For artificial intelligence to work well, it needs massive amounts of organized data to learn from.
Nigeria’s ambitions to become a continental leader in Artificial Intelligence (AI) are hitting a major roadblock, the country’s vast amounts of public data are trapped inside isolated government silos. While the National Information Technology Development Agency (NITDA) and the Ministry of Communications, Innovation and Digital Economy have made bold policy moves including launching a National AI Strategy experts warn that these initiatives will struggle before they truly begin unless the government can successfully open, share, and unify its own databases.
For AI models to be effective, they require massive, clean, and well-organized data to learn from. In Nigeria, however, public information is scattered across dozens of disconnected registries, making it incredibly difficult for local developers and researchers to build intelligent solutions tailored to the country’s unique challenges.
The current digital landscape in Nigeria is deeply fragmented. Eight major government agencies hold some of the country’s most valuable datasets on its citizens, yet these databases remain entirely siloed with little to no interoperability or data sharing.
Even the most aggressive historic pushes such as the 2020 mandate linking SIM cards to National Identification Numbers (NIN) to connect telecom data with verified identities from the National Identity Management Commission (NIMC) have fallen short. Institutional rivalries and concerns over data ownership continue to keep these systems running in parallel rather than as part of a unified digital public infrastructure.
According to Akalugwu Edet, a representative from NITDA, government agencies classify and manage data completely differently, creating massive inconsistencies. “We carried out a survey and realized that different government agencies classify data in different ways,” Edet explained. “How do you harmonize this so that once you have a class of data, you know what type of data you expect and how to manage that data across all agencies?”
Without standardized classifications, an AI system cannot effectively aggregate information from multiple sources. A healthcare AI platform, for instance, cannot seamlessly combine hospital records if different public medical institutions use conflicting formats or standards.
The hurdle is not just technical; it is highly political. Government agencies increasingly recognize that data carries immense value. However, in some cases, that value translates directly into institutional relevance, political influence, or future monetization opportunities.
“A lot of government agencies understand that data has value,” Edet noted during a recent industry panel. “As far as they are concerned, sharing data is giving up that value.”
This creates a severe paradox for Nigeria’s technological sovereignty. AI systems require integrated datasets to generate meaningful economic insights, yet the very institutions that hold these datasets are actively reluctant to share them out of fear of becoming obsolete. The result is a stalled ecosystem where valuable information remains locked behind bureaucratic walls.
As Nigeria looks to build out data exchange frameworks through initiatives like the National Cloud Policy, regulators are also grappling with how to maintain public confidence.
Babatunde Bamigboye, Head of the Legal Enforcement and Regulations Department at the Nigeria Data Protection Commission (NDPC), highlighted that trust is the core currency of AI deployment. Under the Nigeria Data Protection Act, data processing must remain lawful, fair, and transparent even when aggregated at scale.
While collecting millions of data points is technically permissible to train local machine learning models, the purpose must remain strictly legitimate in relation to the citizens. For example, using AI to provide tailored educational tools for underserved communities aligns perfectly with public interest, whereas utilizing the same pooled public data to manipulate consumer behavior or breach privacy boundaries would violate regulatory standards.
If Nigeria wants to turn its National AI Strategy into a real engine of economic transformation, it must move past ministerial enthusiasm and address this fundamental governance gap. Breaking down internal data hoarding, standardizing classifications, and building secure data exchange mechanisms are the only ways local developers will get the data fuel they need to build solutions for the continent.
