Program Officer, AI Access Initiative (EAII Advisors)
Evidence Action
| Company | Evidence Action |
| Category | Data & Analytics |
| Location | Hyderabad |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 15 Jul 2026 |
| Last verified | 7 Aug 2026 |
| Source | Employer ATS (workable) |
Description
This position is with EAII Advisors, Evidence Action’s technical partner in India. About EAII EAII Advisors, Evidence Action’s technical partner in India, supports state governments in delivering evidence-based public health programs, including safe drinking water initiatives and school and Anganwadi-based National Deworming Day and iron and folic acid supplementation. Operating across 10 states, EAII Advisors provides technical assistance to ministries of health, education, water, and women and child development, reducing health burdens in impoverished communities and improving the long-term wellbeing of children and families. For more information, read about our work here: About Evidence Action and EAII About the AI Access Initiative (Incubated at Evidence Action) The AI Access Initiative is a new program being incubated at Evidence Action to scale AI-enabled “big bets” that can improve the lives of tens or hundreds of millions of people living in poverty across low- and middle-income countries. Operating at the intersection of governments, AI labs, researchers, and funders, the Initiative focuses on translating rapid advances in AI into practical, scalable public systems. Initial work focuses on two priority sectors: Agriculture: Scaling AI-enabled weather forecasting systems to improve smallholder farmer decision-making, resilience, and incomes. Health: Transforming primary healthcare quality and access through AI-enabled clinical decision support systems (CDSS) integrated into public platforms, as well as direct-to-consumer AI triage tools to reduce delays in care-seeking. The AI Access Initiative is led by Kanika Bahl, CEO of Evidence Action and founding member of Anthropic’s Long-Term Benefit Trust, with advisors including Nobel Laureate Michael Kremer, Dario Amodei (CEO, Anthropic), and Kent Walker (President, Global Affairs, Alphabet). This work builds on Evidence Action’s track record reaching 530M+ people with cost-effective, evidence-based programs across 9 countries in Africa and Asia, with a focus on last-mile delivery. About the Weather Forecasting Program The AI Access Initiative is launching a new, entrepreneurial initiative to design, test, and scale AI-enabled weather forecasting systems for smallholder farmers. The program will focus on translating recent advances in artificial intelligence into high-impact public systems that deliver timely, localized, and actionable weather information to farmers at scale. More than 500 million smallholder households worldwide depend on agriculture for their livelihoods, yet many lack access to accurate and usable forecasts. Advances in AI offer a step-change opportunity to deliver faster, more accurate forecasts that are cheaper to run, easier to localize, and better suited to farmer decision-making. With targeted investment, AI-enabled forecasting systems could materially improve the livelihoods of hundreds of millions of farmers. To advance this program in India, the Initiative, through Evidence Action’s technical partner EAII Advisors, aims to work with state governments and other partners to explore new models for deploying AI-enabled forecasts and farmer outreach systems. Initial efforts are expected to focus on a state-level implementation in India, with Telangana identified as a potential early partner, subject to finalization. The program aims to: Deploy more accurate, timely, and localized weather forecasts relevant to smallholder farmer decisions Translate technical forecasts into clear, actionable farmer-facing guidance Deliver forecasts at scale through government systems and digital channels Generate operational and impact evidence to inform future state- and national-scale adoption This work is intended to serve as a proof point for scalable, government-led adoption of AI-enabled weather forecasting, with learnings informing expansion to additional states and countries over time. The Rol