Ghana’s ability to leverage artificial intelligence as a governance and development instrument depends less on the sophistication of its technology imports than on whether its institutions can bridge the persistent gap between research output and practical implementation.
That was the substantive challenge framed by Ernest Brogya Genfi, Presidential Adviser on National Resilience and Emergency Preparedness, speaking on behalf of Chief of Staff Julius Debrah at the 2nd Applied Research Conference of Accra Technical University (ARCATU 2026) on 15 April 2026. The conference, convened under the theme “Applied Research and Innovation for Sustainable and Resilient Development in the Era of Artificial Intelligence,” assembled researchers, policymakers, industry practitioners and development partners to examine how Ghana’s innovation ecosystem translates knowledge into measurable public value. Brogya Genfi’s remarks, while diplomatic in tone, pointed to a structural failure that extends well beyond Ghana’s borders: across West Africa, universities and research institutions generate considerable intellectual output that rarely reaches the policy or market stage in any systematic way.
The thesis Brogya Genfi advanced is straightforward, and worth taking seriously. Ghana does not suffer from an absence of ideas or talent. Its universities and technical institutions produce research across agriculture, health, infrastructure and digital systems. What the country lacks, he argued, is an institutional architecture capable of converting that research into products, services and sound public policy at scale. “Our main challenge is moving these ideas into use,” he said, framing applied research not as an academic exercise but as a governance instrument whose value is measured by its impact on citizens’ lives. This framing has direct implications for how Ghana and its regional peers structure technology policy, research funding and public-private collaboration.
The announcement of Ghana’s National Artificial Intelligence Strategy 2025-2035, launched in April 2026, provides the formal policy vehicle for this ambition. The strategy positions AI as a tool for improving planning, public service delivery and information management, three domains where Ghana, like most ECOWAS member states, faces chronic institutional deficits. But a national strategy document, however well-designed, does not automatically produce institutional capacity. The critical variable is whether Ghana’s ministries, regulatory bodies and public universities are equipped to operationalise AI deployment in ways that reflect local socioeconomic conditions rather than simply replicating models designed for high-income contexts with fundamentally different data environments and infrastructure baselines.
Brogya Genfi was explicit on this point, and it represents the most analytically significant dimension of his remarks. AI systems deployed in Ghana must, he argued, be built around the realities of the communities they serve, including local languages, cultural contexts, livelihood structures and economic constraints. This is not a peripheral concern. Across West Africa, AI tools developed without adequate local data risk encoding existing inequalities or generating outputs that are simply irrelevant to the populations they are meant to serve. Ghana’s linguistic diversity alone, encompassing Twi, Ewe, Ga, Dagbani and dozens of other languages, presents a data challenge that no off-the-shelf model from a North American or European technology firm is designed to address. Building locally relevant AI systems requires investment in local datasets, local engineering capacity and regulatory frameworks that incentivise this kind of grounded development.
The regional dimension of this challenge deserves direct attention. Within ECOWAS, Ghana occupies a position as one of the more institutionally stable and digitally advanced economies, alongside Senegal and Côte d’Ivoire. The AfCFTA framework, now in its operational phase, creates both the opportunity and the pressure for member states to develop interoperable digital infrastructure and harmonised data governance standards. If Ghana develops an AI governance framework anchored in local needs and responsible deployment principles, it has the institutional credibility to shape regional norms, particularly in contrast to Nigeria, whose larger market and more complex regulatory environment make coherent AI governance harder to achieve quickly. Senegal, meanwhile, has moved aggressively on digital infrastructure investment, and Côte d’Ivoire has attracted significant fintech capital. Ghana’s comparative advantage in this space will depend on whether its AI strategy produces enforceable standards and replicable public-sector use cases, not merely policy declarations.
The governance mechanism that matters most here is the link between research funding, university output and public procurement. In most ECOWAS economies, this link is weak or non-existent. Public institutions rarely procure domestically developed technology solutions, research councils operate with limited mandates and budgets, and universities have few structural incentives to orient research toward national policy problems. Addressing this requires deliberate institutional redesign: procurement rules that create market access for locally developed AI tools, research funding tied to demonstrable policy relevance, and formal channels through which universities engage with sector ministries on applied problems. Ghana’s Ministry of Finance and Ministry of Communications and Digitalisation would need to coordinate on this, a form of inter-ministerial alignment that has historically been difficult to sustain.
For investors and development finance institutions operating in West Africa, the signals from ARCATU 2026 are worth parsing carefully. A government that frames AI adoption around value creation for citizens rather than technology adoption for its own sake is signalling a more disciplined approach to public digital investment. That discipline, if institutionalised, reduces the risk of costly technology procurement that delivers little public return, a pattern that has undermined confidence in public-sector digital projects across the region. The Bank of Ghana and sector regulators will ultimately determine whether the National AI Strategy produces binding standards or remains aspirational, and that determination will shape how seriously international technology partners and development banks engage with Ghana’s digital economy agenda.
The policy pathway is visible, even if the execution remains uncertain. Ghana needs to move from strategy to institutional mechanism: a funded national AI research agenda with clear sector priorities, procurement frameworks that reward locally grounded solutions, and a regulatory body with the technical capacity to assess AI systems for bias, data adequacy and public-interest alignment. ECOWAS could play a coordinating role in harmonising data governance standards across member states, reducing duplication and enabling the kind of cross-border data flows that would make regionally trained AI models viable. The AU’s Digital Transformation Strategy for Africa provides the continental scaffolding; what Ghana builds within that framework will determine whether it leads or follows in shaping West Africa’s AI governance architecture.
