National AI strategies often fail at the point between ambition and deployment. The AI for Impact model is interesting because it makes that gap visible and gives teams a structured route from problem definition through data, design, development and deployment.
The real test is not the challenge itself. It is whether prototypes become adopted services, whether institutions can support them and whether impact can be measured beyond launch-day visibility.
For Apex Intelligence, this becomes a trackable policy story: strategy, programme, prototype, adoption, outcome.