Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa - Tafadzwa Dzinamarira; Elliot Mbunge; Claire Steiner; Enos Moyo; Adewale Akinjeji; Kaunda Yamba; Loveday Mwila; Claude Mambo Muvunyi (Applied AI Letters)
ABSTRACT The challenge of antimicrobial resistance (AMR) represents one of the most pressing global health crises, particularly, in resource‐constrained settings like Africa. In this paper, we explore artificial intelligence (AI) and machine learning (ML) potential in transforming the potential for antimicrobial stewardship (AMS) to improve precision, efficiency, and effectiveness of antibiotic use. The deployment of AI‐driven solutions presents unprecedented opportunities for optimizing treatment regimens, predicting resistance patterns, and improving clinical workflows. However, successfully integrating these technologies into Africa's health systems faces considerable obstacles, including limited human capacity and expertise, widespread public distrust, insufficient funding, inadequate infrastructure, fragmented data sources, and weak regulatory and policy enforcement. To harness the full potential of AI and ML in AMS, there is a need to first address these foundational barriers. Capacity‐building initiatives are essential to equip healthcare professionals with the skills needed to leverage AI technologies effectively. Public trust must be cultivated through community engagement and transparent communication about the benefits and limitations of AI. Furthermore, technological solutions should be tailored to the unique constraints of resource‐limited settings, with a focus on developing low‐computational, explainable models that can operate with minimal infrastructure. Financial investment is critical to scaling successful pilot projects and integrating them into national health systems. Effective policy development is equally essential to establishing regulatory frameworks that ensure data security, algorithmic fairness, and ethical AI use. This comprehensive approach will not only improve the deployment of AI systems but also address the underlying issues that exacerbate AMR, such as unauthorized antibiotic sales and inadequate enforcement of guidelines. To effectively and sustainably combat AMR, a concerted effort involving governments, health organizations, communities, and technology developers is essential. Through collaborations and sharing a common goal, we can build resilient and effective AMS programs in Africa.