Gates Foundation Grand Challenges 2026 – AI-Enabled Family Planning Solutions in Sub-Saharan Africa (Up to US$500,000)

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Applications are now open for the Gates Foundation Grand Challenges 2026: AI-Enabled Consumer Engagement to Advance Family Planning. This is a funding opportunity supporting innovative AI-powered solutions that improve access to family planning information and services for women and girls across Sub-Saharan Africa.

This RFP seeks to answer a core question for the family planning field: can AI-enabled direct-to-consumer engagement improve contraceptive uptake, continuation, and informed method choice at scale – and, if so, which approach works best?

This challenge is designed to generate practical evidence on what high-quality, AI-assisted family planning engagement looks like in the AI era. They are interested in understanding which AI-enabled tools are most effective to engage users and improve contraception uptake and continuation. More specifically, they are interested in understanding which tools and approaches (e.g., content personalization, rapid content scaling, automated customer journeys, etc.) work best for which types of users to directly engage them and improve uptake and which platforms/tools have demonstrated less success for this objective. They do not expect applicants to arrive with platforms already proven for contraception; we welcome consumer engagement approaches with a demonstrated track record in women’s health or consumer health more broadly, and ask applicants to deploy, test, and assess how well they work for family planning.

The challenge will focus on women and girls of reproductive age in sub-Saharan Africa. Interventions can be delivered through public sector platforms, private sector channels, or hybrid models.

Gates Foundation Grand Challenges Objectives

The objectives of this challenge are to:

Generate evidence on impact and scale. Demonstrate whether and how AI-enabled direct-to-consumer engagement improves contraceptive uptake, method continuation, and/or informed method choice at scale.
Identify the features of effective engagement. Determine which interaction characteristics, content strategies, personalization approaches, prompts, follow-up models, or conversation patterns are associated with stronger user outcomes.
Build a shared evidence base for AI-enabled family planning engagement. Produce labeled conversation examples, interaction taxonomies, quality rubrics, safety, confidentiality, and guardrail protocols, and/or other analytic tools that can help the field evaluate and improve AI-enabled consumer engagement beyond a single program or platform.
Assess cost, feasibility, and added value. Document the cost, operational requirements, feasibility, and comparative value of AI-enabled engagement relative to alternative consumer engagement or demand-generation models, including the conditions under which AI-enabled approaches are likely to add meaningful value.

Proposals should be designed to produce both programmatic results and field-building insights. The strongest applications will combine a compelling intervention model with a rigorous approach to measurement, a clear plan for analyzing interaction quality, and a commitment to generating practical learning that can inform future investments in AI-enabled family planning tools.

Funding Details

They will consider proposals for awards of up to $500,000 USD for each project, with a grant term of up to 12 months.
Application budgets should be commensurate with the scope of work proposed. Indirect costs may be included in the budget, up to a maximum of 15% of the total budget (subject to the Gates Foundation’s indirect cost policy).

Eligibility Criteria

This initiative is open globally to nonprofit organizations, for-profit companies, international organizations, government agencies and academic institutions. Multi stakeholder collaborations are encouraged. Individuals and organizations classified as individuals for U.S. tax purposes are not eligible to receive an award from the foundation as part of this initiative.

They are looking for proposals that:

Applicants should have existing women’s/ consumer health intervention cohorts in Nigeria, Ethiopia, the Democratic Republic of Congo, Tanzania, Senegal, Niger, Kenya, South Africa, Zambia or Côte d’Ivoire.
Applicants should have an existing consumer engagement approach – in family planning, women’s health, or consumer health more broadly – and an established user base or distribution relationship – characterized by engagement (e.g., monthly active users), not size alone – ideally in at least one target geography at the time of application
The AI-enabled engagement approach itself can be new and innovative, but the grant period should be spent on deployment, learning, and evaluation, not on acquiring users or negotiating platform access
Propose a credible evaluation design that measures the quality, safety, and confidentiality of the AI-enabled interaction and downstream user outcomes, including contraceptive uptake, method continuation, or informed method choice
Have a clear theory of what effective engagement looks like and how interaction quality connects to behavior change – and a plan to test it
Operate at sufficient scale to generate meaningful findings within the grant period
Commit to producing outputs that contribute to the shared evidence base – including but not limited to labeled interaction examples, conversation quality rubrics, interaction taxonomies, or safety, confidentiality, and guardrail protocols
Demonstrate that AI-generated content is grounded in vetted, locally relevant family planning information aligned with national MOH or WHO guidelines
Are led by organizations with deep contextual knowledge of the target geography and population
Define their target user and explain how relevant their existing user base is to family planning outcomes – particularly for solutions not originally focused on family planning
Describe their user acquisition model, including key metrics, and their user retention efforts – recognizing that engagement quality and the human touchpoints before and after the digital interaction matter as much to family planning outcomes as user-base size