The conversation about AI in Africa has changed. The question is no longer whether the continent will adopt AI, but whether it can create the conditions to use it responsibly, confidently and at scale.That question is becoming more important as AI systems grow more capable and become increasingly embedded in how organisations work. At the heart of that shift is a defining question of trust: can an organisation benefit from AI without surrendering control of the data, intellectual property and institutional intelligence that make it distinctive?That challenge is already visible in adoption patterns. Microsoft’s Global AI Diffusion Report for the first quarter of 2026 found generative AI usage among working-age populations at 27.5 per cent in the global north compared with 15.4 per cent in what the report categorises as the global south, with the gap continuing to widen. For Africa and other countries across the global majority, closing that gap is both an economic imperative and a chance to shape how the next phase of AI develops.The opportunity remains extraordinary. The African Development Bank estimates that, if developed and deployed inclusively, AI could contribute as much as $1 trillion in additional GDP across Africa by 2035. Realising that opportunity will depend on whether Africa can build AI ecosystems that people and institutions trust.Trust is what enables innovation to move from experimentation to adoption and from adoption to economic impact. Building that trust will require progress across three mutually reinforcing areas: meaningful choice and openness, partnerships that develop local capability, and responsible, secure and resilient deployment.The African Union’s Continental Artificial Intelligence Strategy sets out an Africa-centric, development-focused vision for AI. It identifies the potential for AI to transform areas including healthcare, agriculture, finance, and education.Realising that vision requires African governments, companies, researchers and developers to have meaningful choice in how they build, deploy and govern AI.This means access to a model-diverse and interoperable ecosystem in which organisations can select the technology most appropriate to their needs. Governments and businesses should be able to choose among frontier, open, and specialised models without being locked into a single technological pathway.Openness should not mean the absence of safeguards. It should mean an ecosystem in which innovation can take place across technologies and providers, supported by common standards, appropriate governance, and the ability of customers to retain control of their data and intellectual property.This platform approach is particularly important for Africa. It can lower barriers for local developers, enable solutions to be adapted as community and market needs evolve, and give governments and enterprises greater resilience as models and technologies change.It also creates space for African innovators to participate in the AI value chain rather than simply consume products developed elsewhere.Choice alone will not close the AI adoption gap. Africa’s AI ambitions will also depend on partnerships capable of addressing the interconnected constraints that limit diffusion.No single actor can provide all these foundations. Governments must create enabling policy environments. Universities and research institutions must develop talent. African startups and established businesses must create locally relevant solutions. Civil society has an important role in shaping accountability and public confidence. Technology providers have an important role in contributing cloud infrastructure, technical expertise, security, and responsible AI practices.The strongest partnerships will be those that build enduring African capability, leaving governments and communities better equipped to develop, deploy and govern AI themselves.LINGUA Africa illustrates this approach. The $5.5 million initiative brings together the Masakhane African Languages Hub, Microsoft’s AI for Good Lab, the Gates Foundation and Google.org to strengthen responsibly sourced language data and models for African languages. The 26 selected projects span more than 50 African languages, dialects and sign languages spoken by more than 500 million people across 47 countries. AI systems that work more effectively in the languages people use can improve access to education, healthcare information, government services and economic opportunity.Responsible AI remains the foundation connecting these efforts. It should not be treated as a governance process applied after a system has been developed. Privacy, security, fairness, transparency, accountability, and appropriate human oversight must be incorporated throughout the AI lifecycle.For organisations, it means having the technical and operational controls needed to use AI without losing authority over their information, workflows, and intellectual property.
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