Why Nigeria’s AI future depends on data integrity — Experts

Academics, tech industry leaders, and policymakers have called for urgent action regarding Nigeria’s data infrastructure, warning that poor data quality is actively undermining national development and threatening the country’s integration into the global artificial intelligence (AI) economy.

The consensus was reached during the latest Professor Oye Ibidapo-Obe Biennial Symposium, held in Lagos.

Gathered under the theme: ‘On Data Spaces for Big Data’, a diverse panel of experts from academia, banking, and the oil and gas sectors met to address the systemic challenges of data collection, storage, and integrity in West Africa’s largest economy.

The third edition of the symposium featured a robust panel discussion, moderated by David Olowookere, founding chair of the Department of Engineering at Texas Southern University.

At the event, panelists defined “big data” as massive, fast-changing, and complex datasets that completely overwhelm conventional processing methods, requiring specialised engineering tools to decode and utilise.

While the sheer volume of data being generated in Nigeria is vast, experts warned that quantity does not equal quality.

Tolu Aofolaju, one of the key panelists, emphasised that government planning, policy formulation, and evidence-based decision-making are entirely dependent on the structural integrity of the data used. When the foundation is flawed, the resulting national policies fail.

READ ALSO: Artificial intelligence and African future

Bankole Ojutalayo, also a panelist, delivered a sharp critique of current data management habits in Nigeria, lamenting a widespread “garbage in, garbage out” approach among data handlers.

According to Ojutalayo, this negligence has directly led to the collapse of numerous high-stakes national projects. He further argued that data integrity is not just a technical issue, but a matter of national sovereignty that requires strategic protection.

Compounding this issue is the problem of “data silos,” Panelist Adetunji Adewole warned against using tools that trap data in isolated compartments.

“Data needs to interact; systems must be able to speak to each other,” Adewole stated, urging organisations to discard outdated software that prevents cross-sector data integration.

A senior lecturer in Systems Engineering at the University of Lagos, Comfort Folorunsho, introduced the concept of preventing “data lakes” from degenerating into unmanageable “data swamps”. To achieve this, she advocated for rigorous data cleansing, a process that aggressively filters out false information and ensures datasets remain structured, reliable, and highly usable for end-users.

The urgency for clean data is amplified by the rapid rise of artificial intelligence. Adewole noted that the progress expected from AI over the next few years hinges entirely on the quality of information used to train these systems.

“If the data is poor, the product we will get will be poor. We must emphasise human and ethical use of data so as not to create problems while trying to solve problems. We have to develop the personnel. It is a very important component in the future of technology,” Adewole warned.

Looking ahead, the panel addressed how generative AI will reshape how students and professionals interact with information. Adewole concluded that AI-driven data integration will only be meaningful if it empowers everyday users to make informed choices.

The symposium concluded with a unanimous recommendation: Nigeria must immediately prioritise workforce development, enhance data quality standards, and promote decentralised access to information to strengthen decision-making across all critical sectors.