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Roads, ports and power plants are financed for forty years. The technology around them changes every five. Projects that plan for that gap will hold their value; projects that ignore it will be obsolete before they are paid for.
Most boards treat AI as an IT project or a future compliance matter. The real exposure is already inside their institutions: in the decisions AI quietly shapes, and in systems nobody has inventoried.
Development finance has funded hundreds of AI pilots and few lasting capabilities. The fix is to fund AI the way good investors fund anything uncertain: as a managed portfolio with stage gates, shared foundations and clear exits.
Vendors, consultants and internal teams all bring AI claims to the executive table. Five questions from research practice separate the claims worth funding from the ones worth a polite no.
Building frontier AI models is out of reach for most governments. Controlling the data, standards, skills and procurement that determine how AI serves citizens is not.
Before customers send AI agents to do their banking, every bank needs a control point that knows who is acting, under which mandate and within which limits.
Speed is not the risk in leaving the core. Moving everything at once is.
Kenya's branches handle a sliver of transactions and half of the value. One chart on where a bank's accuracy really matters.
AI, agents, delegates and mandates are not interchangeable. Boards that use them precisely make better decisions about what to automate.
The banks that leave the packaged core fastest will be the ones ready for customers who bank through AI agents. Here is what to adopt instead, and in what order.
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