friendly policies such as targeted tax incentives and simplified regulations; strengthening data-privacy safeguards; and expanding private-sector training pipelines to build skills for adoption.
