You know how they say if something bothers you, it’s a problem waiting for you to solve? 12 months ago by this time, AI was bothering me. Not the field per se, but our continent’s seeming lack of preparation to embrace it. For the first time in my life I wished I had gone into politics.
In the absence of a political or ministerial portfolio that commanded a soap box of media attention on which I could stand to express my general discomfort at our seeming ill preparedness for this AI thing, I did the next best thing. I poured my thoughts onto paper. what was supposed to be rant became research and when I finally put my pen down, my result was an AI framework.
I published it on LinkedIn.
It got limited attention. But at least I felt like I’d done something.
Then last month, President Mahama launched Ghana’s National AI Strategy with impressive monetary committment: 250 million dollars committed to a national AI computing centre. 20 million for implementation. That’s a lot of oppippiis.
The conversation I was trying to start a year ago is now happening at the highest level in the country.
It gave me joy.
The global AI investment surge is a power story that’s forging strange alliances from UAE to China.
In 2024, total corporate AI investment worldwide reached approximately $252 billion. The US alone accounted for $109 billion of that. China, $9.3 billion – if anyone believes China’s probably underreported numbers.
Then there’s us. The entire African continent with all our 54 countries, 1.4 billion people, how many languages, every startup, every lab, every government initiative… attracted roughly 1% of global AI spending. One.
You have an active imagination if you can imagine Ghana’s slice of that.
Countries with the companies attracting AI investment are building (and controlling) the talent pipelines, the compute infrastructure, the regulatory direction, and the data ecosystems that make them more attractive to the next wave of investment. Everyone else is falling further behind with every passing quarter.
Consider talent. Data I refuse to believe states this country loses an estimated 600 data scientists every year to opportunities abroad. The total domestic expert pool sits below 1,000 full-time equivalents. I think that’s wildly optimistic.
The entire working AI professional base in a country of 33 million people – a country with Google’s first African AI centre, a country that just committed $270 million to an AI future – fits comfortably into the national theatre.
But in hindsight, my framework actually traced why. Follow the pipeline from the beginning: approximately 107,000 students enter Ghanaian universities every year. Most choose disciplines with no CS relevance. Those who study computer science, mathematics, or related fields, only make up about 2%. Then there’s the lure of greener pastures. Half of my own graduating class of Software engineers no longer lives here.
107,000 in. Under 1,000 out. Sorta adds up.
The standard response to this is: train more people. And yes, we need to train more people. But training people for opportunities that do not yet exist at home is not a talent strategy. It is an export strategy.
Now here’s something else the framework unearthed that I did not expect, which could change how we should be thinking about implementation entirely.
60% of AI’s potential economic benefit for Ghana sits in 5 sectors. Cocoa and agro-processing. Healthcare delivery. Financial services. Public sector efficiency. The creative economy.
Everything else is important eventually. But these five are where the returns are large enough, fast enough, and certain enough to justify serious early investment. Example, cocoa. We’re the world’s second largest (third now? Fourth? Creepy) cocoa producer. Computer vision and predictive disease modelling applied to the supply chain could raise effective yields by 8 – 12% and significantly reduce post-harvest losses, which across the agric value chain run as high as 30 – 50% depending on the crop and supply chain stage. Applied to Ghana’s cocoa export base, that is an additional GHS 2 billion in annual foreign exchange earnings by 2031. Not by planting more cocoa. By being smarter about the cocoa we already grow.
No new infrastructure required. Tangible results.
Question: how?
Answer: The financing gap is smaller than anyone is admitting.
Total public investment needed to pursue an accelerated AI adoption path across an eight-year roadmap: GHS 2.3 billion. That sums up to approximately 1.1% of projected public expenditure over the same period unless uncle Ato changes his mind. The projected fiscal return on that investment: GHS 36 billion in revenue gains alone. Before the GDP uplift. Before the export revenues. Before the jobs.
That is a 2.6 times fiscal return on public investment. In eight years.
Question: how??!
Answer: The framework proposes a specific financing architecture to get there: 40% from annual ICT budget reallocations, 30% from concessional loans through the World Bank and AfDB, 20% from public-private partnership and telco co-investment in sovereign compute infrastructure, and 10% from green and blue digital bonds. None of this requires us to find money we don’t have. It requires us to allocate money we’re already spending a bit differently… and to attract private and development capital through the governance credibility that a well-governed, publicly committed national strategy provides.
That national strategy now exists. Which means the investment case is stronger today than it was when I built this framework.
So where do we go from here? When I came up with this framework it was conjecture. Now it isn’t.
The framework modelled 3 scenarios for what happens between now and 2036.
The base path: business as usual – lots of talk, limited action, high policy friction, opposition walkouts, minimal coordinated investment, yup even with all that we could still squeeze a $2 billion GDP uplift and 15,000 net new digital jobs. AI only becomes a feature of Ghana’s economy rather than a driver of it.
The accelerated path: resetting like nobody’s business – serious execution, heads will roll type oversight, medium friction, $1.3 billion in coordinated public-private AI investment over 8 years… IF we can do that, it should produce a $10 billion GDP uplift and 45,000 net new digital jobs. That’s roughly 8% of Ghana’s entire economy today, generated by one thing, over one decade. Impressive.
The leapfrog path which we won’t discuss because LOL. Let’s not do that to ourselves.
Point remains, the country has just made the most significant technology commitment in its history and it’s ambitious in the right direction. But that ambition must be sequenced with institutional muscle and with ruthless focus. Otherwise it just produces noise rather than results. And for the first time in the history of the continent, none of us can risk noise on this matter otherwise we opt to be willing slaves to the West and East. Forever.
Next up, I’ll publish my full analysis of the National AI Strategy itself. What it gets right. Where the gaps are. And what the next twelve months need to look like if Ghana is going to find itself on the accelerated path rather than the base one.
The framework exists. The strategy now also exists.
Now let’s close the distance between them, so we can close the distance between where we are now and what an amazing future we can harness with AI.
To conclude, the most important take away from this, the main thought of this piece is, I’m sleeping better. That really is what I’m trying to say. And that’s what’s important for someone who published this blog post at 3:43 am.
Until next time,
Spyda