Strengthening AI Foundations: Emerging Opportunities for Developing Countries – World Bank Group

Report on AI Adoption and its Implications for Sustainable Development Goals

AI Momentum and its Potential for Economic Growth (SDG 8)

An analysis based on the World Bank’s Digital Progress and Trends Report 2025 indicates a significant increase in Artificial Intelligence (AI) adoption within developing nations, presenting opportunities to advance Sustainable Development Goal 8 (Decent Work and Economic Growth). Middle-income countries, including Brazil, India, Indonesia, and Viet Nam, are emerging as major users of Generative AI (GenAI), accounting for over 40% of global ChatGPT traffic in mid-2025. This trend is coupled with a nine-fold surge in GenAI-related job vacancies globally between 2021 and 2024, with one-fifth of these positions located in middle-income countries. These developments signal a strong potential for building skilled AI workforces and enhancing participation in the global digital economy.

The Digital Divide: A Challenge to Innovation and Inequality Reduction (SDG 9, SDG 10)

Despite progress, significant disparities persist, undermining SDG 9 (Industry, Innovation, and Infrastructure) and SDG 10 (Reduced Inequalities). The concentration of AI innovation remains heavily skewed towards high-income countries, which represent only 17% of the global population but account for:

• 87% of notable AI models
• 86% of AI start-ups
• 91% of venture capital funding

This innovation gap poses adaptation challenges for developing economies. However, the proliferation of open-source technologies offers a pathway to democratize AI, allowing countries to tailor solutions to local contexts. This collaborative approach aligns with the principles of SDG 17 (Partnerships for the Goals).

Localized AI Applications Advancing Health and Livelihoods (SDG 1, SDG 3)

Affordable and accessible “small AI” applications are delivering tangible impacts in developing economies, directly contributing to key SDGs. These tools, designed to operate on common devices without requiring extensive digital infrastructure, are enabling progress in critical areas. For example, they are helping doctors analyze health data, supporting SDG 3 (Good Health and Well-being), and allowing small businesses to access new markets, which promotes SDG 1 (No Poverty) and SDG 8 (Decent Work and Economic Growth). Such ground-up innovations empower countries to overcome traditional development barriers.

Foundational Pillars for Equitable AI Integration: The “Four Cs”

To ensure AI’s potential is realized equitably and contributes effectively to the Sustainable Development Goals, investment in four foundational pillars is critical. These “Four Cs” highlight the infrastructure and capacity gaps that must be addressed.

1. Connectivity: Reliable internet access is fundamental for AI participation. The disparity is stark, with 93% internet usage in high-income countries compared to only 54% in lower-middle-income and 27% in low-income countries. This gap is a major barrier to achieving SDG 9 and exacerbates inequalities targeted by SDG 10.
2. Compute: AI relies on significant computing resources. Middle- and low-income countries collectively hold only 23% of global co-location data center capacity, with low-income countries holding less than 0.1%. This severe infrastructure deficit under SDG 9 limits their ability to develop and deploy AI technologies.
3. Context: For AI to be effective, it must be relevant to local languages, data, and cultural realities. The current dominance of English-language training data presents a significant challenge. However, emerging formats like video and audio create new opportunities for developing countries to generate diverse, contextualized data.
4. Competency: AI readiness is contingent upon human capital. A profound skills gap exists, with less than 5% of the population in low-income countries possessing basic digital skills, versus 66% in high-income nations. Bridging this divide is essential for SDG 4 (Quality Education) and for preparing the workforce for the future of work under SDG 8.

Analysis of SDGs, Targets, and Indicators

1. Which SDGs are addressed or connected to the issues highlighted in the article?

   The article highlights several issues related to digital progress, artificial intelligence, and development disparities, which connect to the following Sustainable Development Goals (SDGs):

   • SDG 4: Quality Education – The article emphasizes the “Competency” gap, noting that digital literacy and advanced skills are crucial for AI readiness. It points out the stark difference in basic digital skills between low-income (less than 5%) and high-income countries (66%), directly linking to the goal of inclusive and equitable quality education and lifelong learning opportunities.
   • SDG 8: Decent Work and Economic Growth – The text discusses AI as a driver for growth opportunities, citing the nine-fold surge in GenAI job vacancies globally and the fact that one in five of these jobs are in middle-income countries. This connects to the goal of promoting sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all.
   • SDG 9: Industry, Innovation, and Infrastructure – This is a central theme. The article focuses on the foundational elements for AI, such as “Connectivity” (internet access) and “Compute” (data center capacity). It details the massive infrastructure gap, with high-income countries hosting 77% of global data center capacity while low-income countries have less than 0.1%. It also touches on the innovation gap, with 87% of notable AI models originating in high-income countries.
   • SDG 10: Reduced Inequalities – The core argument of the article is the uneven progress and widening gap between developing and developed nations in the AI sphere. It repeatedly contrasts high-income countries with middle- and low-income countries regarding AI innovation, funding, infrastructure, and skills, directly addressing the goal of reducing inequality within and among countries.

2. What specific targets under those SDGs can be identified based on the article’s content?

   Based on the article’s discussion, the following specific SDG targets can be identified:

   • Target 4.4 (under SDG 4): “By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship.” The article’s focus on the “Competency” pillar and the disparity in digital skills (66% in high-income vs.
   • Target 8.2 (under SDG 8): “Achieve higher levels of economic productivity through diversification, technological upgrading and innovation…” The article presents AI as a tool for driving growth and creating new job opportunities (e.g., GenAI vacancies), which aligns with this target of leveraging technology for economic productivity.
   • Target 9.b (under SDG 9): “Support domestic technology development, research and innovation in developing countries…” The article highlights the concentration of AI innovation (87% of models, 86% of start-ups) in high-income countries, implying a need to support this in developing nations. The mention of open-source technologies helping developing countries tailor solutions also connects to this target.
   • Target 9.c (under SDG 9): “Significantly increase access to information and communications technology and strive to provide universal and affordable access to the Internet in least developed countries.” The “Connectivity” pillar is a direct reference to this target, with the article providing specific data on the internet usage gap (93% in high-income vs. 27% in low-income countries).
   • Target 10.2 (under SDG 10): “By 2030, empower and promote the social, economic and political inclusion of all…” The article’s central theme of uneven progress and the digital divide in AI access, capacity, and innovation directly relates to the challenge of ensuring economic inclusion for developing countries in the global digital economy.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

   Yes, the article provides several quantitative data points that can serve as indicators to measure progress towards the identified targets:

   • For Target 4.4 (Skills): The “Percentage of the population with basic digital skills” is a direct indicator. The article provides a baseline: less than 5% in low-income countries versus 66% in high-income countries.
   • For Target 8.2 (Economic Growth): The “Growth rate of GenAI job vacancies” is an implied indicator of technological upgrading and its impact on the labor market. The article states it surged 9-fold from 2021-2024. Another indicator is the “Proportion of global GenAI jobs located in middle-income countries” (one in five).
   • For Target 9.b (Innovation): The article provides several indicators of the innovation gap:
     • Proportion of notable AI models by country income group (87% in high-income).
     • Proportion of AI start-ups by country income group (86% in high-income).
     • Proportion of venture capital funding for AI by country income group (91% in high-income).
   • For Target 9.c (Internet Access): The “Percentage of people using the internet” is a key indicator. The article gives figures by income level: 93% in high-income, 54% in lower-middle-income, and 27% in low-income countries.
   • For Target 10.2 (Inequality/Inclusion): The “Share of global co-location data center capacity” is a powerful indicator of the infrastructure inequality. The article breaks it down: 77% in high-income, 18% in upper-middle-income, 5% in lower-middle-income, and less than 0.1% in low-income countries.

4. Create a table with three columns titled ‘SDGs, Targets and Indicators” to present the findings from analyzing the article.

   SDGs	Targets	Indicators
   SDG 4: Quality Education	4.4: Increase the number of adults with relevant skills for employment.	Percentage of the population with basic digital skills (e.g.,
   SDG 8: Decent Work and Economic Growth	8.2: Achieve higher economic productivity through technological upgrading and innovation.	Growth rate of GenAI job vacancies (9-fold surge from 2021-2024); Proportion of global GenAI jobs in middle-income countries (one in five).
   SDG 9: Industry, Innovation, and Infrastructure	9.b: Support domestic technology development and innovation in developing countries.	Proportion of notable AI models, AI start-ups, and venture capital funding concentrated in high-income countries (87%, 86%, and 91% respectively).
   	9.c: Significantly increase access to the Internet in least developed countries.	Percentage of people using the internet by country income level (e.g., 27% in low-income vs. 93% in high-income countries).
   SDG 10: Reduced Inequalities	10.2: Empower and promote social and economic inclusion.	Share of global co-location data center capacity by country income level (e.g.,

Source: worldbank.org