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Building African-Centered AI

How Africa can lead the global AI boom / Strive Masiyiwa. Artificial intelligence (AI) is among the most transformative technologies of the ...

How Africa can lead the global AI boom / Strive Masiyiwa.
Artificial intelligence (AI) is among the most transformative technologies of the 21st century, reshaping economies, industries, and societies worldwide. As Africa navigates this new technological era, it faces a critical choice: to adopt external AI regulations, such as those emerging from the European Union, or to develop its own frameworks tailored to the continent’s unique developmental trajectory. 

The need for African-centered AI is underscored by the reality that many AI systems developed in the Western world are often incompatible with African contexts. For example, language-processing models frequently overlook the continent’s rich linguistic diversity, and computer vision systems can struggle to accurately recognize African faces.

Moreover, the lack of representation and diversity in AI development teams can result in biased systems. Foundational Large Language Models (LLMs) such as Llama (Meta), Gemini (Google), Claude (Anthropic), Nova (Amazon), Granite (IBM), Mistral (Mistral AI), Nemotron (Nvidia), and Qwen (Alibaba) may inadvertently reinforce existing social inequalities and biases. 

African-centered AI aims to address these challenges by fostering the development of AI systems that are culturally sensitive, contextually relevant, and socially responsible. Achieving this goal requires the active involvement of African researchers, developers, and stakeholders throughout the AI development process. 

This can be achieved through collaborative research initiatives, capacity-building programs, and community-driven projects. By prioritizing African perspectives and values, African-centered AI can foster a more equitable and inclusive AI ecosystem—one that benefits African communities and advances sustainable development across the continent.

One notable example of African-led AI development is the African Institute for Mathematical Sciences (AIMS), which has established a network of research centers and innovation hubs across the continent. AIMS has played a pivotal role in advancing AI research and development in Africa, while fostering collaboration and knowledge-sharing among African researchers and institutions. Similarly, the African Center for Technology Studies (ACTS) has been at the forefront of promoting science, technology, and innovation across Africa, with a strong emphasis on sustainable development and social impact. 

On 16 July 2025, ACTS officially launched the ACTS AI Institute (ACAII), a visionary initiative dedicated to advancing responsible, African-centered AI innovation, governance, and research. “We are engaged in the research and development of Africanized policies, standards, and ethical frameworks for AI. Specifically, we are already developing an Africanized adaptation of the Responsible AI toolbox,” said Dr Winston Ojenge, Principal Research Fellow and Head of the ACTS AI Institute.

Despite these efforts, the development of AI in Africa faces significant challenges, including limited infrastructure, inadequate funding, and a shortage of skilled personnel. Moreover, the brain drain of African talent to Western countries has hindered the growth of local AI ecosystems. To address these challenges, African governments, institutions, and stakeholders must prioritize investments in AI research and development, while promoting collaboration and knowledge-sharing among African researchers and institutions. 

African-centered AI is grounded in theoretical frameworks that prioritize African epistemologies, ontologies, and axiologies. A central paradigm shift within this perspective is Afrocentricity, which underscores the significance of African cultural values, histories, and lived experiences in guiding AI development. Afrocentricity affirms the data sovereignty, autonomy of African peoples while offering a critical lens through which to examine and deconstruct Western-dominated AI systems.

Don't be Afraid of AI

The rapid growth of Artificial Intelligence (AI) technologies has led to an increasing need for regulatory frameworks that can govern the development and deployment of AI systems. AI regulatory frameworks are designed to ensure that AI systems are developed and used in ways that are transparent, accountable, and beneficial to society. However, the development of AI regulatory frameworks can be a complex and challenging task, particularly in regions such as Africa, where the AI ecosystem is still in its early stages of development. 

The development of AI regulatory frameworks is a critical issue, as it can have a significant impact on the growth and development of the AI ecosystem in Africa. According to a report by the African Union, the adoption of legal frameworks and investments in AI technologies across the continent is expected to increase substantially in the coming years. Several African nations are already making notable progress in AI research and development (R&D), with the top 20 countries driving this transformation, including South Africa, Nigeria, Egypt, Kenya, Morocco, Ghana, Tunisia, Uganda, Cameroon, Tanzania, Zimbabwe, Algeria, Ethiopia, and Rwanda. 

''Our central argument is that AI ethical guardrails should be integrated directly into AI models and automated processes, rather than being imposed externally by policymakers or institutions that lack a deep understanding of the technology.''

Strive Masiyiwa, founder and Executive Chairman of Cassava Technologies, a Pan-African company that develops innovative solutions in Africa and internationally, emphasizes how Africa can take a leading role in the global AI revolution. Mr. Masiyiwa contends that Africa should not fear AI. He argues that the continent must avoid rushing into restrictive regulatory frameworks that could stifle innovation and hinder the growth of its emerging AI ecosystem. 

The continent must prioritize creating an enabling environment where AI research, experimentation, and technical innovation can thrive. Prematurely adopting restrictive AI regulatory frameworks modeled on the European Union’s AI Act or similar standards could inadvertently stifle innovation, limit experimentation, and create barriers for startups and local AI developers still building capacity. While such frameworks are designed for mature AI ecosystems with extensive data infrastructures, robust legal institutions, and well-established technological capabilities, many African nations remain in the early stages of development.

Cassava Technologies began in South Africa and later expanded into Egypt, Kenya, Rwanda, Morocco, and Nigeria, with operations continuing to grow across the continent. Cassava AI is poised to establish a comprehensive network of AI infrastructures and data centers throughout Africa, supporting the development of homegrown AI solutions and advancing the continent’s technological capacity. 

African nations should cultivate indigenous approaches to AI ethics and model development that are grounded in local realities and cultural values. Overregulation or the importation of foreign legal frameworks could hinder Africa’s ability to innovate, experiment, and compete in the global AI landscape. 

The continent’s historical experience with prematurely adopting international nuclear treaties offers a cautionary lesson for AI governance: many African states became signatories to the Nuclear Non-Proliferation Treaty in 1970 before building domestic expertise or developing a foundational understanding of nuclear science and technology. In contrast, Western countries had already developed advanced nuclear capabilities before enacting the treaty, using it to prevent other nations from attaining comparable levels of atomic development.

''Laws cannot effectively govern what is not yet fully understood. The ethical responsibility for artificial intelligence should rest primarily with the developers and architects of AI systems—a principle reflected in China’s approach, which has positioned the country at the forefront of the global AI revolution.''

As a result, the continent has remained largely reliant on external expertise—particularly in the initial development of civil nuclear energy—its progress constrained by prematurely ratified treaties and international regulatory frameworks, before building the capacity to explore, assess, and evaluate technologies within its own context. 

Prematurely importing foreign AI regulatory frameworks could similarly stifle local innovation and entrepreneurship, especially among emerging startups, researchers, and developers across Africa. A comparable outcome must be avoided in the development and governance of AI.

Dr. Nambili Samuel, a trained physician and seasoned AI researcher, advocates for a deliberate, informed, and technologically grounded approach to AI governance—one driven by African data scientists, AI developers, and policymakers who possess a deep, first-hand understanding of the technology.

''Formulating regulatory frameworks before establishing the foundational capacity for AI development in Africa could hinder the growth and evolution of Africa’s AI ecosystem.''

Adopting AI governance frameworks from external jurisdictions, particularly Western nations, risks perpetuating historical patterns of technological dependency, leaving Africa at a disadvantage. While the European Union’s AI Act is often championed as a comprehensive legal document, it has no use for Africa. It was designed for developed countries with strong economies, advanced data infrastructures, and well-established AI ecosystems. In contrast, many African nations still face significant challenges, lacking the foundational digital infrastructure and skilled talent pipelines necessary to support sustainable AI innovation.

Responsible AI

As Artificial Intelligence (AI) becomes increasingly integral to our daily lives, AI systems must be designed to provide helpful, safe, and trustworthy experiences for all users. Responsible AI practices ensure that the development and deployment of AI technologies prioritize ethical considerations, societal impact, and human well-being. 

For example, organizations incorporate Responsible AI principles throughout the AI development lifecycle, from data collection and model training to evaluation, testing, and deployment. The goal of Responsible AI is to place people at the center of design, balancing the benefits of AI systems with careful consideration of potential harms. Six key principles guide AI developers:

  1. Fairness – AI systems should be designed to provide equitable quality of service, ensure fair resource allocation, and minimize bias or stereotyping based on demographics, culture, or other characteristics.
  2. Reliability and Safety – AI systems must operate according to their intended purpose, values, and design principles, avoiding harm to users or society.
  3. Privacy and Security – Given AI’s reliance on data, strict safeguards are implemented to prevent unauthorized disclosure or misuse of information.
  4. Inclusiveness – AI systems should empower and engage diverse communities globally. Collaborations with underserved or minority communities help ensure systems are accessible and culturally sensitive.
  5. Transparency – Developers should communicate openly about how AI systems function, their limitations, and potential risks, so users can understand AI behavior.
  6. Accountability – Organizations must take responsibility for the impact of AI technologies, consistently applying ethical principles throughout design, deployment, and maintenance.

By adhering to these principles, Responsible AI seeks to foster innovation while safeguarding human values, societal trust, and equitable outcomes. Ethical responsibility in AI should rest primarily with those who design, build, and deploy AI systems. Developers, researchers, and innovators must integrate ethical safeguards and transparency directly into algorithms and AI models. China’s approach to AI governance offers valuable insights—placing the burden of ethical responsibility on creators while maintaining a dynamic regulatory framework that encourages technological progress.

AI ethics cannot be approached in the same manner as the regulation of cryptocurrencies; AI represents a fundamentally different technological and ethical governance.

Embedding guardrails such as fairness, accountability, and transparency within the technical architecture of AI systems ensures that regulation is proactive rather than reactive. This approach enables innovation to advance while simultaneously safeguarding against misuse. African nations must invest in developing localized AI ethics frameworks that reflect the continent’s cultural values, social realities, and economic aspirations. This involves:

  1. Strengthening AI Education and Research: Establishing centers of excellence to train local talent in machine learning, data science, and AI ethics.
  2. Creating Indigenous Ethical Benchmarks: Developing guidelines that are informed by African philosophical traditions, such as Ubuntu, which emphasize community, mutual respect, and collective well-being.
  3. Promoting Cross-Sector Collaboration: Engaging governments, academia, and industry to co-create regulatory frameworks that balance innovation with accountability.
  4. Encouraging Regional Integration: Leveraging the African Continental Free Trade Area (AfCFTA) to harmonize AI standards across nations and support intra-African technological collaboration.

Africa’s youthful population, growing digital infrastructure, and expanding innovation ecosystems position it as a potential leader in the global AI revolution. By focusing on ethical innovation and capacity building, Africa can leapfrog traditional industrial pathways and develop homegrown AI solutions for challenges in health, agriculture, education, and governance.

Rather than outsourcing regulation, Africa must lead with confidence, building AI for Africans, by Africans, and grounded in African realities. In doing so, the continent can redefine its role in the global economy, transitioning from a consumer of technology to a producer of transformative, ethical, and inclusive AI systems.

Conclusion

The future of AI in Africa hinges on visionary leadership—leadership that not only recognizes the immense potential of artificial intelligence to transform economies and societies but also remains vigilant to the risks of premature or externally imposed regulation. Effective governance must arise from a profound understanding of the technology’s underlying mechanisms, its socio-economic implications, and its contextual relevance to African realities. Regulatory frameworks shaped by fear or external political pressure risk stifling innovation and entrenching technological dependency. 

Instead, Africa’s policymakers and innovators must focus on embedding ethical principles within AI system design, fostering transparency, fairness, and accountability from the ground up. By investing in indigenous innovation ecosystems, cultivating local expertise, and encouraging cross-sector collaboration, Africa can craft a distinctly African model of AI development—one that is inclusive, sustainable, and globally competitive. In doing so, the continent positions itself not merely as a consumer of imported technologies, but as a co-architect of a more equitable and prosperous global digital future.

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