Data protection, security, trust critical to Nigeria’s AI future – stakeholders say

Data protection, security, trust critical to Nigeria’s AI future – stakeholders say

Stakeholders at the AI Summit Nigeria 2026 have identified data protection, cybersecurity, regulatory clarity and trust among government institutions as critical factors that will determine the success of artificial intelligence (AI) adoption in Nigeria.

The stakeholders, drawn from government, the private sector and the security community, made the submission during a panel session titled “Making the Rules Work: Regulatory Clarity for Government AI” held on Tuesday in Abuja.

Speaking during the session, Emmanuel Edet, Acting Director of Regulations and Compliance at the National Information Technology Development Agency (NITDA), said while the agency has not conducted a comprehensive study to determine the level of AI implementation across government institutions, evidence from technology projects submitted for NITDA clearance suggests that AI adoption is already gaining traction across Ministries, Departments and Agencies (MDAs).

“I would not have the correct statistics of implementation of what you would call the AI strategy across government because we’ve not actually carried out a study on that, which is something we are planning to do,” he said.

According to Edet, NITDA has identified three pillars of Nigeria’s National AI Strategy where significant progress is being recorded. These include ecosystem partnerships and research, AI adoption for sector transformation, and governance frameworks for ethical AI deployment.

He noted that through the National Centre for Artificial Intelligence and Robotics (NCAIR), the government has intensified engagement with researchers and industry practitioners to develop locally relevant AI solutions tailored to Nigeria’s economic, social and cultural realities.

“We want these solutions to be contextual to our economy, to our society and to our culture as well,” he said.

Edet added that many government agencies are increasingly deploying technology solutions with embedded AI capabilities, although the level of adoption remains uneven across institutions.

“One of the challenges that we do have there is the lack of uniform deployment, which is something that we need to address as we go along,” he stated.

On AI governance, Edet disclosed that NITDA is working on ethical frameworks to guide the deployment and use of AI, particularly within government institutions.

Beyond AI deployment, he identified data classification, metadata harmonisation and inter-agency trust as major challenges slowing the development of a robust government data exchange ecosystem.

“Our problem is not technical; I would say it is foundational. A lot of government agencies understand that data has value. And as far as they are concerned, sharing data is giving up that value. How do you build that trust to make them understand that at some point, sharing your data brings you more value than storing it in silos?,’ he said

He explained that existing laws and administrative processes were not originally designed for a digital economy.

He further noted that government agencies often classify data differently, making interoperability difficult.

Also speaking, Babatunde Bamigboye of the Nigeria Data Protection Commission (NDPC) stressed that AI adoption must be anchored on the principles contained in the Nigeria Data Protection Act (NDPA).

According to him, the law already provides guardrails that can be adapted to emerging technologies, including AI.

“The obligations or the guardrails, so to speak, are framed at a very high level of abstraction in the sense that they may almost always be adapted to emerging circumstances,” he said.

Bamigboye argued that the legitimacy of data processing should remain central to AI governance, warning against the indiscriminate collection of personal data.

“Collect, if it is a million points you want to collect, the law permits you. But then, is it now legitimate to the data subject? That is where the issue is,” he said.

He emphasized that organizations deploying AI systems must adopt privacy-by-design principles, conduct data protection impact assessments, maintain clear privacy policies, appoint data protection officers and ensure data subjects can exercise their rights.

He also raised concerns about data sovereignty, warning that organizations risk losing control of citizens’ data if they rely on external AI providers without adequate safeguards.

Fatima Adam Imam, representing the Office of the National Security Adviser (ONSA), highlighted the importance of integrating national security considerations into AI systems from the design stage.

“Embedding security early is easier because essentially, as we are using AI, we’re opening ourselves to vulnerabilities that are much harder to fix and much more expensive to fix afterwards,” she said.

According to her, incorporating security requirements early helps identify critical AI systems, strengthens procurement processes and ensures incident response mechanisms are established before deployment.

“Our role is to ensure that the implementation process embeds security within so that AI can be adopted confidently,” she added.

On his part, John Edokpolo, Head of Legal Affairs, Africa at Microsoft, urged Nigeria to move beyond policy discussions and focus on accelerating AI adoption across government.

Edokpolo noted that countries leading in AI diffusion globally are not necessarily the ones developing the most advanced AI models. Instead, they are countries that have established strong digital foundations, invested in connectivity and digitisation, and created central institutions to drive adoption.

He cited examples from the United Arab Emirates and Singapore, where government-led digital identity systems and coordinated digital transformation programmes have accelerated AI uptake across public services.

“At the risk of appropriating the logo of a very popular sports apparel company, just do it. You have to digitize governance because that’s what brings the data that we’re trying to have in this national data exchange. That’s what’s going to produce quality data,” he said.

According to him, successful AI adoption requires broad access to connectivity, electricity, computing infrastructure and digital skills, supported by a coordinated government strategy.

Edokpolo also advocated responsible AI frameworks built around principles such as safety, security, accountability, fairness and accessibility.

“Responsible AI is not a destination; it’s a journey. It’s a system of processes and controls you put in place to define what you do as you go along the value chain,” he said