Can Ghana Build Its Own AI Ecosystem? — The $250m Compute Centre, the $1bn UAE Hub, the $1.1bn MTN Bet, and the 85th Global Readiness Ranking That Exposes the Gap

Can Ghana Build Its Own AI Ecosystem? — Ghana has announced $250m for an AI computing centre, $1bn for a UAE innovation hub, and $1.1bn from MTN. But the country ranks 85th globally in AI readiness. Our deep‑dive analysis reveals the infrastructure, talent, regulation and ecosystem required — and three scenarios for Ghana’s AI future.

Executive Introduction

Can Ghana Build Its Own AI Ecosystem? — The $250m Compute Centre, the $1bn UAE Hub, the $1.1bn MTN Bet, and the 85th Global Readiness Ranking That Exposes the Gap

The money has been committed. The strategy has been launched. The speeches have been made. In the first half of 2026 alone, Ghana announced a $250 million national AI computing centre, a $1 billion strategic partnership with the United Arab Emirates to build Africa’s largest integrated innovation and AI hub, and a $1.1 billion investment from MTN Group to accelerate AI‑ready digital infrastructure, large‑scale data centre development, and 4G and 5G expansion. The National AI Strategy, launched on 24 April 2026, projects that AI will contribute 500 billion Ghanaian cedis (approximately $45 billion) to GDP by 2035 and envisions a national AI ecosystem that expands literacy and access, strengthens jobs and entrepreneurship, supports local innovation, and improves the performance of the public service.

Yet the distance between this ambition and the country’s current positioning is sobering. In the 2025 Oxford Insights Government AI Readiness Index, Ghana ranked 85th out of 188 countries globally, behind Kenya (65th), South Africa (67th), Mauritius (71st), Nigeria (72nd), and Rwanda (75th). Ghana remains in the “emerging” category of the African AI Governance Index. The country’s overall AI adoption rate among businesses stands at only 9.3 per cent, with less than 5 per cent of small and medium enterprises using sophisticated technologies such as AI and the Internet of Things. Most tellingly, a study exploring generative AI tool use among university students in Ghana found that male students used these tools more frequently than their female counterparts, a statistically significant difference that highlights an emerging gender gap in AI literacy at precisely the moment when foundational skills are being built.

This profile examines whether Ghana can build its own AI ecosystem. It analyses the four essential pillars — compute infrastructure, talent pipeline, regulatory framework and ecosystem maturity — and weighs the undeniable progress against the persistent gaps. The funding is unprecedented. The political will is evident. The private sector is mobilising. But building an AI ecosystem is not a function of announcements. It is a function of execution, integration and trust. The strategy is launched. The compute centre is coming. Now comes the hard part. This is an honest assessment of what Ghana has, what it still needs, and whether the country can close the gap between ambition and reality before the window of opportunity closes.

The Hard Infrastructure: Compute, Connectivity and Power

No AI ecosystem can grow without compute — the raw processing power required to train and run machine learning models. Ghana’s government has recognised this with unusual clarity.

The centrepiece is the proposed $250 million national AI computing centre, announced by President John Dramani Mahama at the launch of the National AI Strategy on 24 April 2026. The facility, which the President described as the “nerve centre for research, innovation and enterprise”, is intended to serve as the backbone of the country’s AI development, allowing Ghanaian experts to create solutions for both the local market and the wider African continent. An additional $20 million has been allocated for short‑ to medium‑term strategy implementation. The National AI Fund will launch with GH¢5 billion in seed capital from 2025 to 2030, scaling to GH¢15 billion by 2035.

The government is also investing a further $20 million for short-to-medium term implementation of the AI strategy. However, the operational timeline of the computing centre remains unclear, and experts have warned that without clear procurement principles and public‑private partnership models, the centre risks becoming a symbolic achievement rather than a functional asset. Data centre development requires three preconditions to be met: a reliable power supply, adequate land availability, and efficient cooling infrastructure. Without these inputs, large‑scale investment in compute infrastructure would carry unacceptable operational risk. The government has acknowledged this explicitly. President Mahama has compared digital infrastructure to roads, railways and power systems that supported development in the past, stating, “Data, computing power, connectivity, and energy are now as important to the digital age”. But acknowledging the need for reliable power is not the same as delivering it.

On connectivity, the picture is mixed. The government has mandated that telecom operators increase data bundle values without raising prices, but the underlying structural barriers — the near‑39 per cent tax burden on telecommunications services, the lack of a dedicated electricity tariff for telecom towers, and the slow rollout of fibre — remain largely unaddressed. The cost of 1GB of mobile data ranges from approximately $0.05 to $1.50, depending on the provider and bundle. While this compares favourably to many peers, affordability for low‑income households remains a significant barrier. If connectivity remains too expensive for the majority of Ghanaian businesses and households, AI adoption will be concentrated among large corporations and affluent urban consumers, and the ecosystem will never achieve the scale required for genuine transformation.

The Soft Infrastructure: Talent and the One Million Coders Question

The second pillar of any AI ecosystem is talent. Ghana’s flagship initiative, the One Million Coders Programme (OMCP) , aims to train one million Ghanaians in practical digital and AI skills at scale, with 300,000 targeted for training in 2026 alone.

The rollout is genuine and tangible. In May 2026, the government delivered 8,500 laptops to training centres nationwide as part of efforts to improve access to digital skills. The Minister for Communication announced that the OMCP represented a GH¢15 billion commitment over four years. The Minister revealed that 50 digital hubs are being established nationwide to support AI and digital skills training. Ground‑level implementation has reached communities beyond Accra: the programme officially commenced at Mepe in the North Tongu District on 18 May 2026, with laptops configured and deployed to facilitate training sessions. The District Chief Executive for North Tongu described the programme as a strategic investment in youth development and digital transformation.

However, critics have raised serious concerns. A participant of the OMCP publicly expressed disappointment over the structure and delivery of the programme, sparking widespread discussions online. Policy analyst Franklin Cudjoe of IMANI Africa has warned that many of the skills promoted under programmes such as coding can be easily learned online and should not be treated as standalone flagship policies unless they are closely linked to industry demand and employment opportunities. The programme trains entry‑level digital skills, but the gap between that training and the advanced AI talent required for high‑value roles — data scientists, machine learning engineers, AI researchers — remains wide. Without a clear pathway from training to employment, Ghana risks training thousands of coders who cannot find coding jobs.

The employment context is sobering. Over 506,000 Ghanaians applied for fewer than 5,000 public sector positions. The country’s security services collectively employ fewer than 100,000 personnel, with their combined wage bill already nearing GH¢13 billion — highlighting the fiscal limits of relying on public sector recruitment to absorb large numbers of job seekers. Dr Bryan Acheampong, Member of Parliament for Abetifi, has called for a comprehensive National Skills Plan for the AI Transition, developed through coordinated efforts involving the Ministry of Education, Youth Employment Agency and private sector partners. Without such a plan, the OMCP risks becoming a political talking point rather than a genuine talent pipeline.

The Regulatory Backbone: The Bank of Ghana and the Emerging Technologies Bill

The third pillar of an AI ecosystem is a regulatory framework that balances innovation with accountability. Here, Ghana has made concrete and measurable progress.

The Bank of Ghana has emerged as an early and active regulator of AI in financial services. In March 2026, the central bank launched the revised Cyber and Information Security Directive (CISD 2026) , which introduces new governance standards for artificial intelligence and machine learning systems used in fraud detection and credit scoring, aimed at ensuring transparency and security in automated decision‑making. The directive extends regulatory coverage beyond banks to include fintechs, microfinance institutions and other financial sector players, shifting toward a system‑wide approach to managing cyber risk. It also sets stricter conditions for cloud adoption, limiting the hosting of sensitive financial data outside Ghana in line with data sovereignty requirements.

The CISD 2026 introduces a proportionality framework that scales compliance requirements based on the size and risk profile of institutions, alongside a new mandate requiring at least one board member to have verifiable expertise in cyber risk management. This is intended to elevate cybersecurity from a technical function to a strategic governance issue. Governor Dr Johnson Pandit Asiama described the directive as a deliberate shift in the scope of central bank supervision. “We are no longer just supervising capital adequacy ratios or liquidity positions of financial institutions,” he said. We are now, more than ever, safeguarding the confidentiality, the integrity and the availability of the data that powers our economy.

The central bank has also established specialised departments on artificial intelligence, data analytics and virtual assets to strengthen oversight of Ghana’s evolving financial sector. The governor disclosed that the central bank was currently considering a dedicated regulatory framework specifically for fintech companies to improve supervision and allow specialised oversight. “We noticed that there was little going on by way of artificial intelligence, data analytics and what have you, and so we decided to set up a department quickly to learn,” Dr Asiama said.

At the national level, the Ministry of Communication is working on an Emerging Technologies Bill, which will provide the legal framework for the deployment of AI, robotics, blockchain and related technologies. The Bill proposes the creation of an Emerging Technologies Agency, which would include an Artificial Intelligence Division, and aims to provide legal certainty for AI developers, investors and users. The government has also established a Responsible Artificial Intelligence Office to oversee the implementation of the AI strategy.

Despite this progress, experts have identified critical gaps. The strategy references a Responsible AI Authority, a Responsible AI Office and a National AI Office without clearly defining their respective mandates or how they would relate to one another. The strategy stops short of specifying a regulatory model, leaving open whether Ghana will adopt a risk‑based framework similar to the EU, a sector‑led approach like the UK, a state‑coordinated model comparable to China, or sandbox‑driven regulation as practised in Singapore. Without a clear regulatory model, AI developers and investors face legal uncertainty that could deter the very innovation the strategy seeks to encourage.

The Ecosystem: Startups, Investment and the Missing Middle

The fourth pillar of an AI ecosystem is the startup community that translates infrastructure and talent into products and services. Here, Ghana has genuine momentum but also a significant concentration problem.

What was once a small cluster of ambitious startups in Accra has grown into a rapidly expanding digital economy powered by fintech, artificial intelligence, agritech, e‑commerce, logistics technology, and digital infrastructure. Ghanaian AI startup Aya Data secured $900,000 in seed funding in January 2026 to advance its mission, including the enhancement of AyaGrow, an AI‑powered tool designed to assist both smallholder and commercial farmers. Google has opened its first AI Community Centre in Accra, committed $37 million to AI development across Africa, and signed an MoU with the Ministry of Education to integrate AI‑driven learning tools into Ghana’s schools.

Private sector capital is also flowing. MTN Group is actively seeking public and private partners to co‑develop large‑scale data centres in Ghana, describing the push as a natural extension of the telecom giant’s continental digital infrastructure strategy. The fresh capital injection echoes a similar pledge made in 2022, when MTN committed to invest more than US$1 billion over five years to modernise infrastructure. This time, the focus extends further into AI and cloud computing, with the development of hyperscale data centres intended to position Ghana as a competitive digital hub in West Africa.

Yet the ecosystem is heavily skewed toward the financial services and telecom sectors, reflecting the country’s historical strengths. Less than 5 per cent of SMEs are using AI. The startups that exist are concentrated in Accra. The agricultural sector, which employs the majority of Ghana’s workforce, remains under‑served. The informal sector, which accounts for more than 80 per cent of the economy, is almost entirely untouched by AI. The venture capital community is still nascent, with only a handful of Ghanaian AI startups attracting international funding. The ecosystem has a top, but it does not yet have a middle or a bottom.

The Implementation Gap: Strategy Without Execution Architecture

Despite the unprecedented funding and the genuine policy progress, experts have identified significant implementation gaps that could undermine Ghana’s AI ambitions.

Hector Dotse, a cybersecurity analyst, identified three major decisions that remain deferred. The strategy sets an ambitious target for private investment but does not outline the instruments required to mobilise that capital. It also stops short of specifying a regulatory model, leaving open whether Ghana will adopt a risk‑based framework similar to the EU, a sector‑led approach like the UK, a state‑coordinated model comparable to China, or sandbox‑driven regulation as practised in Singapore. Additionally, Dotse noted the absence of procurement principles ahead of major infrastructure commitments, including the planned national AI compute centre. Desmond Israel, founder and lead consultant at Information Security Architects Ltd, identified what he described as a mechanical revision of an earlier policy framework, pointing to sections of the strategy that retain language referencing a 2033 endpoint, consistent with a previous 2023 to 2033 draft, despite the document being positioned as a fresh ten‑year roadmap through 2035. “National strategies are built around timelines. If those timelines are inconsistent within the same document, it weakens confidence in execution planning,” he said.

On governance, Israel raised concerns about the strategy’s institutional architecture. The document references a Responsible AI Authority, a Responsible AI Office, and a National AI Office without defining their respective mandates or how they would relate to one another. “AI policy is governance infrastructure, not branding. Without clearly defined institutions, implementation risks becoming fragmented”. Abdul‑Mumin Sofo Yumzaa, Executive Director of Simba Ghana, raised concerns over Ghana’s preparedness to effectively implement the strategy. He concluded that the issue was not capability but the pace at which public institutions are adapting to innovation. He contrasted Ghana’s progress with countries such as Rwanda and Senegal, which adopted national AI frameworks earlier and had since integrated the technology into their broader development agenda.

The central challenge, as Dotse concluded, is that “none of these requires reopening the strategy. All of them require follow‑on documents in the coming months”. The principal risk is not outright failure but gradual misalignment between the strategy’s ambitions and its implementation architecture.

The International Dimension: Competition and Partnership

Ghana’s AI ambitions cannot be understood in isolation. Across the continent, countries are racing to position themselves as AI hubs.

South Africa leads the continent in AI readiness, with established research institutions, a vibrant startup ecosystem, and significant corporate investment. Rwanda has leveraged its national AI framework to integrate technology into its broader development agenda, becoming a magnet for international tech investment. Senegal is emerging as a Francophone AI hub, with support from international partners. Nigeria, despite its infrastructure challenges, has a thriving AI startup ecosystem concentrated in Lagos, attracting the majority of West African AI venture capital.

Ghana’s unique advantage lies in its combination of political stability, English‑language proficiency, relatively advanced digital infrastructure, and a regulatory environment that has been consistently ranked as the best in Africa for mobile money. The country’s partnership with the UAE, which includes a $100m Ghana Startup Fund backed by ADQ and Chimera Capital, a $75m Ghana–UAE AI and Web3 campus supported by the Dubai Future Foundation, and the ambition to attract and scale up to 100 AI startups by 2030, is a genuine differentiator. The hub is designed to attract multinational technology companies such as Microsoft, Meta, Oracle, IBM and Alphabet while strengthening local enterprise capacity and skills development. The agreement reflects a broader shift towards long‑term, infrastructure‑led technology investment in Africa. For Ghana, the project reinforces its ambition to position itself as a regional digital and innovation hub, while creating employment opportunities and supporting skills transfer.

But competition is intensifying. Rwanda has already signed similar partnership agreements. South Africa’s established tech ecosystem cannot be overtaken in a single investment cycle. Ghana’s window of opportunity is open, but it is not infinite. The country that builds a functional AI ecosystem first will attract the talent, capital and partnerships that will define the continent’s AI landscape for the next decade. Ghana has made a credible start. But it has not yet won the race.

The Gender and Inclusion Gaps

A genuine AI ecosystem must be inclusive. By that measure, Ghana’s AI ambitions face significant headwinds.

A study exploring generative AI tool use among university students in Ghana found that male students used these tools more frequently than their female counterparts, and this difference was statistically significant. At the very moment when foundational AI literacy is being built, a gender gap is already emerging. If this trend continues, women will be systematically excluded from the AI economy before it even takes off.

The AI ecosystem is also heavily skewed toward Accra. The startups, the investment, the trained talent and the commercial applications are concentrated in the capital. Rural communities, which constitute the majority of the country’s population, are almost entirely untouched by the AI revolution. The informal sector, which accounts for more than 80 per cent of Ghana’s economy, is not being reached. A national AI ecosystem cannot be an Accra AI ecosystem. If the benefits of AI are not distributed across the country, the technology will exacerbate the very inequalities it promises to reduce.

The National AI Strategy includes provisions for inclusive access, and the government has stated that “the informal sector and persons with disabilities are not excluded from the technological process”. President Mahama has emphasised that the adoption of AI would follow a human‑centred, inclusive approach, where AI would “enhance human capability and not diminish human dignity”. But these are aspirations, not implementation plans. The distance between the rhetoric and the reality of inclusion remains wide.

Future Outlook — Three Scenarios for Ghana’s AI Ecosystem

The trajectory of Ghana’s AI ecosystem will be shaped by three variables: the pace of computing centre deployment, the effectiveness of talent development, and the quality of regulatory implementation.

Scenario One — Gradual, Concentrated Ecosystem (65 per cent probability).

In this base case, the computing centre becomes operational by 2028 but serves primarily research institutions and large corporations. The One Million Coders Programme produces entry‑level graduates but lacks the advanced training needed for high‑value AI roles. The UAE innovation hub is built but takes time to attract tenants. AI adoption remains concentrated in Accra, in the financial services and telecom sectors, and among large enterprises. SMEs and the informal sector remain largely untouched. Ghana’s AI readiness ranking improves to the top 50 globally, but the country does not achieve its ambition of becoming West Africa’s leading AI hub by 2035. AI contributes GH¢150‑200 billion to GDP by 2035 — significant, but well below the GH¢500 billion target.

Scenario Two — Accelerated Ecosystem Breakthrough (25 per cent probability).

The computing centre is operational by 2027 and attracts foreign investment. The One Million Coders Programme is reformed to focus on job‑ready skills with clear placement pathways. The National Skills Plan for the AI Transition is implemented effectively. The UAE innovation hub attracts anchor tenants — Microsoft, Meta, Oracle — creating a genuine cluster of AI activity. The BoG’s open banking framework enables fintechs to access bank data, unlocking a wave of AI‑powered financial innovation. Ghana’s AI readiness ranking rises to the top 30 globally. AI contributes GH¢350‑450 billion to GDP by 2035, approaching the government’s target. Ghana becomes a recognised regional leader in AI development.

Scenario Three — Stagnation and Fragmentation (10 per cent probability).

The computing centre faces technical and financial challenges, and its operational timeline slips. The One Million Coders Programme produces graduates who cannot find AI jobs. The UAE hub is built but fails to attract anchor tenants. The gap between Accra and the rest of the country widens. The gender gap in AI literacy deepens. Regulatory fragmentation persists. Ghana’s AI readiness ranking stagnates, and the country falls behind Rwanda, Nigeria and Kenya. The GH¢500 billion target is never achieved. This scenario is the low‑probability, high‑impact risk that keeps policymakers focused on execution.

The most likely path is Scenario One: gradual, concentrated ecosystem development, with AI transforming the largest enterprises but leaving SMEs and the informal sector largely untouched. The GH¢500 billion target is not impossible, but it is improbable without sustained, coordinated action across compute, talent, regulation and ecosystem development.

Conclusion

Ghana has made a credible start. The $250 million computing centre, the $1 billion UAE innovation hub, and the $1.1 billion MTN investment represent the largest coordinated push for AI infrastructure in West African history. The Bank of Ghana’s CISD 2026 and the creation of dedicated AI and fintech departments demonstrate that the regulator is not waiting for innovation to happen; it is actively shaping the conditions for it. The One Million Coders Programme, despite its flaws, is putting digital skills into communities that have never had access to them. The strategy is launched. The institutions are being built. The capital is flowing.

But a credible start is not the same as a functional ecosystem. Ghana ranks 85th in global AI readiness. Less than 5 per cent of SMEs are using AI. The gender gap in AI literacy is already statistically significant at the university level. The computing centre is announced but not yet operational. The regulatory model for AI is not yet specified. The talent pipeline produces entry‑level coders, not advanced AI engineers. The gap between the GH¢500 billion target and the current reality is vast.

Can Ghana build its own AI ecosystem? The answer is yes — but only if it closes the gap between ambition and execution. The strategy is not the problem. The institutions are being built. The funding is unprecedented. The missing ingredient is not infrastructure or capital. It is the sustained, coordinated, cross‑sectoral implementation that turns announcements into assets, training into employment, and investment into inclusion.

The algorithm is not coming. It is already here. The question is whether Ghana will build an AI ecosystem that serves all its citizens — or whether it will build one that serves a few, leaving the majority behind. The funding is flowing. The institutions are rising. Now comes the hard part.

Frequently Asked Questions (FAQ)

Q1: Can Ghana realistically build its own AI ecosystem?

Yes, but only if it closes the gap between ambition and execution. Ghana has unprecedented funding — $250 million for a computing centre, $1 billion for a UAE innovation hub, $1.1 billion from MTN — and a clear National AI Strategy. However, the country ranks 85th globally in AI readiness, less than 5 per cent of SMEs use AI, and key implementation decisions — procurement principles for the computing centre, a clear regulatory model, and a coordinated skills plan — remain unresolved.

Q2: How much is Ghana investing in AI infrastructure?

The government is investing $250 million for a national AI computing centre and $20 million for strategy implementation. The UAE partnership adds $1 billion for an integrated innovation and AI hub in Ningo‑Prampram. MTN Group is committing $1.1 billion over three years for network expansion, AI‑ready data centres, and digital skills development. A five‑year National AI Fund will launch with GH¢5 billion from 2025 to 2030, scaling to GH¢15 billion by 2035.

Q3: What is Ghana’s National AI Strategy?

Launched on 24 April 2026, the strategy spans 2025‑2035 and projects that AI will contribute GH¢500 billion (approximately $45 billion) to GDP by 2035. It is built around eight pillars: AI education, youth employment, digital infrastructure, data governance, ecosystem development, sectoral AI adoption, applied research, and ethical AI governance. A Responsible AI Office has been established to oversee implementation.

Q4: What is the $1 billion UAE AI innovation hub?

Ghana and the UAE signed a $1 billion strategic partnership in December 2025 to develop Africa’s largest integrated innovation and AI hub in Ningo‑Prampram, Greater Accra Region. The investment includes $180m for an AI Compute Hub (G42), $100m for a national AI‑powered digital identity system, $120m for a Ghana AI Startup Studio to scale up to 100 AI startups by 2030, and $350m for 5G deployment and a Tier IV data centre.

Q5: What is the One Million Coders Programme?

The OMCP aims to train one million Ghanaians in practical digital and AI skills at scale, with 300,000 targeted for 2026 alone. The programme represents a GH¢15 billion commitment over four years. Fifty digital hubs are being established nationwide. In May 2026, the government delivered 8,500 laptops to training centres nationwide. However, critics have raised concerns about programme structure, job placement pathways, and the lack of advanced AI training for high‑value roles.

Q6: How is the Bank of Ghana regulating AI in financial services?

The BoG launched the revised Cyber and Information Security Directive (CISD 2026) in March 2026, which introduces new governance standards for artificial intelligence and machine learning systems used in fraud detection and credit scoring, aimed at ensuring transparency and security in automated decision‑making. The central bank has also established dedicated departments for artificial intelligence, data analytics and virtual assets and is considering a dedicated regulatory framework for fintech companies.

Q7: How does Ghana’s AI readiness compare to other African countries?

Ghana ranks 85th out of 188 countries globally in the Oxford Insights Government AI Readiness Index, behind Kenya (65th), South Africa (67th), Mauritius (71st), Nigeria (72nd), and Rwanda (75th). In the Global AI Index measuring investment, innovation and implementation, Ghana ranks 61st, with low scores in development, research, talent, and infrastructure. Ghana remains in the “emerging” category of the African AI Governance Index.

Q8: What are the biggest barriers to Ghana building its own AI ecosystem?

The five most significant barriers are: infrastructure gaps (the computing centre is announced but not yet operational; power reliability remains a challenge), talent shortages (the One Million Coders programme produces entry‑level coders, not advanced AI engineers), regulatory uncertainty (the regulatory model for AI is not yet specified), the implementation gap (key decisions on procurement, capital mobilisation and institutional mandates remain unresolved), and the inclusion gap (the ecosystem is concentrated in Accra; the gender gap in AI literacy is already statistically significant).

Q9: How much of Ghana’s SME sector is using AI?

Less than 5 per cent of Ghanaian small and medium enterprises surveyed are using sophisticated technologies such as AI and the Internet of Things (IoTs). The majority of businesses have adopted less sophisticated technologies such as social media and mobile banking, but adoption of advanced AI remains negligible outside large corporations.

Q10: What is the Emerging Technologies Bill?

The Ministry of Communication is working on an Emerging Technologies Bill, which will provide the legal framework for the deployment of AI, robotics, blockchain and related technologies. The Bill proposes the creation of an Emerging Technologies Agency, which would include an Artificial Intelligence Division, and aims to provide legal certainty for AI developers, investors and users.

Q11: What is the gender gap in AI literacy in Ghana?

A study exploring generative AI tool use among university students in Ghana found that male students used these tools more frequently than their female counterparts, and this difference was statistically significant. At the very moment when foundational AI literacy is being built, a gender gap is already emerging. If this trend continues, women will be systematically excluded from the AI economy.

Q12: What is the future outlook for Ghana’s AI ecosystem?

The most likely scenario is gradual, concentrated ecosystem development. The computing centre will become operational by 2028 but will serve primarily research institutions and large corporations. AI adoption will remain concentrated in Accra, in the financial services and telecom sectors, and among large enterprises. SMEs and the informal sector will remain largely untouched. AI will contribute GH¢150‑200 billion to GDP by 2035 — significant, but well below the GH¢500 billion target. A genuine breakthrough would require the computing centre to be operational by 2027, the OMCP to be reformed to focus on job‑ready advanced skills, and the UAE hub to attract anchor tenants such as Microsoft and Meta.

Esther Aku-Sika

Esther Aku-Sika is a content writer and social media strategist who helps brands and startups grow through intentional storytelling and practical marketing strategies. With a keen eye for trends and audience behavior, she shares business insights, content strategies, and real-life lessons to help entrepreneurs build visibility and turn ideas into income. Through her writing, she simplifies complex concepts and equips readers with actionable steps to grow in today’s digital space.