Operationalizing AI for Economic Policymaking: Insights from ACET's Nigeria Creative Economy Hackathon
9th Mar. 2026, 8:45 PM .
What does it actually take to move AI from a flashy demonstration to a tool government will use? A new policy brief from the African Center for Economic Transformation (ACET)—developed in partnership with Nina Jojer Africa—draws on the AI for Digital Music Economy Hackathon in Nigeria to answer that question. And the answer has less to do with the technology than you might expect.
At the heart of the initiative was a challenge of institutional coordination, not engineering. Nigeria's government systems do not adequately capture data on the creative economy, leaving policy decisions on a fast-growing music industry poorly informed. To address this, NJA partnered with ACET to convene and sustain a Technical Working Group in early 2025—bringing together five government ministries and development agencies, including the National Bureau of Statistics and the Federal Ministry of Communications, Innovation & Digital Economy, to institutionalise cooperation beyond one-time consultations. This was the connective tissue that turned a hackathon into policy infrastructure.
Held in October 2025, the program drew 132 applications from 33 states, advancing 12 teams to build prototypes aimed at closing the creative economy's persistent measurement gap. But the brief's central argument is that AI's credibility in government rests on co-creation—embedding institutions into the design, risk management, and validation of the work rather than handing finished tools off to them. It examines what genuine multi-agency engagement really looks like, how data protection compliance was built in from the outset, and why the most common failure of innovation events isn't technical quality but the absence of ownership and follow-up.
Drawing on direct, ministerial-level engagement across government, the brief offers a practical blueprint for moving AI initiatives from experimentation to institutionalisation. Read the full document below.
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