Let's Create Africa

Why the AI progress bar is stuck - Deep Dive


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We keep talking about AI like it’s a simple upgrade. New model, better prompts, bigger "wow". But after my first Cornell CAIO session on abundant intelligence, one uncomfortable truth became clearer: in most organisations, the AI progress bar is not stuck because the tools are weak. It’s stuck because the foundations are missing.

AI is now capable enough to feel like magic. Yet the hard work is still stubbornly human: data classification, access controls, procurement, security, accountability, and the courage to say “not in production yet” even when the demo looks perfect. The World Bank’s recent work on AI foundations makes the point that progress depends on readiness, not hype. That resonates deeply in African and LMIC contexts, where the gap between “pilot” and “operational reality” can swallow budgets and reputations.

And then there’s the shift many leaders are underestimating: we’re moving from automating tasks to automating workflows. Once AI enters workflows, it touches money, identity, customer trust, and compliance. That’s not an app decision. It’s an institutional decision.

In Africa, the progress bar also sticks for a different reason: distribution is strong, but governance is uneven. Mobile is already a major economic rail on the continent, contributing USD 220 billion in 2024 (about 7.7% of GDP). So yes, we can deploy at scale. The question is whether we can deploy responsibly, with sovereignty, safety, and inclusion built in.

In this episode, I’ll unpack the real blockers behind “stuck AI" and share a simple lens for leaders: capability is abundant, but readiness is scarce. If we want the progress bar to move, we stop chasing the next demo and start building the muscle that makes AI boring, reliable, and accountable.

If your organisation is “AI curious” but progress feels slow, this conversation is for you.

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