INTRODUCTION:
Antimicrobial resistance (AMR) poses a recurrent public health threat in Africa. National action plans (NAPs) on AMR provide frameworks for national responses aligned with the WHO global action plan. Artificial intelligence (AI) offers potential to strengthen AMR surveillance, stewardship and data-driven decision-making, yet its integration into national policy frameworks remains poorly understood. AI-enabled tools can support real-time detection of resistance trends and strengthen antimicrobial use oversight. This review assesses AI integration within AMR NAPs of 10 high-burden African countries and identifies critical gaps for policy development.

METHODS:
A structured qualitative review of AMR NAPs was conducted across 10 high-burden African countries: Central African Republic, Lesotho, Eritrea, Nigeria, Kenya, South Sudan, Burundi, Rwanda, Tanzania and Algeria. Data sources included WHO AMR NAPs library, national ministry of health websites and Africa CDC reports. AI integration was assessed across six domains: surveillance; diagnostics; antimicrobial stewardship; infection prevention and control; risk communication; and governance and ethics.

RESULTS:
AI integration within AMR NAPs was limited and largely indirect across all countries. Central African Republic, South Sudan and Eritrea are in early digital phases with basic electronic reporting platforms such as DHIS2. Nigeria and Kenya demonstrated relatively higher digital readiness through national AMR data platforms and electronic prescribing tools. Across all countries, governance frameworks addressing data ethics and regulatory oversight were largely missing.

CONCLUSIONS:
Artificial intelligence remains underutilized in national action plans on AMR across high-burden African countries. There is an urgent need to institutionalize AI within AMR policy frameworks through sustainable financing, workforce capacity development and governance mechanisms to support ethical and country-owned implementation.