Request for Proposals: Evidence for AI in Health Initiative

Deadline: 01-Apr-2026

The Evidence for AI in Health initiative is inviting proposals to evaluate AI-enabled Clinical Decision Support Tools (CDSTs) used in primary and community health care settings. Funding is available through two pathways: up to $1 million for early-stage real-world evaluations and up to $3 million for rigorous impact evaluations at scale. Eligible applicants must be legally recognized entities operating in Sub-Saharan Africa, South Asia, or Southeast Asia with regional leadership and strong evaluation expertise.

The Evidence for AI in Health call supports locally led evaluations of AI-enabled Clinical Decision Support Tools (CDSTs) designed to assist frontline health workers.

The goal is to generate decision-relevant evidence on how AI tools can be responsibly integrated into primary health care systems and scaled effectively.

What Are AI-Enabled Clinical Decision Support Tools (CDSTs)?

AI-enabled CDSTs are digital health tools that use artificial intelligence to assist health workers with:

Diagnosis support
Treatment recommendations
Triage decisions
Referral guidance
Risk assessment

These tools may use:

Text inputs
Voice-based interfaces
Image analysis
Multimodal systems combining multiple inputs

They are typically used in primary health care and community settings where frontline workers require timely clinical guidance.

Core Objectives of the Call

This funding opportunity aims to:

Strengthen integration across levels of care
Improve interoperability with digital health systems
Enhance referral processes and service coordination
Support responsible integration of AI into health systems
Reduce inequities by expanding reach to vulnerable populations
Improve outcomes for high-burden conditions

Proposals should generate actionable evidence for:

Ministries of Health
Health system implementers
Funders and development partners

Funding Pathways

Applicants must choose one of two pathways.

Pathway A – Early Deployment Evaluation

Funding: Up to USD $1,000,000

Target Tools: AI-enabled CDSTs that are early in deployment

Focus Areas:

Usability and user experience
Workflow integration
Adoption and acceptability
Safety assessment
Feasibility in real-world settings

Purpose: To generate implementation evidence that informs future large-scale impact evaluations.

Pathway B – Rigorous Impact Evaluation

Funding: Up to USD $3,000,000

Target Tools: AI-enabled CDSTs ready for scale

Focus Areas:

Measurable health outcomes
System performance indicators
Service delivery efficiency
Quality of care improvements

Purpose: To determine the causal impact of AI-enabled CDSTs at scale and inform national or regional expansion decisions.

Priority Research Themes

Proposals are especially encouraged if they:

Strengthen integration of service delivery across levels of care
Assess interoperability with digital health tools and data systems
Evaluate integration of regulated health commodities where permitted
Explore multimodal AI applications
Address rural, underserved, or marginalized populations
Focus on high-burden diseases with potential for significant improvement

Who Is Eligible?

Eligible applicants must meet all of the following criteria.

Geographic Eligibility

Must operate in Sub-Saharan Africa, South Asia, or Southeast Asia
Principal Investigator (PI) or Project Lead must be based in the region

Legal Status

Must be a legally recognized entity

Eligible organization types include:

Nonprofit organizations
For-profit companies
International organizations
Government agencies
Academic institutions
Multi-sector consortia

Partnership Requirements

Applications must include partners responsible for:

Clinical implementation
Overall project management
Evaluation design and execution

Technical Expertise

Teams must demonstrate:

Expertise in health systems research
Experience conducting impact evaluations
Capacity for rigorous study design and analysis

What Projects Must Demonstrate

Successful proposals must:

Access to an AI-enabled CDST already deployed or ready for deployment
Strong evaluation framework
Clear research questions aligned with decision-making needs
Ethical and responsible AI considerations
Relevance to Ministries of Health and national health strategies

Why This Call Matters

AI tools are increasingly being introduced into primary health care, but many lack rigorous evidence on:

Safety
Effectiveness
Equity impact
System integration

This call aims to close that evidence gap by supporting locally led research that informs:

Responsible AI adoption
Health system strengthening
Future scale-up decisions

It prioritizes evidence generation in regions with high disease burden and constrained health system resources.

How to Apply

Step 1: Confirm Tool Readiness
Ensure your AI-enabled CDST is either early in deployment (Pathway A) or ready for scale (Pathway B).

Step 2: Form a Qualified Consortium
Include partners responsible for:

Clinical implementation
Evaluation
Project management

Step 3: Define Evaluation Framework
Clearly outline:

Study design
Outcome indicators
Data collection methods
Ethical safeguards
Integration strategy

Step 4: Align with Policy Needs
Demonstrate how findings will inform:

Ministry of Health decisions
National digital health strategies
Future scale-up pathways

Step 5: Submit Complete Proposal
Ensure eligibility criteria are met and documentation is complete.

Common Mistakes to Avoid

Proposing tools without real deployment access
Weak evaluation methodology
Lack of regional leadership
Insufficient health systems research expertise
Vague policy relevance
Failure to address interoperability or equity

Strong proposals clearly link evaluation findings to real-world decision-making.

H2: Key Definitions

Clinical Decision Support Tool (CDST)
A digital system that provides clinicians or frontline health workers with evidence-based guidance during patient care.
Interoperability
The ability of digital systems to exchange and use data across platforms and institutions.
Impact Evaluation
A rigorous research design that measures causal effects of an intervention on predefined outcomes.
Primary Health Care
First-level contact care provided in community or local health facilities.

H2: Frequently Asked Questions (FAQ)

How much funding is available?
Pathway A offers up to $1,000,000. Pathway B offers up to $3,000,000.
Who can apply?
Legally recognized entities operating in Sub-Saharan Africa, South Asia, or Southeast Asia with regional leadership.
Can international organizations apply?
Yes, if they meet regional and legal eligibility requirements and include appropriate local leadership.
Must the AI tool already exist?
Yes. Applicants must have access to a CDST that is deployed or ready for deployment.
What is the difference between Pathway A and Pathway B?
Pathway A focuses on implementation and usability. Pathway B focuses on rigorous measurement of impact.
Is partnership mandatory?
Yes. Applications must include partners for clinical implementation, project management, and evaluation.
What types of conditions are prioritized?
High-burden health conditions where AI-enabled tools can significantly improve outcomes.

Conclusion

The Evidence for AI in Health call provides a major opportunity to generate high-quality, locally led evidence on AI-enabled clinical decision support tools in primary health care systems.

By funding both early-stage implementation research and large-scale impact evaluations, this initiative supports responsible AI integration, improved health outcomes, and evidence-based policy decisions across Sub-Saharan Africa, South Asia, and Southeast Asia.

For more information, visit Abdul Latif Jameel Poverty Action Lab (J-PAL).