Africa’s push to harness artificial intelligence is moving from policy ambition to a harder question: whether governments and institutions have the data, skills, funding and oversight to deliver it.
From strategy to delivery
The African Union’s sixth Specialised Technical Committee on Communication and ICT opened its experts’ session in Libreville, Gabon, on 26 October. The meeting is reviewing progress on continental digital policy, including the AU’s AI strategy, data policy framework and digital transformation agenda.
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Its agenda puts implementation at the centre. Delegates are considering a proposed action and investment plan for the continental AI strategy, guidelines on AI governance and regulation, frameworks for data sharing and cross-border data flows, and measures intended to strengthen inclusion of women and young people in AI and digital policy.
That focus reflects a growing consensus among African policy specialists: publishing a national strategy is only the beginning. The more difficult work is establishing clear mandates, securing finance, building technical capacity and ensuring public institutions can assess and supervise technology suppliers.
Weak data foundations create risk
A 2026 OECD assessment based on a policy dialogue involving 12 African countries identified weak data quality and governance as a major obstacle to reliable and trusted AI. It cited inconsistent data standards, incomplete classification, poor interoperability and uneven enforcement of data-protection rules.
Those shortcomings matter because AI systems are only as dependable as the information used to train, test and operate them. In public services, unreliable or unrepresentative data can deepen exclusion, produce poor decisions and make it harder for citizens to challenge harmful outcomes.
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The OECD also highlighted gaps in affordable connectivity, computing capacity, stable funding and specialist skills. Many governments have agencies with relevant responsibilities, including data-protection authorities and telecoms regulators, but AI-specific expertise and coordination across ministries remain limited.
A question of African control
UNDP has argued that Africa’s AI future should be judged not by the number of strategies or data centres announced, but by whether investments build domestic capability, retain value locally and improve public outcomes.
That means decisions about procurement, local-language technology, cybersecurity, public data and energy infrastructure cannot be treated as secondary technical issues. They determine whether African countries can adapt and govern AI systems on their own terms, rather than becoming dependent on external platforms and vendors.
For Black communities across the continent and diaspora, the stakes are direct. AI is increasingly shaping access to information, financial services, health support, agriculture and government services. If African languages, lived realities and rights are absent from datasets and design choices, new technology can repeat old patterns of marginalisation.
What Libreville could change
The AU meeting runs through 29 October, with ministers expected to consider recommendations emerging from the experts’ discussions. A ministerial declaration is expected, but its significance will depend on whether it is matched by financing, enforceable governance and practical support for member states.
Related DGBN reporting includes African Union Opens Sixth ICT Committee Session in Gabon.
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Africa does not lack AI ambition. The immediate test is whether continental commitments translate into institutions and infrastructure capable of delivering trustworthy, locally relevant technology at scale.