The global HIV response stands at a precarious crossroads. With U.S. government funding freezes, shifting donor priorities, and geopolitical uncertainty, hard-won gains in prevention and treatment are under threat. signal that global health leaders are beginning to take this shift seriously.
Amid this turbulence, artificial intelligence (AI) is no longer just on the horizon—it’s here, reshaping global health programming with new urgency and potential. With health systems under strain and human resources stretched thin, AI presents a transformative opportunity to overcome programmatic barriers and fast-track progress toward achieving global targets by 2030.
However, this potential can only be fully realized if AI solutions are designed with community input, prioritize digital equity, and uphold quality and ethical standards, ensuring that innovations serve those who need them most.
10 Ways AI Can Improve HIV Prevention
Artificial intelligence to enhance HIV prevention in age of disruptions shows the HIV field is well positioned to lead the integration of AI into health systems with decades of experience in innovation, community-centered design, and task-shifting. What’s more, the HIV response operates at a scale unmatched in global health—thanks to robust public-private partner- ships, community-led networks, and established platforms.
- AI can play in strengthening and scaling HIV prevention programs, especially amid health workforce shortages, limited funding, and the need for more targeted services.
- AI and digital tools can optimize HIV prevention by enhancing demand creation, predicting adherence risks, and supporting differentiated service delivery models. By analyzing behavioral patterns, identifying adherence challenges, and tailoring interventions to individual needs, AI can enable programs to align more closely with user preferences.
- AI tools can help provide information and remote access to services to people who face stigma, enable more precise HIV vulnerability risk stratification, identify individuals at risk of disengagement from care, and optimize the timing and targeting of prevention services. Evidence from electronic medical record (EMR)-based machine learning models shows effectiveness in clinical decision support across the HIV continuum—from PrEP initiation to retention and viral suppression—while also reducing costs and improving resource allocation.
- AI can automate data collection and analysis, enabling governments and partners to identify gaps, adapt programs in real time, and improve overall efficiency. When collective, scalable solutions are developed and integrated responsibly into donor-supported HIV platforms, AI can support more responsive, differentiated, and equitable service delivery.
- AI can support health workers by handling routine tasks such as initial risk assessments, adherence reminders, and appointment scheduling. This allows staff to focus on more complex aspects of care while maintaining service coverage, especially in areas facing workforce shortages.
- AI also supports HIV self-management. Through chatbots, virtual check-ins, and personalized digital reminders, AI-enabled tools can help individuals manage PrEP adherence, navigate side effects, or find nearby services through geo-location. This not only empowers clients but also reduces the burden on frontline workers, making service delivery more sustainable.
- AI also shows promise in improving risk stratification—a long-standing challenge in HIV prevention.9 Traditional screening tools often fall short in identifying those who would most benefit from PrEP. AI-based models could help address this gap by using more diverse, real-time data, combined with the confidentiality afforded by AI chatbots, to improve targeting.
- AI can contribute to data-informed decision-making through rapid analysis of large-scale datasets, including better forecasting of supply needs, optimizing outreach, and identifying geographic hotspots for intervention. These insights can help programs do more with fewer resources, especially as financial uncertainty grows.
- AI is a potential resilience mechanism– with the right enabling environment, AI can help provide continuity and efficiency during periods of disruption, such as funding disruptions and staff shortages.
- ___ What are other ways AI can improve HIV prevention? Please suggest your ideas in the comments.
A synopsis of Artificial intelligence to enhance HIV prevention in age of disruptions
