As Artificial Intelligence (AI) continues to transform the world of work, its impacts in the Global South present urgent and unique challenges. Unlike advanced economies with formal labour markets and stronger safety nets, many countries in the Global South face high levels of informality, limited social protection, and unequal access to skills and digital infrastructure.
These issues were explored at “Securing Labour Justice in the Age of AI: A Global South Policy Dialogue,” a pre-summit event held on 15 January 2026 in New Delhi as part of the lead-up to the India AI Impact Summit 2026. The dialogue was convened by JustJobs Network in collaboration with the IDRC-funded FutureWORKS Collective, with support from the International Development Research Centre (IDRC). Researchers and policy experts from Africa, Asia, and Latin America came together to discuss how AI is reshaping work in developing economies.
“Securing Labour Justice in the Age of AI: A Global South Policy Dialogue” panel discussion
Helani Galpaya, Chief Executive Officer of LIRNEasia, participated as a panelist in the discussion, sharing insights from ongoing research under the Future of Work Asia project. This initiative is part of the broader FutureWORKS Collective, where LIRNEasia is leading the development of a regional research network and currently supports 12 research projects. These projects examine the effects of technological change, climate change, and demographic shifts on the future of work and skills in Asia.
The panel also included Ali Abboud (Assistant Professor, American University of Beirut), Peter Quartey (Professor, University of Ghana), Ramiro Albrieu (Lecturer, University of Buenos Aires / Sur Futuro), and Ruth Castel-Branco (Senior Lecturer, University of the Witwatersrand), with the session moderated by Sabina Dewan, Founder and Executive Director of JustJobs Network.
Speaking on the panel, Helani noted that while South Asia appears, at an aggregate level, to be less exposed to AI-related job disruption, the World Bank’s South Asia Development Update 2025 highlights significant variation within the region. Countries such as India and Nepal are assessed as having relatively lower exposure, largely due to their substantial agricultural workforces and higher shares of lower-skilled occupations, which are assumed to be less immediately susceptible to AI substitution. In contrast, Bhutan and Sri Lanka show higher average levels of AI exposure, reflecting their comparatively more skilled occupational structures. However, she cautioned that “exposure” does not automatically translate into job loss, in many cases, AI may substitute specific tasks rather than eliminate entire roles. Furthermore, she noted that the method of calculating AI exposure is based on the assumption that the task composition of a job in Asia is the same as that of the same job in America or OECD countries. Therefore, the assumptions for such predictions are really questionable.
Helani also highlighted uneven patterns of value capture across the AI value chain. While South Asian countries, including India, Pakistan, Bangladesh, and Sri Lanka, have played important roles in cloud work and data labelling for AI systems, many of these lower-paid, gig-based roles are already being reshaped or rendered obsolete as automation advances. At the same time, higher-end roles in software engineering and AI model development remain integrated into global value chains, though even these may face gradual substitution pressures. Crucially, she stressed that the bulk of economic value generated by AI is likely to accrue to large multinational corporations that control core technologies, data infrastructures, and platforms, rather than to the dispersed workforce supporting AI systems. This raises important concerns around value capture, inequality, and the concentration of economic power. Given the global and interconnected nature of AI development, Helani points out the need for stronger international coordination and multilateral policy discussions to ensure more equitable governance outcomes.
Helani speaking on the panel about AI-related job exposure, value capture, and the implications for labour and economic equity in South Asia.
The broader dialogue also emphasized that as algorithmic systems increasingly influence access to work and livelihoods, they can reinforce existing inequalities, reflecting broader social, economic, and political structures rather than acting as purely technical tools. While routine and clerical jobs are declining, new AI-related opportunities remain largely accessible only to those with the right skills, digital access, and infrastructure.
The discussion underscored the importance of context-specific, inclusive policy approaches to ensure that AI supports decent work and labour justice, rather than widening existing inequalities.
For those interested, the full panel discussion can be viewed here:
