Join us at Deep Learning Indaba 2026 for a working session with RICH, the AI4D Research and Innovation for Climate Hub including live climate AI demos, candid dialogue on responsible scaling, and real partnership opportunities.

Across Africa, AI innovations are being built to address climate variability e.g. improving seasonal forecasts, predicting droughts, enabling early warning, and strengthening food security, green energy. However,most of them never reach the communities they were designed to serve. This is not because the science is weak but because the pathways to scale are not well understood, underfunded, and largely uncharted. This session is where we start defining an action plan for scale.

About the session

RICH is a continent-wide initiative co-led by the Local Development Research Institute (LDRI), AfriClimate AI, and Landscape Alliance. Its mission is to bridge the gap between promising African climate AI research and real-world, community-scale deployment, with a particular focus on the public and institutional pathways to scale that most climate innovations must take.
This three-hour session is RICH’s first convening at Deep Learning Indaba. It brings together live demonstrations of African climate AI innovations already in deployment, candid dialogue on what responsible scaling demands, and structured time to forge the data, research, and funding partnerships the field needs.

Your expertise and experience in the room will shape the Hub’s work.

Part 1: Live innovation demonstrations

The session opens with live demonstrations of African climate AI innovations already reaching farmers and communities. The first confirmed demo is ImvulaNet, AfriClimate AI’s AI-driven hyperlocal seasonal forecasting system for smallholder farmers in South Africa’s Limpopo and Free State provinces. Demonstrations are designed to surface questions, not just answers.

Part 2: Roundtable Dialogue

A rotating dialogue with researchers, innovators, funders and policy actors. The central question: whose definition of “ready to scale” are we using, and who is harmed when we get it wrong? This conversation will surface real tensions around data ownership, community consent, the environmental cost of AI, and the limits of responsible AI frameworks developed outside African contexts.

Part 3: Working groups

Three parallel groups will be formed to each address a live, unresolved challenge the Hub is facing in its first year. Your group’s output feeds directly into the Hub’s published innovation scaling framework, with contributions attributed.
The working group topics will be shared with the full program.

Part 4: Partnership sprint

A structured matchmaking session across three stations:

• Funding and Investment
• Climate Data and Infrastructure, and
• Research and Technical Mentorship.

Participants will bring a pre-prepared offer-and-ask card with each station host documenting concrete next steps before the session ends.

Who should attend

For Researchers, innovators, and partners working at the intersection of AI, climate, and development
You will get the most from this session if you are:

• A researcher or practitioner working at the intersection of AI, climate, and development in African or majority-world contexts
• Someone working on AI governance, data justice, or community-centered technology design
• Engaged with the tension that scaling AI itself contributes to the climate crisis through its energy and resource demands
• A funder, investor, or data holder actively looking for credible African-led initiatives to partner with or resource

 Reserve your spot