• Inclusive AI deployment could add up to $1 trillion to Africa’s GDP by 2035, the AfDB said.
• The report lays out three scenarios, with productivity gains ranging from about $250 billion to $1 trillion.
• The full-activation scenario also projects 35 million to 40 million digital-related jobs.

Inclusive deployment of artificial intelligence could add up to $1 trillion to Africa’s GDP by 2035, or nearly one-third of the continent’s current economic output, driven by productivity gains across many sectors, according to a report published on December 12 by the African Development Bank (AfDB).

Titled “Africa’s AI productivity gain - Pathways to labour efficiency, economic growth and inclusive transformation,” the report said the expected productivity gains from developing and deploying AI at scale are a realistic opportunity, supported mainly by the continent’s growing digital capabilities, favorable demographics, and ongoing sector reforms. It presented three scenarios for Africa’s possible AI trajectories by 2035.

The first scenario, “Status Quo Drift,” would translate into modest productivity gains of around $250 billion and limited benefits for the job market. The second scenario, “fragmented progress,” could lead to productivity gains of about $500 billion to $600 billion and positive job market effects in only some countries.

The final scenario, “full activation,” has the potential to deliver $1 trillion in productivity gains, create 35 million to 40 million digital-related jobs, and achieve broad sector and regional coverage. Naturally, only the third scenario would unlock the full social and economic potential of AI on the continent.

Africa’s ability to fully harness AI-driven productivity gains depends on five interdependent factors: computing power, data, human skills, trust, and capital. Reliable and interoperable data are essential for using AI, while powerful and scalable computing infrastructure is a prerequisite for effective deployment of solutions. A skilled workforce is critical to develop and maintain AI systems, while trust, supported by strong governance and regulatory frameworks, is key to adoption. Adequate capital is also required to build infrastructure, reduce risks, and accelerate innovation.

A three-phase roadmap

On computing power, the report said the continent should establish six “data embassies” rich in graphics processing units (GPUs), including four central nodes and two peripheral nodes, governed by an African Union charter, based on the authors’ modeling. Around 60 national and regional open data platforms aligned with FAIR principles (Findable, Accessible, Interoperable, Reusable) should also be set up across regional economic communities.

On human capital, around 3 million professionals would need to be trained for AI-related jobs.

A legal framework for managing AI-related risks should also be adopted at the African Union level and implemented by more than 20 African countries to strengthen trust in the technology. In addition, about $10 billion in blended finance would need to be mobilized under the leadership of the African Fund for AI Growth and Innovation.

Prepared by consulting firm Bazara Tech as part of the G20 Digital Transformation Working Group, the report also outlined a three-phase roadmap to turn Africa’s AI potential into tangible results. The first phase, known as “ignition,” would run from 2025 to 2027 and focus on establishing policy frameworks, launching pilot projects, and initiating the rollout of computing power.

The “consolidation” phase, from 2028 to 2031, would involve creating regional computing and data corridors and developing skills and capital. A final “scaling” phase would allow for the full deployment of AI readiness across all regions and sectors.

Five sectors to capture 58% of gains

Africa’s 54 countries do not start from the same level of readiness for AI adoption. To guide policy and investment priorities, the report grouped countries into four categories based on their readiness to deploy AI: “catalytic agents,” large and dynamic economies such as Nigeria, Kenya, and South Africa; “scale accelerators,” mid-sized countries with emerging AI ecosystems such as Ghana, Morocco, Tunisia, and Côte d’Ivoire; “innovation hubs,” countries with smaller but agile digital systems suited to testing new policies, including Rwanda and Mauritius; and “foundation builders,” countries that need support to develop core capabilities.

Bridging the gaps between these four categories is essential to achieve regional equity and avoid a two-speed transition.

The report also noted that AI-related productivity gains will not be evenly distributed across economic sectors. Using a data-driven scoring model based on GDP share, digital readiness, and leverage of the Sustainable Development Goals, the authors identified five high-potential sectors: agriculture and food systems (20%), wholesale and retail trade (14%), manufacturing and Industry 4.0 (9%), finance and financial inclusion (8%), and health and life sciences (7%). Together, these sectors are expected to capture 58% of total AI-driven gains, or about $580 billion by 2035, reflecting their economic weight, strong capacity to adopt AI, and high potential for inclusive development.

 Other sectors do not stand out for high individual potential, but together they represent a significant opportunity estimated at $420 billion, or 42% of the expected productivity gains. In the energy sector, AI can refine demand forecasting, balance smart grids, and detect failures before they spread. In transport and logistics, the technology can support real-time traffic management, intelligent fleet route optimization, and predictive maintenance programs that extend asset lifespans.

Walid Kéfi