AI4D African Scholars Programme

The programme places particular value on responsible AI approaches that consider inclusion, ethics, human rights and equitable access to technology.

Eligibility

For the PhD category, applicants must generally:

• Be an African researcher
• Be enrolled in a PhD programme at a university located in Africa
• Have completed a master's degree
• Have an approved and successfully defended PhD research proposal
• Be undertaking research that incorporates AI and/or Machine Learning
• Be working on research that is relevant to responsible AI and development
• Meet the programme's institutional and application requirements

Applicants studying for a PhD outside Africa are not eligible for the PhD scholarship, even if they are African nationals.

The Early Career Academic category has separate requirements and is intended for academics who have obtained their PhD within the programme's specified five-year period.

Funding and Benefits

The scholarship provides research and academic support rather than a full personal maintenance package.

Eligible support can include:

• Tuition support
• Research-related expenses
• Research-related travel
• Conference participation
• Journal publication and dissemination costs
• Mentorship
• Capacity-building activities
• Support for translating research findings into policy-relevant outputs

For PhD scholars, tuition support is capped at US$4,000 over the two-year scholarship period, with the amount paid according to applicable university fees and programme arrangements.

The scholarship does not provide a general living allowance or personal upkeep stipend.

Research-related travel must be justified and connected to the approved research rather than personal or leisure travel.

Mentorship and Research Support

A distinctive feature of the programme is that scholars receive support beyond financial assistance.

PhD scholars can receive mentorship to strengthen their AI and Machine Learning research capacity. This can be particularly useful where the scholar's primary academic supervisor has expertise in the research discipline but limited specialist experience in AI.

The programme also aims to strengthen connections among African researchers working on responsible AI and development-focused applications.

Research Dissemination

The programme can support scholars in communicating their findings beyond the thesis itself.

Eligible dissemination activities can include conference participation and publication of research findings.

Scholars are also encouraged to translate research findings into policy-oriented outputs, including policy briefs that can communicate relevant evidence to decision-makers.

This reflects the programme's wider objective of connecting AI research with practical development and policy challenges in Africa.

Who Can Benefit

The programme is particularly relevant to African researchers whose existing doctoral or academic work can be strengthened through AI or Machine Learning.

For example, a PhD researcher studying agriculture could potentially incorporate machine-learning methods into crop disease detection, pest prediction, yield forecasting or agricultural decision-support systems.

Similarly, researchers in health, environmental science, engineering, economics or social sciences may be eligible where AI is an integral part of the research rather than an incidental topic.

Applicants should therefore demonstrate a genuine connection between their research problem and AI/ML rather than simply adding AI terminology to an unrelated proposal.

Important Eligibility Limitation

This programme should not be confused with a scholarship for someone who is only planning to start a PhD.

A candidate who has been admitted to a PhD programme but has not yet obtained faculty approval for the research proposal does not meet the stated PhD eligibility requirements.

Likewise, an African student enrolled in a university outside Africa is not eligible for the PhD scholarship under the programme's current rules.

These restrictions make the opportunity particularly suitable for researchers who are already well into their doctoral research.

Application Requirements

Applicants should be prepared to provide evidence of their academic and research status and demonstrate how their work incorporates AI or Machine Learning.

For PhD applicants, documentation relating to the approved and defended research proposal is particularly important.

Applicants should also be able to explain:

• The development problem their research addresses
• How AI or Machine Learning is being applied
• Why the research is relevant to responsible AI
• The expected research outputs
• How the findings could benefit African communities, institutions or policy
• What additional support is required to complete the research

Applicants in the Early Career Academic category have additional institutional and team requirements.

Application Advice

The strongest application should make the relationship between the research problem, AI/ML methodology and development impact immediately clear.

Avoid presenting AI simply as a fashionable technology. Explain the specific research task that requires AI or Machine Learning and why the approach is appropriate for the African context.

Applicants should also demonstrate that their research is sufficiently advanced to benefit from the programme. For PhD applicants, proposal approval should already have been completed before submission.

It is also useful to distinguish between expenses that directly advance the research and general personal costs, since the scholarship is designed primarily as research support rather than a living stipend.

Important Dates

Application deadline: November 30, 2026

Applicants should confirm the final submission time and any programme-specific document requirements on the official application portal before submitting.

How to Apply

Eligible applicants should apply through the official AI4D Africa scholarship application process and select the appropriate category: PhD or Early Career Academic.

Applicants should ensure that their university, research stage and proposed AI/ML work satisfy the programme requirements before completing the application.