In early April, the Rwandan government hosted the inaugural Global AI Summit on Africa, which served as a forum to facilitate critical discussions on the impact of artificial intelligence (AI) in Africa and present tangible progress made within the AI startup, digital infrastructure, economic, and governance landscape. With almost 2,000 delegates in attendance, a significant number of whom were from Africa, the event provided a venue for global stakeholders to understand the nuances and experiences of advancing AI in Africa. Over two days, the summit presented a diverse array of sessions, side events, and cultural celebrations. For many observers of AI governance and policy, this marked the first major international forum where African perspectives were comprehensively represented, resulting in the first Africa Declaration on Artificial Intelligence (“Declaration”).
The Africa Declaration on Artificial Intelligence
The Declaration presents a roadmap for advancing AI development in Africa, while setting goals for African countries and stakeholders across the continent to ensure AI development aligns with African values, priorities, and cultural contexts. Signed by 49 out of 55 African Union member states, the African Union secretariat, and Smart Africa, the Declaration represents the first cohesive AI-focused agreement within the continent, and this development occurs within a broader context of international AI governance initiatives. Numerous other AI declarations have emerged over the past few years, including the Bletchley Declaration, the Hamburg Declaration on Responsible AI, and the Global Partnership on Artificial Intelligence’s New Delhi Declaration. However, these previous efforts have demonstrated limited transparency regarding implementation strategies and outcomes of accompanying funding commitments. The Africa Declaration’s success will ultimately depend on whether signatory nations can effectively align with the outlined objectives and follow through on their commitments.
Geopolitical challenges and regional fragmentation
Despite the summit’s achievements, several structural challenges threaten the harmonization of Africa’s AI ambitions. The event itself appeared to be affected by geopolitical tensions, most notably Rwanda’s ongoing conflict with the Democratic Republic of Congo. From my observation, this situation led to a notable absence of representatives from prominent funders within the African AI ecosystem, particularly international development agencies from European and North American countries. The limited presence of African Union employees, aside from the chairperson of the African Union Commission and the Commissioner of Infrastructure and Energy, further highlighted these perceived tensions. Additional conflicts, such as violent extremism in the Western Sahel, the departure of authoritarian-ruled countries from the ECOWAS regional bloc, and the humanitarian crisis in Sudan, continue to impact regional harmony. These divisions raise concerns that efforts to position the continent as a “major AI player” may inadvertently lead to further stratification. Such fragmentation could advance the goals of larger countries with more economic resources to devote to AI, while marginalizing smaller countries with fewer resources, a pattern that mirrors existing economic inequalities within the continent.
Avoiding the trenches of AI hype in Africa
My engagement in the summit revealed concerning patterns of AI hype that reflect broader issues in Africa’s technology and development discourse. The fundamental premise that AI represents a panacea for Africa’s myriad challenges across effective governance, corruption, socioeconomic development, infrastructure, and conflict demonstrates a form of technological determinism that warrants critical examination. This ethos is encapsulated in the term “technosolutionism,” which is the belief that societal problems can be solved through technological solutions, often with a focus on digital technologies and automation.
Evidence of this “technosolutionist” approach emerged in a report distributed at a session sponsored by Google, Sand Technologies, and the African Leadership University. This document claimed that “AI is the Only Way to Transform Critical Sectors in Sub-Saharan Africa.” This assertion exemplifies the ideology of technosolutionism, which has become increasingly prominent in efforts to “democratize” AI development and implement solutions targeted toward the United Nations’ Sustainable Development Goals, a set of 17 interconnected goals adopted by all United Nations (UN) member states in 2015. Such claims require particular scrutiny, given that large and emerging tech companies have significant incentives to promote these narratives. These organizations seek to sell applications to consumers, businesses, and governments, with African governments likely representing the largest potential market for AI solutions across the continent. This commercial interest creates inherent conflicts when evaluating the objective merits of AI interventions.
The past few years have given rise to numerous problematic claims that demonstrate the gap between AI hype and current technical capabilities, and Africa has not been exempt from this. During the summit, a comment was made that artificial general intelligence (AGI) would arrive by the end of 2025, a timeline unsupported by current AI progress and expert consensus. The concept of AGI itself raises important questions about cultural and linguistic inclusivity. AGI refers to a hypothetical form of AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks and domains, similar to or even surpassing human cognitive abilities. If an AI system cannot function effectively across diverse languages, contexts, and domains, its claim to “general intelligence” becomes questionable. Current definitions of AGI often implicitly assume Western, English-speaking contexts, excluding the experiences and needs of millions of communities who make up a significant portion of the world’s population. Similarly, a comment made stating intentions to build large language models (LLMs) for every African language, demonstrate both technical infeasibility and conceptual misunderstanding given linguistic data gaps and infrastructural deficiencies that inhibit model performance for African languages. However, these attempts to adopt mainstream paradigms of AI development may overlook the greater utility of small language models, which show promise for consumers using mobile devices in resource-constrained settings.
The reality is that AI systems are quite far from being generally intelligent, LLMs are not the solution to every natural language processing challenge, and this interest in accelerating toward AGI is a significant factor driving AI hype, along with negative climate and social impacts.
Balancing perspectives on AI’s potential
Due to the need for substantial progress in addressing fundamental development issues on the African continent, AI adoption efforts may generate positive spillover effects, even if (and when) the current AI bubble contracts. Because meaningful participation in AI research and development necessitates sizable investment in electrical infrastructure, telecommunications, cloud computing, and education, investments in these areas could enable African countries to deliver stable electricity, higher internet penetration, better access to digital services, and stronger educational systems to their citizens. Such improvements could potentially result in more robust health care systems, higher agricultural yields, reduced poverty, greater employment opportunities, and improved governance structures. In lieu of this vision becoming reality, AI hype should not distract governments from making fundamental progress toward development needs independent of their AI interests.
Recommendations for responsible AI development in Africa and beyond
The pursuit of AI innovation in Africa should prioritize technical approaches that align with local constraints and opportunities. Edge computing, federated learning, and model quantization represent promising directions that can address infrastructure limitations while maintaining effectiveness. These approaches acknowledge the realities of resource-constrained environments while avoiding the computational intensity and connectivity requirements of large-scale AI systems.
Effective AI development in Africa requires grounding in current realities rather than aspirational technological visions. This approach demands that AI systems be accessible to consumers and reflect the demands of the continent’s growing population. Development priorities should focus on addressing immediate needs while building capacity for future innovation.
AI research must also be driven by African stakeholders and rooted in the contexts of the continent. This principle requires meaningful participation from local researchers, developers, policymakers, and civil society organizations. While maintaining ambitious goals remains appropriate, these objectives must be realistic and achievable within existing constraints.
Researchers, developers, funders, policymakers, and civil society advocates must play a significant role in countering AI hype. This responsibility includes promoting evidence-based approaches, challenging unrealistic claims, and ensuring AI development priorities align with genuine needs rather than commercial interests.
Ending reflections
The inaugural Global AI Summit on Africa represents a significant milestone in the global AI ecosystem, particularly in centering African perspectives and priorities. However, the event also highlighted persistent challenges including geopolitical tensions and the influence of technosolutionist thinking—critical aspects that must be considered as the organizers prepare for a second convening. The true measure of progress in AI development lies not in the sophistication of algorithms but in whether these tools genuinely serve the people and communities they seek to empower. Without grounding in human dignity and local contexts, AI acceleration risks creating technological microcosms of subjugation rather than serving as catalysts for indigenous self-determination.
As Africa continues to engage with AI development, success will depend on maintaining realistic expectations, addressing fundamental infrastructure and development needs, and ensuring that technological progress serves broader goals of social and economic empowerment. The continent’s AI future should be shaped by African voices, priorities, and values, not by external hype or commercial interests that may not align with local needs and aspirations.
