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Beyond the AI Policy: When Governance Becomes Operational Accountability An organization does not demonstrate responsible AI governance by merely publishing an AI policy. It demonstrates responsibility when that policy changes how AI use cases are assessed, approved, deployed, monitored, challenged and held accountable. Across Africa, artificial intelligence is moving from a specialist technology conversation into the practical domains of public administration, financial services, health, education, media and elections. This creates a strategic opportunity. It also creates a governance test: can institutions adopt AI in a way that improve outcomes without weakening rights or public trust The answer will not be found in policy documents alone. It will be found in whether principles such as fairness, transparency, privacy, safety and accountability are translated into everyday decisions. The African Union’s Continental Artificial Intelligence Strategy places this challenge wi...

AI Governance Cannot Be the Responsibility of Technology Teams Alone The conversations at the AI and Democracy Forum in Abuja reinforced an important point: responsible AI governance cannot be treated as the responsibility of technology teams alone. It requires collaboration among policymakers, civil society, researchers, businesses, technology professionals, institutions, and citizens. One of the most important lessons in AI governance is that governance must begin before deployment. By the time an AI system is in use, critical decisions may already have been made about the data it relies on, the risks considered acceptable, the people who may be affected, and who will be held accountable for the outcome. This is why organisations need visibility into how AI is being used. They should be able to identify the systems in operation, understand the decisions those systems influence, assess the data involved, recognise who may be affected, and assign clear responsibility for ov...