Africa’s governments are moving on AI. Over half the countries reviewed in the State of AI Policy in Africa 2025—a research report published by Column, my B2B research and comms agency—have published national AI strategies.
But the report’s central finding is most of those strategies carry no binding laws, no dedicated budgets, and no monitoring frameworks to track whether anything changes.
Egypt and Ethiopia scored highest on our twelve-point AI Governance Maturity Index because they’ve attached institutional anchors, measurable milestones, and visible deployment to their plans. Most others publish good documents and stop there. Ambition is not in short supply, but accountability is.
That divide between strategy and delivery is a government problem, and it’s also an organisational one. African companies that wait for policy clarity before acting will fall behind those that don’t. The private sector has always moved faster than government, and AI is no different.
“The countries that treat AI as a public good—not a private experiment—will shape the continent’s technological and economic future.” — State of AI Policy in Africa 2025
AI and emerging technologies are projected to contribute $1.5 trillion to Africa’s GDP by 2030, according to the UN’s Economic Commission for Africa (ECA). Those gains won’t distribute evenly—they’ll flow to organisations that build the right foundations now.
Start with an AI audit, not an AI strategy
Before you buy a tool, build a policy, or hire an AI consultant, you need to know where you actually stand.
Run an internal AI audit:
- Map what tools your teams already use (many are using AI-powered features without realising it)
- Identify where your data lives and how clean it is, and
- Document the workflows where AI could reduce time or error
You can’t deploy responsibly or plan effectively without that baseline.
Build a working AI policy, not a perfect one
The clearest lesson from our report is that a document with no enforcement mechanism changes nothing. Countries that included ethics language in their strategies but attached no binding rules or accountability structures scored no better on governance than those that said nothing on ethics at all.
The same logic applies inside organisations. You don’t need a 40-page policy—you need a working one.
Define acceptable use cases, set data handling rules, clarify who approves AI-assisted decisions, and review it quarterly.
Something functional beats something aspirational every time.
Invest in training your people, not just in AI tools
According to PwC’s 2025 AI Jobs Barometer, revenue growth in AI-exposed industries has accelerated sharply since 2022, and workers with AI skills command a 56% wage premium over peers in the same role without them.
That premium flows to people who know how to use the tools well, not just to organisations that own a licence.
And AI training doesn’t mean a two-hour onboarding session; it means deliberate, role-specific investment in how your teams use AI to do their actual jobs.
| Training type | Who it’s for | What it produces |
| AI literacy | All staff | Confident, responsible day-to-day use |
| Tool-specific training | Function teams (marketing, finance, ops) | Faster output, fewer errors |
| Prompt and workflow design | Power users and team leads | Custom workflows, measurable time savings |
| AI governance training | Senior leaders and compliance teams | Smarter policy decisions, reduced risk |
Think now about an AI adoption specialist
A Botswana Stock Exchange-listed real estate investment firm recently advertised for an AI Transformation Lead. Botswana scored 3/24 on our AI Governance Maturity Index, which put it firmly in the early-stage category—and yet a private company there is already building internal capacity to manage AI adoption at a strategic level.
You don’t need to make this hire today, but you need to know what the role looks like, what it costs, and what problem it solves. The organisations that define that spec now will fill it faster when the moment arrives.
Watch your competitors and choose your AI partners carefully
If your competitors are ahead on AI, you’ll notice it in output speed, pricing, and product or service quality before you see it in any announcement they make.
Track what tools your sector is adopting, what roles companies like yours are advertising, and what partnerships they’re forming.
McKinsey’s 2025 State of AI research found that AI high performers are more than three times more likely to have senior leaders actively driving adoption across the organisation. That leadership lag compounds quickly.
On AI partners: not all AI implementation consultants, platform vendors, or AI training providers understand the African context. Prioritise those with local delivery experience, who understand your regulatory environment, and who can show you what they’ve built, not just what they’ve pitched.
If you want to explore what this looks like for your organisation, get in touch. I work with teams on the practical side of AI adoption—what to use, how to train for it, and where to start—with lived experience in six African countries over 30 years.