Artificial intelligence is developing faster than many countries can adapt to it. New AI systems are changing education, healthcare, business, scientific research, and public services, but access to the technology remains highly unequal. While some countries and companies are investing billions in advanced AI infrastructure, many developing countries are still working to strengthen basic digital connectivity, skills, data systems, and computing capacity.
That gap was at the center of a major message from United Nations Secretary-General António Guterres at the India AI Impact Summit in New Delhi in February 2026.
Speaking at the summit, Guterres called for the creation of a $3 billion Global Fund on AI to help developing countries build the basic capacity needed to participate in the AI economy. He argued that the future of artificial intelligence should not be controlled by a small group of countries or wealthy technology companies and that developing nations need access to the skills, data, computing power, and ecosystems required to benefit from the technology.
The proposal comes at a time when AI is becoming an increasingly important part of discussions about development, inequality, and the future of work.
Why Is a $3 Billion AI Fund Being Proposed?
The basic argument behind the proposal is that countries cannot benefit from AI if they do not have the infrastructure and skills needed to use it.
Artificial intelligence requires more than software. Countries need reliable electricity, internet connectivity, data infrastructure, skilled workers, computing resources, research institutions, and organizations capable of deploying AI responsibly.
For wealthier countries and technology companies, many of these resources already exist or can be developed through large investments. Developing countries can face much greater barriers.
Guterres warned that without investment, many countries risk being “logged out” of the AI age. He called for funding that would help developing countries strengthen skills, data capacity, affordable computing power, and inclusive AI ecosystems.
The proposed target is $3 billion.
Guterres argued that this would be a relatively small investment compared with the revenues of major technology companies, while potentially helping countries participate more meaningfully in the AI transformation.
AI Is Becoming a Development Issue
The discussion around AI is no longer limited to technology companies and computer scientists.
AI is increasingly being viewed as a development issue because it could influence some of the areas that international development organizations have been working on for decades.
According to Guterres, AI could help:
- Accelerate medical and scientific discoveries.
- Expand access to learning opportunities.
- Improve food security.
- Strengthen climate action and disaster preparedness.
- Improve access to essential public services.
- Support economic development.
- Help organizations deliver services more efficiently.
And these opportunities are particularly significant for developing countries, where artificial intelligence could provide a means to address some of the shortcomings experienced in fields including healthcare, education, agriculture, and public administration.
But access to the technology will matter.
If access to advanced AI is limited to nations and institutions with vast computing resources, access to high-quality data, and access to highly skilled technical staff, it may exacerbate existing inequalities.
The Global South Needs a Stronger Voice
The location of Guterres’ speech was significant.
The India AI Impact Summit was the first AI summit held in the Global South, according to the United Nations. Guterres said that meeting in India had particular importance because it brought the global AI discussion closer to the realities facing much of the world.
This matters because much of the world’s population lives in developing and emerging economies, yet many of the companies developing the most powerful AI systems are based in a relatively small number of countries.
There is therefore a growing concern that countries in Africa, Asia, Latin America, and other parts of the Global South could become primarily consumers of AI technologies developed elsewhere.
That could create a form of technological dependency.
Instead of developing local expertise and infrastructure, countries could end up relying on foreign companies for AI models, cloud infrastructure, data systems, and technical standards.
The issue has remained prominent throughout 2026. At the United Nations General Assembly in September, developing countries again called for a greater role in shaping global AI governance, warning that countries should not simply become users of technologies and standards designed elsewhere.
Skills Are One of the Biggest Gaps
One of the most important parts of the proposed fund would be investment in people.
AI systems may be powerful, but organizations still need people who understand how to use them, evaluate their results, and manage the risks involved.
Developing countries may face shortages of AI researchers, data specialists, engineers, cybersecurity professionals, and policymakers with technical expertise.
But the skills challenge goes beyond highly specialized technology jobs.
Teachers may need to understand AI-assisted education. Healthcare workers may need to understand AI-supported diagnostic tools. Government officials may need to evaluate AI systems used in public services. NGO workers may need to understand AI-assisted data analysis and fundraising tools.
This means AI capacity building needs to reach a much wider group of people.
A strong AI ecosystem cannot be built simply by purchasing computers or subscribing to AI platforms. Countries also need education, training, research institutions, and opportunities for local innovation.
Data Is Another Major Challenge
Guterres also highlighted data as an important part of AI capacity.
AI systems depend heavily on data. But countries and communities do not always have access to the high-quality datasets required to develop or evaluate AI systems effectively.
This creates several problems.
If local data is missing, AI systems may not perform well for local populations. Languages, cultural contexts, and social conditions can be underrepresented. Systems developed using data from one part of the world may not work equally well somewhere else.
For developing countries, building responsible data systems can therefore be just as important as obtaining computing power.
This is particularly relevant to NGOs.
Organizations working with communities often collect valuable information about health, education, livelihoods, climate vulnerability, and humanitarian needs. But using such data for AI requires strong safeguards around privacy, consent, and security.
The objective should not simply be to collect more data. It should be to develop responsible, secure, and locally relevant data ecosystems.
Affordable Computing Power Matters
Another major barrier is computing.
Training and operating advanced AI systems can require enormous computing resources. Even organizations that do not build large AI models may need affordable access to computing infrastructure to run applications, process datasets, or conduct research.
For many developing countries, expensive computing can become a major barrier to innovation.
This is why Guterres included affordable computing power among the areas that the proposed $3 billion fund should support.
Affordable infrastructure could allow universities, startups, governments, and nonprofits in developing countries to experiment with AI without having to depend entirely on large foreign technology companies.
That could encourage more locally developed solutions.
What Could This Mean for NGOs?
For NGOs, the proposed fund could have an important long-term implication.
Nonprofits are increasingly experimenting with AI for activities such as proposal writing, translation, data analysis, research, communications, fundraising, and service delivery.
But many smaller organizations face barriers similar to those identified by Guterres: limited budgets, lack of technical expertise, inadequate infrastructure, and concerns about data security.
A global AI capacity-building fund could potentially support the wider ecosystem that NGOs depend on.
For example, investment could help create:
- Training programs for nonprofit workers.
- Affordable access to computing infrastructure.
- Local-language AI tools.
- Responsible data systems.
- AI research partnerships with universities.
- Digital skills programs for community organizations.
- Technical support for small and grassroots NGOs.
- AI governance and accountability frameworks.
- Tools designed specifically for local development challenges.
This is important because the AI divide could otherwise become another barrier between large international organizations and smaller grassroots groups.
AI Should Support Human Development, Not Replace It
Guterres also emphasized the importance of workers in the transition to AI.
He called for investment in workers so that AI can augment human potential rather than simply replace people.
This is particularly important for the nonprofit and development sectors.
Many NGOs operate in environments where human relationships are central to their work. A health worker needs to understand a patient’s circumstances. A community organizer needs to build trust. A humanitarian worker may need to make decisions in unpredictable situations.
AI can assist with information, analysis, and repetitive tasks, but it cannot automatically replace the human relationships behind effective community work.
For NGOs, the more useful question may therefore be:
How can AI give workers more time and better information without removing the human judgment communities depend on?
That approach is very different from simply using AI to reduce staffing costs.
AI Can Also Increase Inequality
The UN Secretary-General’s message was not simply optimistic.
He also warned that AI can deepen inequality, amplify bias and cause harm if it is not developed and governed responsibly.
This is one of the central challenges facing the global AI debate.
AI can create opportunities, but the benefits are not automatically distributed equally.
A country with strong digital infrastructure can adopt new technologies much faster than one struggling with unreliable electricity or limited internet access.
A large company can hire AI specialists more easily than a small community organization.
A major university can afford advanced computing resources while a local research institution may struggle to access basic infrastructure.
Without deliberate investment, AI could therefore widen existing economic and technological gaps.
AI Governance Cannot Be Left to a Few Countries
Guterres also connected the funding proposal to the wider question of AI governance.
The UN has already taken steps to strengthen international cooperation around artificial intelligence. At the time of the India summit, Guterres highlighted the establishment of an Independent International Scientific Panel on AI, consisting of 40 experts from different regions and disciplines, as well as the launch of a Global Dialogue on AI Governance.
The goal is to create stronger international cooperation around AI rather than leaving every country to develop its own approach in isolation.
This becomes particularly important because AI systems operate across borders.
A model developed in one country can be used in another. Data can move across jurisdictions. AI-generated content can spread internationally within seconds.
Global problems therefore require some level of global cooperation.
The Energy and Environmental Cost of AI
There is another part of the AI conversation that is increasingly difficult to ignore: the environmental impact of AI infrastructure.
Large data centers require electricity and water, and the rapid expansion of AI is increasing demand for computing infrastructure.
Guterres warned that as AI’s energy and water demands grow, data centers and supply chains should move toward clean power rather than shifting environmental costs onto vulnerable communities.
This creates an important connection between AI and climate action.
If developing countries are expected to expand their AI infrastructure, they will also need to consider how that infrastructure affects energy systems, water resources and climate commitments.
For NGOs working on climate and development, this could become a new area of advocacy.
Why India Was an Important Location for the Message
India provided an important setting for this discussion because it has positioned itself as a major participant in the global AI ecosystem while also emphasizing the needs of the Global South.
At the India AI Impact Summit, Indian Prime Minister Narendra Modi described AI as something that should be democratized and used for inclusion and empowerment, particularly across the Global South.
India has also been developing its own AI infrastructure and policy initiatives.
This makes the country an important example of the wider question facing developing economies: how can countries participate in the AI revolution while ensuring that they retain meaningful control over how the technology is used?
The debate is not simply about catching up with wealthier countries.
It is also about ensuring that developing countries have the ability to shape the future of AI according to their own priorities.
The Risk of Becoming AI Consumers
One of the biggest concerns for developing countries is that they could become primarily consumers rather than creators of AI.
If countries depend entirely on foreign companies for models, cloud services, data infrastructure and technical standards, they may have limited influence over how those systems operate.
This could create long-term dependencies.
Developing local AI capacity does not mean that every country needs to build its own version of every major AI model. It can instead mean building enough expertise, infrastructure and institutional capacity to make informed decisions about technology.
Countries need to be able to ask:
- Does this AI system work for our population?
- Is the data representative?
- Who controls the data?
- Can we audit the system?
- What happens when it makes a mistake?
- Is the technology affordable?
- Can local organizations use it?
- Are workers being supported?
- Are communities being protected?
These are governance questions as much as technology questions.
Why Local and Community Organizations Matter
Inclusive ai is as much about local organizations as it is about how these tech giant organizations.
While nations and big tech might carve out national strategies, it’s not necessarily the governments or companies that reach the folks on the ground who are impacted by them.
A grass roots group might spot digital exclusion well before it makes its way into national stats.
A women’s group can look at whether an automated system has an adverse effect on women.
A disability-focused NGO may identify accessibility problems.
The youth organisation might have a good grasp on how young people really are using AI.
This diverse range of perspectives can help make the AI policies more workable and inclusive.
That’s part of why the overall movement toward community-led tech is becoming something the nonprofit industry should pay closer attention to.
A $3 Billion Fund Could Be More Than Technology Funding
If the proposed Global Fund on AI becomes a reality, its importance could extend beyond buying computers or supporting AI laboratories.
The real value could be in building long-term capacity.
That could include developing local institutions, strengthening education systems, training workers, supporting researchers, improving digital infrastructure and helping governments and civil society organizations develop responsible AI policies.
The fund could also help countries move from simply adopting foreign technologies to participating in AI development and governance.
For NGOs, this could mean a stronger ecosystem in which local organizations have access to technical expertise and infrastructure rather than relying entirely on international partners.
The Bigger Picture
The debate about Guterres’ proposal is just the tip of the iceberg about what the future of AI will be.
AI can bring speed, but disparity in access to it.
Certain nations are spending large amounts on computing power and AI research. Others are still struggling with fundamental digital and connectivity deficiencies.
If that gap persists, AI could be yet another tool that disproportionately enriches the haves to the detriment of the have-nots.
The United Nations’ suggestion thus builds on one simple premise: that the investment in AI capacity shouldn’t be restricted to the usual suspects already winning the tech race.
Developing countries need the opportunity to participate.
Conclusion: Making AI a Global Opportunity
Antnio Guterres calling for a $3 billion Global Fund on AI is the end goal: AI.
It’s a question of who will be involved in the next major tech revolution.
AI is too important to leave to the few or the wealthy. At the India AI Impact Summit the UN Secretary-General highlighted why developing countries need access to skills, data, computing power and ecosystems to harness AI.
A massive challenge AI is advancing rapidly and governments, organisations and communities are struggling to stay abreast of its growth. And it’s not a luxury countries can afford to disregard for the potential impact it has on healthcare, education, agriculture, climate adaptation, public services and economic prosperity.
For NGOs, the discussion is particularly important.
Not only technology companies will determine the future of AI. Governments, researchers, civil society, local communities and young people will all have a part to play.
Will they even have the resources and the opportunity?
A $3 billion fund isn’t the whole answer to the global AI divide. But it would send an important signal: let AI be one arena in which developing countries are not expected to play catch-up after the really big decisions have been taken.
If AI is really going to democratise these benefits, countries and communities will need more than access to the finished technology – they’ll need the skills, infrastructure, data, funding and voice to help decide what happens next.
That may be the biggest takeaway of the AI event in India: The future of artificial intelligence shouldn’t only be in the hands of those who make it. It should also be in the hands of the people and communities it will impact.
