Bright Simons proposes $13m civil service AI assistant as alternative to Ghana’s $270m GhanaChat plan

Vice-President and head of Research at the IMANI Centre for Policy and Education, Bright Simons has proposed a cheaper alternative to Ghana’s planned US$270 million GhanaChat project, arguing that a sovereign artificial intelligence (AI) assistant for the civil service could be a more practical starting point for the country’s AI ambitions.

In a post on X, Mr Simons questioned the rationale for developing a national AI platform to compete with global services such as ChatGPT, Gemini and Claude when existing models could potentially support government operations at a lower cost.

1. Readers of this page know by now that JoyNews held a forum on Ghana’s AI strategy and prospects. And the Digital Minister and I got into a serious debate about his Ministry’s plan to build Ghana’s competitor to Gemini, Kimi, ChatGPT, Qwen, Claude, etc. 2. Ghana’s competitor to these global AI platforms is called GhanaChat. 3. It will be trained and hosted in a brand new AI datacenter. 4. 48 registries pooling data from across the public sector will make this AI smarter about Ghana than the foreign ones. 5. The AI datacenter and the "AI Fund" will cost about $270 million. Expect more to be spent on the registries and the apps. A lot of contracts. You can bet that a lot of ICT contractors are very happy. 6. The question is, if we have a couple of hundred million dollars to spend on making AI deliver great benefits for Ghana, should we spend it on GhanaChat, a top-tier AI data center, and the data-pooling system? And should we do it according to the strategy the Ministry has devised? 7. Or could we do much better by more critically assessing all our strategic options and comparing them to the Ministry’s? 8. My argument on the show was that I am not convinced about GhanaChat offering the best value for our money. 9. It would take many pages to explain my position fully. But in this post I will highlight just the most important points. 10. Attached are extracts from page 13, 50, and 68 of Ghana’s AI strategy. 11. If you have even the barest exposure to AI, you can see a massive error. Can you? 12. The target for how much computing capacity the country needs for next year (2027) is indicated as "1021 FLOPS" and the 2035 target as "1025 FLOPS". 13. If this was indeed correct, it would mean that the Ministry would like the entire computing capacity of the country in 2027 to be equivalent to a 1970s desktop computer. Or 2% of the capacity of the 1980 Intel math chip. 14. Howzat? 15. I’m sure you can agree that this would be totally ridiculous if that was the Ministry’s intent. So, what happened? 16. Somebody who didn’t fully understand how FLOPS work must have been involved in the drafting. What was meant to be 10 raised to the power 21 operations per second (10²¹ operations a second) was written out as "1021". Same for "1025". 17. Why wasn’t the error caught? Because in Ghana when doing "consultations", governments rarely engage independent and critical voices who will point out absurdities without fear of offending big men and women. 18. I am not being petty. There is a serious strategic confusion beyond mere typos. 19. Read properly as 10²¹ FLOPS, the Ministry is telling us that by next year it will have some 200,000 of Nvidia’s newest chips in use in Ghana, 500 MW of power devoted to AI, all costing about US$24 billion (close to the Ghanaian government’s entire programmed spending for 2026). 20. The US$250 million AI datacenter now being procured supplies about 1% of this 2027 target. 21. Howzat? 22. Clearly, no serious critique of the plan would have okayed such a vision. Throughout the ministry’s own review, cabinet approval, and a high-profile media launch, it is absolutely clear that not one critical reviewer was engaged. 23. My first major point here is that this is classic KATANOMICS: the lack of critical policy audiences. This is exactly how a sugar factory that was "designed from the start to fail" was allowed to be built. Many programs and initiatives in Ghana fail for precisely this absence of critical review. 24. In the strategy, you find statements like: "government aggressively building AI compute clusters" and by courting hyperscalers, "to leverage the scaling laws towards building general purpose AI and AGI". Then: "drastically increase Ghana’s energy capacity 0.5 to 1 OOM per year". "OOM" means "order of magnitude". 25. When I challenged the Minister on TV, he confidently rebutted by claiming that the Energy Minister/Ministry has assured him of feasibility. Ghana’s energy Ministry is committing to increase Ghana’s power output by 3x to 10x EVERY YEAR so that the Digital Minister can deliver his AI strategy? Did anyone in Cabinet not protest that this projection in 8 years would mean expanding Ghana’s electricity output by 10,000x? 26. I can bet you any amount that the Energy Minister will deny making any such commitments in Cabinet. Can we have clarity? Can JoyNews check? 27. Page 68 of the strategy defines an "Artificial General Intelligence Lab" as "an AI lab with access to more than 1010 compute". No unit is given at all. In fact, as written it is totally meaningless. What they likely mean is that Ghana will support the establishment of a lab with computing capacity of 10¹⁰ FLOPS (10 gigaFLOPS). 28. The problem is that such a lab would be totally useless. To give you perspective, an iPhone 7 has about 350 gigaFLOPS of capacity. 29. What would be required to meet the Ministry’s 2027 AI target? If for frontier model development, then the following spec would be reasonable: 400,000 16-bit Nvidia B300 GPU units, 1,114 MW of dedicated power (which is 26% of Ghana’s peak demand). And the budget could easily hit US$47.2bn. For less frontier use, we can halve these numbers. 30. Counted in the 64-bit arithmetic that scientific supercomputers are ranked by, Ghana’s 2027 target is 455 times the world’s fastest machine, China’s LineShine at 2.2 exaflops, and 53 times all 500 machines on the list combined. 31. Anyone with the barest exposure to Ghana’s fiscal context can tell the Minister for free that this won’t happen next year. 32. Ghana’s 2035 target of 10²⁵ is 160 times the entire global stock of AI compute today. Even if chips grow 1.4 times more energy-efficient every year, it would draw about 377 GW, 65 times Ghana’s current installed generating capacity. 33. I will be charitable and propose that the strategy’s drafters may have been thinking about training FLOP (note: without the "per second" at the end). For example, GPT-4’s training run used about 2.1×10²⁵ FLOP, the same order of magnitude as Ghana’s 2035 endpoint. 34. Unfortunately, that doesn’t save the strategy. Recast this way, the target collapses the other way. 10²¹ FLOP is about 12 days’ work for one H100 chip at 16-bit precision. 10²⁵ FLOP is one GPT-4-sized training run, which the US$250 million centre could finish in about four months. On that reading the centre meets the 2035 target before its first anniversary. Not meaningful. 35. Given how confusing the overall strategic plan is, would you bank on the first AI compute center and GhanaChat product already being procured at about $270 million? 36. Here are some bare numbers: the budget, per our modelling, maps to about 2,100 GPUs and 4.3 MW of IT load. That alone adds the equivalent of 90% of Ghana’s entire commercial data-centre load in 2024 (4.8 MW). Running it costs about US$76 million a year, which is about six times the revenue of the whole commercial industry. 37. A utilised GPU-hour costs about US$22 at base-case demand, against a market rate of US$6.71 today and roughly US$4.50 averaged over the hardware’s life. The base case thus implies a subsidy of about US$61 million a year. 38. If the concern is about Ministers and their Directors uploading sensitive documents into Gemini or Kimi, then why not a simpler sovereign AI assistant for the civil service first? 39. That would need roughly 144 GPUs: about 7×10¹⁷ operations a second at 8-bit, US$13 million up front and US$6.7 million a year. That is under a thousandth of the 2027 target, and a far more realistic initial-term strategy. Does Ghana really need to train its base model when orchestrators now allow one to host their own data and switch across multiple advanced open-weight models to serve an Assistant or Agentic system? 40. Howzat?

— Bright Simons (@BBSimons)

October 25, 2026

Mr Simons said if the government’s main concern was protecting sensitive public-sector information from being uploaded to external AI platforms, it could begin by developing a secure AI assistant for civil servants.

He estimated that such a system would require about 144 graphics processing units (GPUs), delivering approximately (7 \times 10^{17}) operations per second at eight-bit precision.

He put the initial cost at US$13 million, with annual operating expenses of about US$6.7 million.

“That is under a thousandth of the 2027 target, and a far more realistic initial-term strategy,” he wrote.

Mr Simons also questioned the need to train a foundational AI model from scratch, arguing that systems capable of coordinating multiple existing open-weight models could provide an alternative.

He suggested that such an approach could allow government institutions to retain control over their data while drawing on the capabilities of different AI models.

The government’s AI strategy includes plans to develop GhanaChat, a national platform intended to compete with international AI services.

The proposed system would be trained and hosted in a new AI data centre, with 48 public-sector registries expected to contribute data to improve its understanding of Ghanaian institutions and local needs.

The data centre and an accompanying AI Fund are estimated to cost about US$270 million, with additional expenditure expected for registries and related applications.

Mr Simons has questioned whether the proposed investment is justified, particularly given the cost of the infrastructure and the resources required to operate it.

Mr Simons also challenged the strategy’s computing capacity target for 2027, which he interpreted as (10^{21}) floating-point operations per second (FLOPS).

He estimated that meeting the target would require about 200,000 Nvidia chips, 500 megawatts of power and investment of approximately US$24 billion.

He said the US$250 million data centre being procured would provide only about one per cent of the stated target.

“Clearly, no serious critique of the plan would have okayed such a vision,” he wrote.

The estimates are Mr Simons’ assessment of the infrastructure needed to achieve the target. Their assumptions and the precise relationship between the target and the proposed data centre would require independent technical verification.

Mr Simons described the apparent shortcomings in the strategy as “classic KATANOMICS”, a term he uses to criticise projects that proceed without sufficient independent scrutiny.

He drew a comparison with a sugar factory he says was designed to fail, arguing that inadequate critical review has contributed to the failure of other government programmes.

“Throughout the Ministry’s own review, cabinet approval, and a high-profile media launch, it is absolutely clear that not one critical reviewer was engaged,” he wrote.