Gates Foundation Grand Challenges 2026: Up to US$500,000 for AI-Enabled Family Planning Solutions in Sub-Saharan Africa
The Gates Foundation has opened applications for the 2026 Grand Challenges funding opportunity, “AI-Enabled Consumer Engagement to Advance Family Planning.”
The initiative will support organisations that can deploy, test and evaluate artificial intelligence-enabled, direct-to-consumer engagement tools designed to improve contraceptive uptake, method continuation and informed contraceptive choice among women and girls of reproductive age in sub-Saharan Africa.
Selected projects may receive up to US$500,000 for an implementation period of up to 12 months. The opportunity is open to eligible organisations worldwide, but proposed activities must be implemented in sub-Saharan Africa and applicants must already have an operational user base, intervention cohort or distribution relationship in a target geography.
The application deadline is 25 August 2026 at 11:30 a.m. United States Pacific Time.
Applicants should review the official Grand Challenges opportunity page, request for proposals, rules, application instructions, budget template and frequently asked questions before submitting.
Overview of the Opportunity
The initiative seeks practical, scalable and evidence-generating solutions that use artificial intelligence to improve family planning engagement.
Successful applicants will not simply be expected to build an AI tool. They must demonstrate how an AI-enabled consumer engagement approach can be deployed through an existing platform, tested with real users and evaluated against meaningful family planning outcomes.
Key information includes:
- Opportunity title: AI-Enabled Consumer Engagement to Advance Family Planning
- Initiative: Grand Challenges
- Organiser: Gates Foundation
- Challenge topic: Artificial intelligence
- Application opening date: 21 July 2026
- Application deadline: 25 August 2026 at 11:30 a.m. U.S. Pacific Time
- Maximum funding: US$500,000 per project
- Maximum project period: 12 months
- Maximum indirect costs: 15% of the total budget, subject to the Foundation’s indirect cost policy
- Geographic focus: Sub-Saharan Africa
- Primary target group: Women and girls of reproductive age
- Proposal-review completion: Expected in October 2026
- Estimated project commencement: Late January or early February 2027
- Application method: Online submission through the Gates Foundation portal
The Foundation has not stated how many projects will be selected.
Why This Initiative Has Been Launched
Despite substantial investment in family planning programmes across sub-Saharan Africa, many women and girls continue to face unmet contraceptive needs.
Access to family planning is influenced by several barriers, including:
- Lack of accurate information
- Limited access to personalised counselling
- Concerns about side effects
- Misinformation and social stigma
- Limited access to trained providers
- Language and communication barriers
- Weak continuity between awareness and service uptake
- Lack of confidential spaces for asking sensitive questions
- Limited follow-up after selecting or beginning a contraceptive method
Clinic-based counselling remains important, but it cannot independently provide continuous, personalised engagement to every potential user at the scale and cost required.
Digital health platforms have increased the reach of health information. However, many existing systems depend on one-way messages, fixed scripts or rule-based responses. Such systems may deliver standard information but cannot always respond effectively to an individual user’s concerns, follow-up questions and changing circumstances.
How Artificial Intelligence Could Improve Family Planning Engagement
Recent advances in large language models and conversational AI have created new possibilities for direct engagement with consumers.
AI-enabled tools may be able to:
- Conduct multi-stage conversations rather than providing a single response.
- Communicate in local languages.
- Respond to individual questions and concerns.
- Personalise information according to the user’s situation.
- Address misconceptions through interactive dialogue.
- Provide consistent information at a low marginal cost.
- Support follow-up communication.
- Guide users towards appropriate family planning services.
- Operate through public-sector, private-sector or hybrid channels.
- Integrate with established telecom, health-system, community or commercial platforms.
Organisations across sub-Saharan Africa are beginning to use these tools for women’s health and broader consumer-health needs. However, the field still lacks sufficient evidence showing which AI-enabled engagement models produce meaningful family planning outcomes.
The Evidence Gap the Challenge Seeks to Address
The Gates Foundation is seeking evidence that goes beyond the number of messages sent, users registered or sessions completed.
The initiative seeks to understand:
- Which AI-enabled approaches are most effective.
- Which tools work best for different categories of users.
- Whether personalisation improves outcomes.
- Which prompts or conversational patterns produce stronger engagement.
- Whether automated follow-up affects method uptake or continuation.
- How interaction quality should be measured.
- How AI-generated conversations influence user behaviour.
- Which approaches do not work or produce weak results.
- Whether the cost and operational requirements justify the added value.
- How safety, confidentiality and content accuracy can be protected.
- Whether successful models can be responsibly replicated and scaled.
Without this evidence, investments in AI-enabled family planning platforms cannot be properly compared, improved or expanded.
The Central Question
The initiative seeks to answer whether AI-enabled, direct-to-consumer engagement can improve:
- Contraceptive uptake
- Continued use of a selected contraceptive method
- Informed method choice
- Quality of family planning engagement
- Access to accurate and personalised information
- Movement from awareness to action
Applicants must also help explain which approaches work, for whom they work, why they work and under what operating conditions they are most valuable.
Types of Solutions That May Be Considered
The Foundation does not require applicants to have an AI platform that has already demonstrated family planning results.
Organisations may apply with an existing consumer engagement approach that has a proven record in:
- Family planning
- Women’s health
- Reproductive health
- Consumer health
- Digital health
- Community health
- Other closely related health areas
The proposed AI component may be new. However, the applicant must already have an established user base, intervention cohort or distribution relationship that makes deployment and evaluation possible within the 12-month period.
Projects may be delivered through:
- Government health systems
- Public-sector digital platforms
- Private-sector health platforms
- Telecom networks
- Community networks
- Commercial consumer channels
- Nongovernmental organisation platforms
- Hybrid public-private delivery models
The programme is not intended to finance a platform that still needs to begin building its user base or negotiating access to a distribution channel.
Primary Objectives
The initiative has four central objectives.
1. Generate Evidence on Impact and Scale
Projects should demonstrate whether and how AI-enabled, direct-to-consumer engagement affects:
- Contraceptive uptake
- Method continuation
- Informed method choice
- User understanding
- Behavioural outcomes
- Engagement at scale
Applicants must present a credible evaluation design capable of connecting AI-enabled interactions with downstream family planning outcomes.
2. Identify Features of Effective Engagement
Projects should determine which elements of an AI-enabled interaction are associated with stronger results.
These elements may include:
- Content personalisation
- Conversation design
- Prompt structures
- Follow-up methods
- Automated customer journeys
- Rapid content adaptation
- Local-language communication
- Interaction frequency
- Timing of follow-up messages
- Referral pathways
- Human support before or after digital engagement
Applicants should develop and test a clear theory of what effective consumer engagement means in their proposed context.
3. Build a Shared Evidence Base
Funded work should generate learning that benefits the wider family planning and digital-health field rather than only improving the applicant’s own platform.
Possible shared outputs include:
- Labelled examples of AI-user interactions
- Conversation taxonomies
- Interaction-quality rubrics
- Safety protocols
- Confidentiality frameworks
- AI guardrail protocols
- Content-quality assessment tools
- Evaluation frameworks
- Standardised engagement measures
- Practical guidance for future implementers
Applicants should explain how these outputs could help other organisations evaluate and improve AI-enabled family planning engagement.
4. Assess Cost, Feasibility and Added Value
Projects must examine the cost and operational requirements of using AI-enabled engagement.
Applicants should assess:
- Implementation costs
- Technical requirements
- Staffing requirements
- Platform costs
- Monitoring and evaluation costs
- Feasibility within existing systems
- Cost compared with alternative engagement models
- Conditions in which AI adds meaningful value
- Conditions in which non-AI approaches may be more suitable
Budgets should be proportionate to the proposed deployment and evaluation activities.
Expected Characteristics of Strong Proposals
Competitive applications should combine a credible operational intervention with a rigorous evaluation plan.
Strong proposals are expected to:
- Produce real programme results.
- Generate learning for the broader field.
- Use an existing platform or distribution relationship.
- Operate at sufficient scale to produce meaningful findings.
- Measure interaction quality rather than only platform activity.
- Track downstream family planning outcomes.
- Include appropriate safety and confidentiality protections.
- Ground AI-generated information in reliable family planning guidance.
- Demonstrate deep knowledge of the target geography and population.
- Present a realistic 12-month implementation plan.
- Use an appropriate and clearly justified budget.
- Explain how learning will be shared beyond the applicant’s organisation.
Eligible Organisations
The opportunity is open globally to:
- Nonprofit organisations
- For-profit companies
- International organisations
- Government agencies
- Academic institutions
Collaborations involving multiple stakeholders are encouraged.
Potential partnerships could involve:
- Technology companies and health organisations
- Universities and government agencies
- Telecom operators and family planning programmes
- Nongovernmental organisations and AI developers
- Public health institutions and community organisations
- Research institutions and operational delivery partners
Individuals are not eligible to receive funding directly. Organisations classified as individuals for United States tax purposes are also ineligible.
Awards will be made to the organisation where the responsible investigator or project lead holds their primary appointment.
Geographic Requirements
Although eligible organisations may be headquartered anywhere in the world, the proposed intervention must operate in sub-Saharan Africa.
Applicants should already have women’s-health or consumer-health intervention cohorts in one or more of the following countries:
- Nigeria
- Ethiopia
- Democratic Republic of the Congo
- Tanzania
- Senegal
- Niger
- Kenya
- South Africa
- Zambia
- Côte d’Ivoire
The Foundation has expressed a preference for solutions targeting:
- Nigeria
- Ethiopia
- Democratic Republic of the Congo
- Tanzania
- Senegal
- Niger
- Côte d’Ivoire
Projects in other eligible sub-Saharan African settings may be considered, but activities outside sub-Saharan Africa will not be funded under this call.
Existing User Base and Distribution Requirements
Applicants must already have an operational consumer-engagement approach and an established user base or distribution relationship.
The existing approach may relate to family planning, women’s health or consumer health more broadly.
The Foundation will examine the quality of engagement, not merely the headline size of the platform.
Applicants should provide evidence such as:
- Monthly active users
- User-retention rates
- Repeat engagement
- Completion of health journeys
- Existing delivery partnerships
- Reach within the proposed geography
- Level of interaction with women and girls
- Established referral or service pathways
An applicant with a large registered user base but weak active engagement may be less competitive than an organisation with a smaller but consistently engaged population.
Requirements for AI-Generated Health Content
AI-generated content must be based on vetted and locally relevant family planning information.
Content should align with:
- National Ministry of Health guidance
- World Health Organization guidance
- Relevant national family planning protocols
- Local clinical and ethical requirements
- Appropriate language and cultural context
Applicants should explain how they will prevent the AI system from providing inaccurate, unsafe or inappropriate information.
The proposed safeguards should address:
- Medical misinformation
- Hallucinated content
- Confidentiality
- Sensitive personal information
- Harmful recommendations
- Bias
- Escalation to human support
- Referral to qualified services
- Appropriate consent
- Protection of vulnerable users
Measurement and Evaluation Requirements
Applicants must propose an evaluation design that measures both the interaction and the outcomes occurring after it.
Relevant measures may include:
- Quality of AI-user conversations
- Accuracy and relevance of responses
- Safety and confidentiality
- User trust
- User comprehension
- Personalisation quality
- Use of referral pathways
- Contraceptive uptake
- Method continuation
- Informed method choice
- User retention
- Comparative cost
- Operational feasibility
Applications should present a clear pathway connecting interaction quality with behavioural or service-delivery outcomes.
Projects should investigate not only whether behaviour changed, but also how and why the change occurred.
Importance of Human Touchpoints
The Foundation recognises that digital engagement does not operate in isolation.
Human contact before and after an AI interaction may be important to family planning outcomes. Applicants should therefore describe relevant human touchpoints, such as:
- Community-health workers
- Family planning counsellors
- Call-centre agents
- Clinic staff
- Peer educators
- Referral coordinators
- Pharmacists
- Healthcare providers
Applications should explain how digital and human engagement will work together.
Activities That Will Not Be Funded
The Foundation will not support proposals that:
- Use engagement metrics alone as the principal evidence of effectiveness.
- Focus only on messages sent, sessions completed or users registered.
- Lack an existing user base or distribution relationship in a target geography.
- Propose activities outside sub-Saharan Africa.
- Are primarily research projects without real-world operational deployment at scale.
- Spend the funding period primarily acquiring users.
- Depend on negotiating new platform access after the project begins.
- Focus mainly on building an untested tool without deployment and evaluation.
- Offer only incremental improvements.
- Duplicate work already funded by the Foundation or another Grand Challenges initiative.
- Lack sufficient safety, confidentiality or content-quality safeguards.
Funding Level and Project Duration
The Foundation will consider awards of up to US$500,000 for each project.
The project term may be up to 12 months.
Budgets should be proportionate to:
- Proposed activities
- Number of users
- Target geography
- Evaluation design
- Technology requirements
- Operational scope
- Expected outputs
Indirect costs may be included up to a maximum of 15% of the total budget, subject to the Gates Foundation’s indirect cost policy.
The maximum available amount is not an automatic entitlement. Applicants should request only the funding reasonably required to deliver the proposed work.
Required Application Components
The application consists of three principal elements:
- Applicant profile and organisational information completed through the online portal.
- A proposal uploaded in Microsoft Word or Adobe PDF format.
- A budget table and accompanying budget narrative.
Applicants should follow the official application instructions.
Proposal Length and Formatting
The proposal must not exceed two pages.
Figures, diagrams and references are included in the two-page limit.
The proposal must use:
- Font size of at least 11 points
- Aptos, Arial or Times New Roman
- Single-line spacing
- Standard character spacing
- Margins of at least 0.5 inches
- Microsoft Word or Adobe PDF format
- Maximum file size of 3MB
Applicants should not include a separate cover page. The application system will automatically generate one using the registration information.
Applications that do not follow these restrictions may be blocked from submission or review.
Recommended Proposal Structure
The Foundation recommends dividing the two-page proposal into three sections.
1. Introductory Information
Suggested length: Half a page.
Applicants should provide:
- A brief description of the problem being addressed.
- One or two bold sentences explaining the essence of the proposed solution.
2. Proposal Information
Suggested length: One page.
Applicants should provide:
- A clear hypothesis.
- A concise description of the proposed work.
- An explanation of how the activities will produce the intended outcomes.
- The proposed evaluation approach.
- The relationship between AI engagement and family planning outcomes.
3. Path to Impact
Suggested length: Half a page.
Applicants should explain:
- What will happen if the proposed work is successful.
- How the intervention could generate impact.
- How the model could be expanded or replicated.
- How findings could influence the wider field.
Budget Table and Narrative
Applicants must submit a budget table and narrative of no more than one page.
The budget may include:
- Personnel
- Subcontracts
- Subgrants
- Capital assets and equipment
- Travel
- Supplies
- Other expenses
- Indirect costs
A one-paragraph narrative should explain the major cost drivers and show how the requested resources relate to the planned activities and outcomes.
Applicant Webinar
A dedicated webinar is scheduled for:
- Date: 4 August 2026
- Time: 7:00–8:00 a.m. U.S. Pacific Daylight Time
- Format: Online
The webinar will provide an overview of the request for proposals and allow potential applicants to ask questions.
Interested organisations may register for the webinar.
A recording is expected to be added to the official challenge page after the event.
Application Review Process
Applications will proceed through four main stages.
Stage One: Initial Screening
Applications will be assessed to determine whether they address the challenge’s central requirements.
Proposals may be removed if they:
- Are unrelated to the challenge.
- Address specifically excluded areas.
- Offer only incremental improvements.
- Duplicate existing Foundation or Grand Challenges investments.
- Are considered unsuitable for the initiative.
Applicants removed during screening may receive a decline notification without detailed feedback.
Stage Two: Technical Review
Technical leads from the Foundation, and potentially other funding partners, will chair or co-chair the review.
Applications may be assessed by internal and external reviewers with expertise in the topic or complementary areas.
Applicants should write clearly for a multidisciplinary audience because not every reviewer will necessarily be a specialist in the applicant’s exact technical field.
Stage Three: Validation and Final Selection
The Executive Committee will validate the review and select proposals for possible funding.
The committee may recommend funding subject to changes. These modifications may be negotiated during the award process.
Selected organisations may be invited to submit a more detailed proposal and will receive further instructions.
Stage Four: Due Diligence and Negotiation
The final stage will include:
- Due-diligence review
- Discussions with investigators
- Review of organisational and tax status
- Negotiation of project modifications
- Agreement on the budget
- Acceptance of applicable terms and conditions
Main Review Criteria
Applications will be reviewed against five principal areas.
Existing Reach and Family Planning Relevance
Reviewers will consider:
- Strength of the existing user base
- User-engagement level
- Monthly active users or equivalent evidence
- Existing distribution relationships
- Relevance to family planning outcomes
- User-acquisition and retention models
- Human support surrounding the digital interaction
Evaluation and Measurement Rigor
Reviewers will assess:
- The pathway from AI interaction to family planning outcomes
- Measurement of interaction quality
- Measurement of downstream outcomes
- The clarity and testability of the theory of effective engagement
- Whether the approach goes beyond basic engagement metrics
Contribution to Shared Evidence
Reviewers will examine whether applicants will produce outputs useful to the broader field, such as:
- Labelled interaction examples
- Quality rubrics
- Taxonomies
- Safety protocols
- Confidentiality protocols
- AI guardrails
- Evaluation tools
Safety, Confidentiality and Content Grounding
Reviewers will assess:
- Alignment with national Ministry of Health or WHO guidance
- Accuracy of AI-generated information
- Confidentiality measures
- Safeguarding processes
- Appropriate AI guardrails
- Management of sensitive contraceptive information
Organisational Fit and Feasibility
Reviewers will consider:
- Knowledge of the target geography
- Understanding of the target population
- Ability to operate at scale
- Feasibility within 12 months
- Appropriateness of the budget
- Realism of the timeline
- Focus on deployment and evaluation
Intellectual Property and Confidentiality
Applicants should assume that information submitted to the Foundation will not remain confidential.
The Foundation may share application information with:
- External reviewers
- Consultants
- Contingent workers
- Key partners
- Co-funders
Applicants should not include proprietary or confidential information in proposals, budgets or supporting materials.
The Foundation is also required to publish information about awarded funding and may describe selected projects through its websites, press releases or promotional materials.
Funded organisations generally retain ownership of intellectual property created through their projects. However, project outputs must be made widely available to the intended beneficiaries under the Foundation’s global-access requirements. These conditions are explained further in the official FAQs.
Additional Application Information
Applicants should note that:
- Organisational tax-status information must be provided during registration.
- The Foundation may request additional tax documentation.
- Applications may be edited after submission until the deadline.
- A confirmation email will be issued after successful submission.
- The identities of potential reviewers will not be disclosed.
- Applicants cannot request the exclusion of a particular reviewer.
- Reviewers must disclose conflicts of interest.
- Unsuccessful applicants may not receive individual feedback.
- The applicant organisation must accept the applicable terms and conditions before an award is activated.
Key Dates
- Application period opened: 21 July 2026
- Applicant webinar: 4 August 2026, 7:00–8:00 a.m. U.S. Pacific Time
- Application deadline: 25 August 2026, 11:30 a.m. U.S. Pacific Time
- Proposal review expected to conclude: October 2026
- Estimated project start: Late January or early February 2027
Any changes to these dates will be published on the official Grand Challenges website.
How to Apply
Applicants should complete the following steps:
- Review the official request for proposals.
- Read the Rules and Guidelines.
- Review the Application Instructions and FAQs.
- Confirm organisational eligibility and tax status.
- Confirm the existence of a relevant user base or distribution relationship.
- Develop a compliant two-page proposal.
- Prepare a one-page budget table and narrative.
- Create or access an account on the application portal.
- Complete the applicant profile.
- Upload the proposal and budget documents.
- Review the submission carefully.
- Submit before 25 August 2026 at 11:30 a.m. U.S. Pacific Time.
Applications may be started and submitted through the official Gates Foundation application portal.
Questions concerning eligibility, selection criteria or application instructions may be sent to:
grandchallenges@gatesfoundation.org
Conclusion
The Gates Foundation Grand Challenges 2026 opportunity for AI-enabled consumer engagement in family planning represents a significant funding opportunity for organisations already operating women’s-health, reproductive-health or consumer-health platforms in sub-Saharan Africa.
With awards of up to US$500,000 for projects lasting up to 12 months, the initiative is designed to move beyond theoretical AI research. It prioritises real-world deployment, measurable family planning outcomes, operational feasibility, responsible AI use and practical learning that can benefit the wider field.
Competitive applicants will need more than an innovative chatbot or a large list of registered users. They must demonstrate an engaged user base, an established distribution pathway, strong local knowledge, credible evaluation methods, adequate safety protections and a clear connection between AI-enabled interaction and contraceptive outcomes.
Eligible organisations should carefully review all official materials and submit a concise, evidence-driven and technically compliant application before 25 August 2026 at 11:30 a.m. U.S. Pacific Time.
For more global opportunities, click HERE.
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