Unlocking the Potential: AI in Sub-Saharan Africa

Departmental Papers, July 21, 2026

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Unlocking the Potential: AI in Sub-Saharan Africa

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Bibliographic details

• Authors: Martin Schindler, Andrew J Tiffin, Andrea Richter Hume, Kamil Dybczak, Marwa Ibrahim, Youssouf Kiendrebeogo, Jacinta Bernadette Shirakawa, Nikola Spatafora, Solo Zerbo
• Published: July 21, 2026
• Series: Departmental Papers
• DOI: https://doi.org/10.5089/9798229047821.087

Overview

• Title: Unlocking the Potential: AI in Sub-Saharan Africa
• Authors: Martin Schindler, Andrew J Tiffin, Andrea Richter Hume, Kamil Dybczak, Marwa Ibrahim, Youssouf Kiendrebeogo, Jacinta Bernadette Shirakawa, Nikola Spatafora, Solo Zerbo
• Publication date: July 21, 2026
• Summary of purpose:
  • Applies recent AI-exposure and productivity methods to sub-Saharan Africa (SSA).
  • Combines country-level estimates with adoption scenarios and evidence from emerging African use cases.
  • Focuses on whether SSA countries can adopt, adapt, and scale AI quickly enough to capture benefits and avoid falling further behind.

Key Findings

• General observation:
  • Artificial intelligence (AI) is emerging as a general-purpose technology with the potential to reshape productivity, labor markets, and growth trajectories worldwide.
• Regional emphasis:
  • For sub-Saharan Africa (SSA), the central concern is not the risk of technological disruption, but whether countries will be able to adopt, adapt, and scale AI quickly enough to capture its benefits and avoid falling further behind.
• Methodology and contribution:
  • The paper applies recent AI-exposure and productivity methods to sub-Saharan Africa, combining country-level estimates with adoption scenarios and evidence from emerging African use cases.
• Current capacity constraints in SSA:
  • Unreliable and insufficient electricity.
  • Limited digital infrastructure.
  • Scarce technical skills.
  • Gaps in regulatory and institutional capacity.
• Outlook:
  • AI gains are within reach if countries move quickly to strengthen the foundations for adoption.

Policy Implications and Recommendations

• Priorities to unlock AI potential in SSA:
  • Strengthen electricity supply to address unreliable and insufficient electricity.
  • Expand and improve digital infrastructure.
  • Invest in technical skills to reduce scarcity of qualified personnel.
  • Close gaps in regulatory and institutional capacity to enable safe and effective adoption and scaling of AI.
• Strategic approach:
  • Combine country-level diagnostics with tailored adoption scenarios and support for emerging local use cases to guide policy sequencing.

Publication and Metadata

• Series: Departmental Paper No 2026/013
• Volume: 2026
• Issue: 013
• Pages: 56
• DOI: https://doi.org/10.5089/9798229047821.087
• ISBN: 9798229047821
• ISSN: 2616-5333
• Access note included in source: Visit the IMF eLibrary (our eLibrary offers over 25,000 IMF publications in multiple formats).
• Citation preview provided in source: Martin Schindler, Andrew J Tiffin, Andrea Richter Hume, Kamil Dybczak, Marwa Ibrahim, Youssouf Kiendrebeogo, Jacinta Bernadette Shirakawa, Nikola Spatafora, and Solo Zerbo. "Unlocking the Potential: AI in Sub-Saharan Africa", Departmental Papers 2026, 013 (2026), accessed 8/13/2026, https://doi.org/10.5089/9798229047821.087

Content derived from "Unlocking the Potential: AI in Sub-Saharan Africa", Departmental Paper No 2026/013 (July 21, 2026).

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