Ghana's National AI Strategy, an ambitious policy document for sub-Saharan Africa, risks concentrating wealth among large corporations. This concentration arises from existing control over critical infrastructure, telecommunications, and financial institutions. These entities already possess the computing power and distribution networks needed to leverage artificial intelligence (AI) at scale.
This outcome is not due to malicious intent but stems from inherent structural factors within the economy. AI profoundly creates value at scale. In emerging markets like Ghana, this scale naturally gravitates towards established players. These include multinational technology firms and large domestic institutions that already hold significant market power and data assets. The strategy's focus on fintech, agriculture, and creative industries, while appropriate, faces this fundamental challenge.
This scenario fits into the broader Ghanaian economic narrative of balancing growth with equitable distribution. Data from the Ghana Statistical Service consistently highlights the importance of inclusive growth. The AI strategy, mirroring trends in digital platform economics, could widen the gap between well-resourced entities and smaller businesses or individuals. Ensuring that economic benefits of technological advancement are broadly shared is a perennial policy challenge for Ghana.
Paulette Watson MBE highlighted this issue in a recent analysis on BFTOnline. She noted that ambition alone does not guarantee equitable value capture from AI. "That is decided later, in procurement rooms, data licensing agreements, and talent pipelines," Watson stated. She stressed the need for business leaders and policymakers to actively consider who benefits from the strategy's design.
What happens next hinges on explicit policy interventions regarding data ownership and access. Without these, the AI layer built on Ghana's ambitious strategy will likely reinforce existing economic advantages. This means addressing questions of who licenses access to national datasets and on what terms. It also involves ensuring that value derived from community data is fairly shared with the original data subjects.
Policymakers must seriously consider designing participation into the AI system from the outset. This moves beyond post-facto redistribution. It involves creating inclusive talent pipelines, particularly for women who are underrepresented in STEM fields. Currently, women make up less than 25% of Ghana's STEM workforce. Addressing this gap is critical for national competitiveness. Furthermore, business leaders must integrate inclusion as a core strategy, not just an ethical consideration. This means validating data sourcing for representativeness. It also means prioritising inclusive approaches in public procurement processes. The success of Ghana's AI strategy depends on ensuring its benefits reach all citizens, fostering broad-based economic growth.