Mentorship as a Catalyst for AI-Ready Health Information Management in Nigeria: Building an Ethical and Future-Ready Digital Health Workforce

Abstract

Artificial intelligence (AI) is changing how health data are generated, curated, analysed, exchanged, and used for decisions. In Nigeria, Health Information Management professionals occupy a strategic position between clinical practice, administration, technology, regulation, and public health, yet longstanding digital skills and infrastructure gaps may limit their ability to govern AI-enabled systems safely. This review examines mentorship as a practical mechanism for building an ethical and future-ready Health Information Management workforce. Evidence from Nigeria, sub-Saharan Africa, and other low- and middle-income settings was synthesised alongside digital-health competency frameworks and authoritative governance guidance. The review identifies six connected competency domains: data and AI literacy, data quality and interoperability, privacy and cybersecurity, ethics and bias appraisal, implementation leadership, and continuous evaluation. It proposes a context-sensitive MENTOR-AI framework that combines competency mapping, supervised workplace projects, ethical reflection, peer learning, and measurable service outcomes. Mentorship should complement formal education and institutional investment rather than substitute for them. Nigerian health institutions, professional bodies, universities, and government agencies should embed structured mentorship into digital-health transformation while protecting patients, strengthening local data stewardship, and evaluating effects on workforce capability and health-system performance.