Project Summary

This 12-month pilot aims to establish early, locally led frontier AI governance capacity in Africa, starting with Nigeria. The project addresses a critical global AI governance gap: Africa is rapidly adopting advanced AI systems, yet institutional oversight is extremely limited. By building practical governance capacity, the pilot reduces global catastrophic AI risk while creating a scalable model for the continent.

The focus is on delivering concrete, governance-grade outputs:

• Policy frameworks for high-risk AI deployment adapted to African contexts.

• Applied AI risk assessment briefs informing policymakers.

• A small cohort of trained AI governance fellows embedded in or advising public institutions.

This pilot tests feasibility, demand, and pathways for scale rather than immediately building a large institution.

Project Goals (12 months)

1. Produce 2–3 frontier AI governance frameworks adapted to African institutional realities.

2. Establish an applied AI risk assessment function capable of producing actionable risk briefs.

3. Train and place 5–10 AI governance fellows in or alongside public institutions as proof of concept.

Approach

• Conduct focused research on AI policy and governance aligned with global safety standards, localized for African contexts.

• Develop governance-grade risk assessment methods, including capability mapping, misuse scenario analysis, and deployment risk reviews, tailored for policymakers.

• Run a selective fellowship program combining intensive training with hands-on advisory or embedding roles.

• Leverage existing relationships with policymakers, regulators, and civil society to validate outputs and encourage uptake.

Use of Funds
Funding will support rapid execution through:

• Part-time founder stipend to ensure sustained delivery

• Research and policy drafting support

• Fellow training workshops and modest stipends

• Small technical and analytical infrastructure costs

• Government engagement, convenings, and dissemination of outputs

The budget is lean and focused on direct outputs rather than overhead.

Team & Track Record
The project is led by Muhammad Ahmad, Founder and Executive Director of the Responsible AI Governance Initiative (RAI-GI). Muhammad has extensive experience at the intersection of AI governance, institutional capacity-building, and African policy contexts. He is a recognized contributor in global AI governance communities and has led multi-stakeholder initiatives, policy-relevant research, and collaborations with public institutions and civil society.

The pilot will also draw on part-time advisors and collaborators with policy, technical, and civil society expertise.

Risks & Contingencies
Likely causes of failure:

• Slower-than-expected government engagement

• Difficulty recruiting qualified fellows

• Overextension of scope beyond the pilot’s capacity

Potential outcomes if the project fails:

• Partial delivery of outputs (e.g., fewer frameworks or fellows)

• Limited immediate policy uptake

Even in the event of partial failure, the project will generate valuable research, lessons, and credibility signals to inform future AI governance initiatives in Africa.

Funding History
Over the past 12 months, the initiative has operated on minimal external funding, primarily founder time and in-kind contributions. No significant institutional grants have yet been secured; this application represents an early effort to move from conceptual planning to tangible execution.

Contact & Info
Website: www.ResponsibleAiGovernance.org
Email: muhammad@ResponsibleAiGovernance.org
LinkedIn: Muhammad Ahmad