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What the AI divide covers
The phrase is broader than who has an internet connection. The International Telecommunication Union (ITU) treats the wider digital divide as spanning digital infrastructure, policy and regulation, affordability and skills. Its Connecting Humanity Action Blueprint page, dated September 2025, estimates that 2.6 billion people were offline in 2024. That is a global figure. It counts people without any connection, and it says nothing about how well connected people can use AI tools.
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ITU frames universal meaningful connectivity as a goal for 2030 and notes that the divide persists as AI arrives. The word “meaningful” carries the argument. A household with a mobile subscription that cannot sustain reliable service, a school with a connection but unstable power and few devices, or a ministry with no staff to assess vendor tools may all count as online while remaining largely unable to use AI. Policy attention therefore has to move from subscriber counts to the conditions that make use possible.
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Why the gap bites hardest in small and vulnerable states
The Secretariat’s report says small and other vulnerable Commonwealth states face a digital divide that can limit access to transformative technologies such as AI, add to their vulnerability, and constrain growth and competition. The report does not break that claim down country by country. The mechanisms below are the reasoning that links the documented access gaps to that conclusion. They are not measured outcomes.
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- Power and computing are fixed-cost inputs. Electricity supply, data infrastructure and computing capacity cost much the same to build whether a market is large or small. A small economy has fewer users over which to spread those costs.
- Institutions carry the policy load. Ministries and regulators need staff and usable data to assess AI tools. Where that capacity is thin, adoption tends to follow the terms set by outside vendors rather than national priorities.
- Skills pipelines are short. When few people are trained to build, procure or audit AI systems, that work goes to external providers, and much of the economic value they create sits outside the country.
The power constraint is stated directly by Paula Ingabire, Rwanda’s Minister of Information Communication Technology and Innovation. Her remark, reproduced in a Broadband Commission article from June 2024, is:
“The ability to harness artificial intelligence to revolutionize access to broadband and other services as well as boost productivity for different sectors will require massive investments in the building blocks including power, connectivity and computing resources, particularly in emerging economies.”
The Commonwealth response: the Artificial Intelligence Consortium
The Secretariat presents the CAIC as a support ecosystem for AI adoption in small states and vulnerable economies. Its work is organised into four working groups:
- Capacity building
- Policy development
- Research and innovation
- Data and infrastructure
The report names the following examples. They are activities reported for the July 2023–June 2024 period. The report summary does not say whether each one remains active, and it does not tie each activity to a specific working group.
| Activity | Partner named in the report | Description in the report |
|---|---|---|
| Commonwealth AI Academy | Not stated | Named as a CAIC activity; no further detail in the summary |
| StrategusAI | Not stated | AI-driven policy toolkit |
| AI policies report | Deloitte | Developed with the partner |
| Commonwealth AI Principles for Development Guide | Not stated | Guidance on principles for AI in development |
| AI research and talent development | CSIRO Australia | Research and talent work |
| AI incubator | OBREAL Global | Launched with the partner |
| Infrastructure work | NVIDIA and SAS | Infrastructure collaboration |
| Domain-specific training | Intel and Cleveland Clinic | Training in specialist fields |
The wider multilateral frame is the UN Pact for the Future, whose Objective 5.7 calls for capacity-building to bridge AI divides, improve access to AI applications, and develop high-performance computing and related skills in developing countries. It is policy context rather than a dated commitment with verified milestones, and the published material cited here does not establish progress against it.
Skills and inclusion
The Secretariat’s report links the initiative to the Commonwealth’s commitment to equip citizens, especially women, girls, young people and others facing inequality, with the skills to benefit from innovation, while supporting inclusive access. The published material cited here does not include enrolment or outcome data for CAIC training. The commitment is therefore a stated aim, not a measured result.
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A public-sector model: the ITU-UNESCO programme
UNESCO describes a joint ITU-UNESCO programme that makes learning on AI, digital policy and digital transformation available to public officials. It combines self-paced learning, national, regional and global training, institutional support and training-of-trainers. The programme page reports reach across 194 countries, more than 115,000 ITU Academy users, more than 50 schools of public administration and ITU Academy Training Centres, and 200 UNESCO National Commissions. These are reach figures. The page does not show course completion or measured impact, and the user count should not be read as either.
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Reading the numbers
Several figures circulate in discussions of the AI divide. Each has a specific scope, and none is a Commonwealth-specific measure of AI access.
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| Figure | Source and date | Scope | What it does not measure |
|---|---|---|---|
| 2.6 billion people offline in 2024 | ITU, Connecting Humanity Action Blueprint page, September 2025 | Global | Commonwealth access, or access to AI tools specifically |
| USD 2.6–2.8 trillion needed to close the global divide | ITU, same page | Global; includes demand-side considerations | An AI-only bill, or a Commonwealth funding requirement |
| Up to USD 15.7 trillion potential contribution to the global economy by 2030 | Commonwealth Secretariat, Annual Results Report 2023/24, which associates it with productivity and consumption-side effects | Global | A guaranteed outcome, or an independently verified Commonwealth forecast. The cited passage does not name the original source of the estimate. |
| 115,000+ ITU Academy users | ITU-UNESCO capacity-development programme page, accessed October 2026 | Programme reach | Course completion or learning impact |
Opportunity and risk
ITU Secretary-General Doreen Bogdan-Martin links the two sides of the issue: “Broadband is fundamental to ensure that everyone can benefit from digital technologies when so many people are still offline around the world,” and “AI and other emerging technologies can help efforts to achieve universal meaningful connectivity, and it’s our job to make sure this happens in a way that is responsible for people and the planet.” These remarks appear in the Broadband Commission’s June 2024 article.
That article identifies possible AI applications in government, education, healthcare and finance. It also names the risks: energy use, misinformation, bias and gender discrimination. Energy appears on both lists. It is among the building blocks that small grids lack and also among the risks that a larger AI footprint would raise. UNESCO Director-General Audrey Azoulay, quoted in the same article, put the governance point this way: “We must also address the risks faced by those online, through better governance of digital platforms, ethical use of AI and massive upscaling in digital skills, including media and information literacy.”
How to judge an initiative
The following five tests follow the focus areas in the sources. They help separate programmes that address the underlying gaps from those that address only one symptom. The sources support these tests but do not rank interventions or show which approach is most cost-effective.
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- Can people and institutions afford the tools and reach them in practice?
- Do education and skills programmes reach women, young people and underserved groups?
- Do local institutions have usable data, policy capacity and governance safeguards?
- Does the proposal measure outcomes and manage risks including energy use, misinformation, bias and discrimination?
What the evidence does not yet establish
The material available for this article does not provide a current, comparable measure of AI access, computing capacity, skills and adoption across Commonwealth countries. It also contains no causal estimate of the development gains that small states would gain from closing the gap. The Commonwealth case for action therefore rests on a reasoned policy argument: documented access inequalities, the Secretariat’s own description of the constraints small states face, and existing Commonwealth work such as the CAIC. It is not quantified proof that closing the gap will produce particular gains.
Within that limit, the argument is strong enough to act on. The gaps are documented, the Commonwealth has organised a response aimed at the states most exposed, and the global evidence shows that the solutions must cover power, affordability, regulation and skills together, not just network coverage.
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