The National AIDS Control Organisation (NACO), the apex body steering India’s HIV/AIDS response, has recently announced plans to roll out an AI-based predictive system aimed at identifying high-risk individuals  with a target of alerting 100,000 (1 lakh) people by 2026. The system combines analysis of behavioural patterns, clinical history, and other digital signals to flag individuals who may be at increased risk of HIV even before they show clinical symptoms or test positive.

Once flagged by the AI, these individuals would receive timely outreach: counselling, testing and  where relevant  preventive treatment or precautionary measures. The intent is to catch potential HIV cases early, reduce delays in diagnosis, and interrupt transmission chains by engaging at-risk populations proactively. According to NACO, this marks a significant evolution from traditional reactive surveillance (waiting for patients to come forward) toward anticipatory, data-driven public-health intervention. 

The adoption of an AI-driven early-warning mechanism reflects growing global evidence that predictive analytics can help identify high-risk individuals and optimise resource deployment. For NACO, this could translate into more efficient targeting of prevention efforts, better outreach in underserved communities, reduced stigma (through earlier engagement), and overall stronger control of HIV spread in India. Given that India has achieved considerable success in reducing HIV prevalence over the years, the move may further strengthen the country’s long-term HIV-response strategy. 

However, rolling out such a system also raises challenges: data-privacy concerns, need for robust patient consent mechanisms, ensuring equitable access to testing and care post-alert, and avoiding unintended stigma or discrimination linked with AI-flagged risk. Experts emphasize that AI must complement  not replace  human-led care, counselling and community-engagement efforts.