The report, titled Mind the AI Divide: Shaping a Global Perspective on the Future of Work found that AI is revolutionizing industries worldwide, offering tremendous opportunities for innovation and productivity. However, it is also exacerbating economic and social inequalities due to uneven rates of investment, adoption, and use. This emerging “AI divide” means high-income nations disproportionately benefit from AI advancements, while low- and medium-income countries, particularly in Africa, lag behind.

The workplace is where Artificial Intelligence can lead to productivity gains and improved working conditions. Unequal access to infrastructure, technology, quality education, and training, however, could lead to uneven adoption of AI, which would, in turn, deepen inequalities globally.

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High-income countries are well-positioned to leverage AI for productivity gains, while developing countries could face bottlenecks due to a lack of digital infrastructure. This disparity could turn a temporary buffer against AI-driven changes into a long-term barrier to economic prosperity.

Global partnerships and pro-active strategies to support developing nations, including access to digital infrastructure, upskilling, and social dialogue, are necessary prerequisites to closing the technological gap and ensuring that the AI revolution doesn’t leave significant portions of the world’s population behind.

Annually, more than $300 billion is spent globally on technology to enhance computing capacity, but these investments are focused mainly on higher-income nations, creating a disparity in access to infrastructure and skills development that puts developing countries and their homegrown start-ups at a severe disadvantage.

In addition, without national tech industries, workers in developing nations who have the skills will offer their skills through freelance platforms, effectively building up companies in other countries, creating a virtual brain drain.

The report also notes that women, are most vulnerable to the automating effects of AI, particularly in clerical and business process outsourcing roles, such as call centers, prevalent in developing economies. However, the research suggests that while automation risks job displacement, it also offers potential for job augmentation, improving job quality and productivity.

The report proposed three policy pillars: strengthened international cooperation, building national capacity, and addressing AI in the world of work. This includes:

Enhancing Digital Infrastructure: Developing countries need robust digital infrastructure to support AI adoption. This includes access to electricity, broadband, and modern communication technologies.

Promoting Technology Transfer: High-income countries should assist in transferring AI technologies and knowledge to developing nations, fostering a collaborative environment for technological advancement.

Building AI Skills: Investment in education and training is crucial to equip the workforce with necessary AI skills. This will enable workers to adapt to and benefit from AI-driven changes.

Encouraging Social Dialogue: Effective integration of AI in workplaces requires social dialogue to ensure that technological advancements respect workers' rights and improve job quality.

The "Mind the AI Divide" report also calls on policymakers, industry leaders, and international organizations to work together in shaping a fair and inclusive AI-driven future.

The report, titled Mind the AI Divide: Shaping a Global Perspective on the Future of Work found that AI is revolutionizing industries worldwide, offering tremendous opportunities for innovation and productivity. However, it is also exacerbating economic and social inequalities due to uneven rates of investment, adoption, and use. This emerging “AI divide” means high-income nations disproportionately benefit from AI advancements, while low- and medium-income countries, particularly in Africa, lag behind.

The workplace is where Artificial Intelligence can lead to productivity gains and improved working conditions. Unequal access to infrastructure, technology, quality education, and training, however, could lead to uneven adoption of AI, which would, in turn, deepen inequalities globally.

High-income countries are well-positioned to leverage AI for productivity gains, while developing countries could face bottlenecks due to a lack of digital infrastructure. This disparity could turn a temporary buffer against AI-driven changes into a long-term barrier to economic prosperity.

Global partnerships and pro-active strategies to support developing nations, including access to digital infrastructure, upskilling, and social dialogue, are necessary prerequisites to closing the technological gap and ensuring that the AI revolution doesn’t leave significant portions of the world’s population behind.

Annually, more than $300 billion is spent globally on technology to enhance computing capacity, but these investments are focused mainly on higher-income nations, creating a disparity in access to infrastructure and skills development that puts developing countries and their homegrown start-ups at a severe disadvantage.

In addition, without national tech industries, workers in developing nations who have the skills will offer their skills through freelance platforms, effectively building up companies in other countries, creating a virtual brain drain.

The report also notes that women, are most vulnerable to the automating effects of AI, particularly in clerical and business process outsourcing roles, such as call centers, prevalent in developing economies. However, the research suggests that while automation risks job displacement, it also offers potential for job augmentation, improving job quality and productivity.

The report proposed three policy pillars: strengthened international cooperation, building national capacity, and addressing AI in the world of work. This includes:

Enhancing Digital Infrastructure: Developing countries need robust digital infrastructure to support AI adoption. This includes access to electricity, broadband, and modern communication technologies.

Promoting Technology Transfer: High-income countries should assist in transferring AI technologies and knowledge to developing nations, fostering a collaborative environment for technological advancement.

Building AI Skills: Investment in education and training is crucial to equip the workforce with necessary AI skills. This will enable workers to adapt to and benefit from AI-driven changes.

Encouraging Social Dialogue: Effective integration of AI in workplaces requires social dialogue to ensure that technological advancements respect workers' rights and improve job quality.

The "Mind the AI Divide" report also calls on policymakers, industry leaders, and international organizations to work together in shaping a fair and inclusive AI-driven future.

Social security institutions have taken significant steps toward integrating AI into their core operations, something that the ISSA has already focussed on in webinars, analysis articles and at the ICT 2024 conference. The report Artificial Intelligence in social security organizations sheds further light on the transformative potential of AI in social security.

AI has demonstrated its ability to increase capacity, enhance service delivery and support institutions in automating tasks to significantly improve administrative efficiency in social security institutions as part of an institutional data-driven strategy. By leveraging diverse and different types of data, AI can also allow organizations to create new business processes and provide value-added services to better reach and service people with adequate support. Since AI thrives on data, its integration into service and operations relies on high-quality information. It is therefore essential to ensure data availability and quality for effectively training AI systems.

The authors argue that staying updated on AI solutions and experimenting with their use will prepare institutions for future advancements. As the field of AI evolves, social security institutions must prioritize capacity building and adopt guidelines to navigate challenges. A seamless transition toward a data-centric digital landscape will position institutions to fully leverage AI solutions for their specific needs.