Nigeria has launched a new AI equity report, titled Make This Matter, which calls for the urgent development of locally driven technology to ensure the country remains competitive in the global digital economy.
The report serves as a Nigerian-focused synthesis of the global 2026 Goalkeepers Report. It warns that without intentional efforts to build domestic artificial intelligence (AI) capabilities, Nigeria risks a widening technological gap where the benefits of automation and machine learning are concentrated in developed economies.
By advocating for “AI equity,” the document highlights the need for technology that is built by Nigerians, for Nigerians, using data that accurately reflects the country’s diverse linguistic, cultural, and economic landscapes.
Addressing the AI digital divide
The launch of the Make This Matter report signals a shift in how Nigerian policymakers and tech leaders view the rapid integration of AI systems into daily life.
A central theme of the report is the danger of technological dependency. As global tech giants deploy large language models (LLMs) and automated tools, there is a growing concern that these tools may not be optimised for the African context. This includes issues ranging from inaccurate linguistic representation of local dialects to algorithmic biases that do not account for Nigerian socio-economic realities.
The report argues that for AI to drive meaningful productivity, there must be a concerted effort to invest in local infrastructure, such as data centres and high-speed internet, alongside human capital development. This involves training a new generation of engineers and data scientists who can design systems tailored to local sectors, including agriculture, healthcare, and fintech.
For small and medium enterprises (SMEs), the report suggests that locally adapted AI could lower the barriers to entry for digital services. For instance, AI-driven tools that understand local trade patterns or agricultural cycles could provide better credit scoring and weather forecasting than generic global models.
However, the report also notes that the lack of high-quality, localised datasets remains a major hurdle. Currently, much of the data used to train global AI models is sourced from Western contexts, which can lead to errors when applied to Nigerian users. The document urges the Nigerian government and private institutions to prioritise the creation of robust, local datasets to ensure accuracy and reliability.
Industry experts suggest that the report’s recommendations will require significant collaboration between the private sector and the government to create regulatory frameworks that encourage innovation while protecting data sovereignty. The report’s findings are expected to inform upcoming government discussions on national digital infrastructure and data protection laws.
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