Experts urge Nigeria to adopt AI governance framework that protects patients

By Ojoma Akor

ABUJA, Nigeria – Health experts and digital technology stakeholders say Nigeria needs an AI governance framework. Without clear rules, shared standards and accountability, they warn, the fast spread of artificial intelligence (AI) in healthcare could threaten patient safety, privacy and public trust.

They said the technology could also widen health inequalities if it is used without enough safeguards.

The call was made at the Artificial Intelligence in Health Summit 2026, organized by the Africa Hub for Innovation and Development (AHFID) on October 19–20 in Abuja.

Government officials, researchers, technology innovators and development partners discussed how AI could strengthen health systems. They also looked at how it could speed up universal health coverage in Nigeria and across Africa.

Why Nigeria needs an AI governance framework

Speaking at the summit, Dr Leke Ojewale, Senior Technical Adviser on Digital Health, said AI is already entering healthcare through patients, health workers and new digital health systems. For this reason, Nigeria must decide how the technology should be used.

“The real question is not whether AI will shape healthcare in Nigeria or across Africa. The real question is who will shape AI,” Ojewale said.

He urged stakeholders to build a national framework that sets clear expectations for AI adoption. According to him, it should protect patients and health workers, promote equal access and encourage locally relevant technologies.

He said the framework should set standards for safety, privacy and accountability. It should also make sure AI does not widen gaps between urban and rural communities, or between rich and poor people.

He also stressed the need to build local expertise, data and solutions. In his view, African countries should become producers and innovators in AI, not just consumers of technologies built elsewhere.

Dr Ojewale warned that delay could leave the country reacting to problems after they appear, instead of preventing them. He called for open talks about what was working, what was failing and which assumptions needed to be challenged.

He also listed early uses of AI in health:

• helping frontline health workers spot early signs of illness in children;
• reducing paperwork in overstretched clinics; and
• strengthening disease surveillance so outbreaks can be detected earlier.

However, he cautioned that these benefits would need clear national priorities and effective safeguards. They would also need teamwork among government, clinicians, researchers, technology companies, civil society and development partners.

Patient safety and accountability concerns

Pharmacist Nkiru Ukor, the World Health Organization’s (WHO) National Professional Officer for Health Information, Research and Innovation in Nigeria, said AI is developing faster than many countries can write policies and regulations.

She said moving too slowly could leave countries dependent on technologies and standards built elsewhere. Moving too quickly, on the other hand, could endanger patients and erode public confidence.

Ukor also raised the question of who is responsible when AI-enabled healthcare technology fails and harms a patient.

She recalled talks during the review of Nigeria’s first national telemedicine guideline and its implementation plan. Stakeholders debated who should bear responsibility if an AI-enabled clinical decision harmed a patient.

According to her, some private-sector participants wanted indemnity for service providers and clinicians. Representatives of the Federal Ministry of Health and Social Welfare, however, insisted that someone must take responsibility when technology fails.

Ukor stressed that AI should support healthcare professionals, not replace their clinical judgment.

What an AI governance framework should cover

Ukor said a national AI governance framework should state:

• what evidence is needed before AI technologies are adopted;
• how they should be regulated;
• which health priorities they should address; and
• how investments should be coordinated.

She also stressed the need for shared digital infrastructure and interoperability standards, so that different health information systems can communicate.

Ukor said the Federal Ministry of Health and Social Welfare is working to put the National Digital Health Architecture into operation. It is expected to help connect digital health systems.

Without common standards, she explained, AI systems will keep analyzing fragmented data in isolation. That limits their usefulness to clinicians and patients.

“Countries should not have to rebuild their digital foundations every time a new AI application emerges,” she said. She added that shared infrastructure could reduce duplication, improve affordability and support innovation across different health priorities.

Africa must build its own AI solutions

The summit’s convener, Dr Kunle Kakanfo of AHFID, said Nigeria does not mainly lack technology. Instead, he said, the country lacks a coordinated approach to governance, evidence and financing.

He traced the initiative to earlier work by organizations using AI across different sectors. In November 2025, an AI in public health capacity-building workshop, held with partners including the University of Toronto, brought together 53 organizations, ministries, departments and agencies. They reviewed existing AI applications, policies and gaps.

One key finding, he said, was that stakeholders had no shared governance approach. They also lacked common standards for judging evidence produced by AI systems, and had no coordinated financing routes for deploying solutions.

He also pointed to confusion over the roles of different regulators. Several agencies, he noted, have their own views on how AI should be governed within their mandates.

The summit was designed to bring these issues into a wider national conversation. Its aim was to help stakeholders agree on practical steps for responsible AI adoption in healthcare, including an AI governance framework.

Kakanfo said the effort involved government institutions, international development partners, researchers and technology organizations. This reflects the need for a joined-up approach rather than separate projects.

He added that the countries most likely to benefit from AI will not necessarily have the most advanced technology. They will be those with clear strategies, strong institutions, reliable data and a capable workforce.

He further called for innovation to be guided by evidence, patient safety, equity and sustainability.

A shared responsibility

Ukor described building an AI governance framework as a shared job for government, regulators, academic and research institutions, innovators and the private sector.

She said governments should provide strategic leadership and national ownership. Regulators should set proportionate safeguards, and researchers should produce independent evidence. Technology developers, in turn, should build solutions that are safe, interoperable and responsive to local needs.