These questions are not theoretical. The World Economic Forum’s Future of Jobs Report 2023 forecasts that 83 million jobs could be lost globally by 2027 due to AI, automation, and digital platforms. Although 69 million new roles are expected to emerge, the result is a net loss of 14 million jobs, or approximately 2% of the current global workforce. This shift is neither linear nor evenly distributed—it disproportionately affects low- and middle-income countries and low-skilled workers, raising urgent equity concerns.
In advanced economies, AI accelerates productivity and creates high-value positions in data science, cloud engineering, and cyber security. However, the same technologies are replacing routine, manual, and clerical work at alarming rates. According to the McKinsey Global Institute (2022), up to 30% of work activities globally could be automated by 2030. Sectors most at risk include manufacturing, retail, logistics, and administrative services—industries that historically provided mass employment.
In contrast, countries across the Global South, particularly in South Asia and sub-Saharan Africa, confront a dual crisis: a burgeoning young labour force with limited opportunities and a technological transition for which they are ill-prepared. In Sri Lanka, for instance, informal employment remains above 55% (ILO, 2022), and access to AI-related training and digital infrastructure is still limited to urban centres. Fiscal austerity and structural reforms have further curtailed public sector hiring, eroding traditional employment safety nets.
This global asymmetry demands a multidimensional policy response. AI cannot be treated purely as a technological innovation—it is a development challenge. Finland provides a forward-looking model. Its “Elements of AI” programme, launched in 2018, was designed to upskill citizens in basic AI literacy through free online modules. By 2021, over 1% of the Finnish population had completed the course, including older workers and those in non-tech fields. Importantly, the initiative was government-led, publicly funded, and industry-supported—proving that inclusive upskilling is both feasible and scalable.
Regulation must also evolve to match AI's reach into employment practices. Increasingly, algorithmic management governs labour in platform-based gig economies, replacing human supervisors with data-driven systems. These opaque algorithms allocate work, assess performance, and determine pay—with minimal transparency or accountability. The European Union's proposed Artificial Intelligence Act recognizes this challenge by classifying AI systems used in employment as “high-risk” and requiring human oversight, impact assessments, and audit mechanisms.
Developing nations must not lag behind in instituting protective legal frameworks. Uruguay, for example, amended its labour laws in 2020 to guarantee platform workers access to social security and collective bargaining. India’s Code on Social Security (2020) includes provisions for gig and platform workers, but its implementation remains limited by jurisdictional and bureaucratic challenges. Without effective regulation, digital labour risks devolving into digital precarity.
Financial investment in workforce development is equally critical. UNESCO’s Education Progress Report 2023 reveals that most low-income countries allocate less than 0.5% of GDP to technical and vocational education and training (TVET). This underinvestment is unsustainable. Rwanda’s partnership with Carnegie Mellon University to cultivate AI talent demonstrates how international academic collaborations can bridge local skill deficits. Countries must view such partnerships not as luxuries, but necessities for future-readiness.
The economic model underpinning labour rights must also shift. Payroll taxes and employer-based contributions—cornerstones of 20th-century social protection systems—are increasingly inadequate in a gig-driven economy. France has piloted a “Universal Activity Income” that decouples welfare from employment status, offering a lifeline to those in non-standard jobs. Likewise, Universal Basic Income (UBI) experiments in Canada, Spain, and Kenya offer insights into income security in high-automation contexts. While not universally applicable, these models illustrate creative policy thinking that matches the pace of technological change.
For Sri Lanka and similar nations, the challenge is formidable but not insurmountable. National AI strategies must integrate human capital development, labour rights, and equitable access. Sri Lanka’s National Digital Economy Strategy remains largely focused on infrastructure and e-governance. However, a successful digital transition must be worker-centric. This requires coordinated inter-ministerial action—particularly among the ministries of education, labour, technology, and finance—and robust engagement with trade unions and civil society.
The role of trade unions is also undergoing transformation. Traditional collective bargaining, while still essential, is no longer sufficient. Digital organizing platforms and algorithmic accountability mechanisms are vital tools for the 21st-century labour movement. The International Trade Union Confederation (ITUC) advocates a “Just Transition” that includes AI, emphasizing participation, equity, and sustainability. Unions must build digital competencies, form strategic alliances, and participate actively in AI governance forums.
Cultural shifts are equally important. In many countries, including Sri Lanka, technical and vocational education is seen as second-tier compared to university degrees. This perception must change. Germany’s dual education system, which combines academic learning with apprenticeships, provides a benchmark for aligning skills development with labour market needs. By enhancing the social status of vocational training and integrating it with digital skills, countries can better prepare youth for a tech-driven economy.
In essence, Labour Day 2025 should prompt reflection not only on the past but also on the urgent redefinition of work in a digital age. The Fourth Industrial Revolution will not wait for outdated institutions or reactive policies. Policymakers, academics, employers, and civil society must collaborate to craft a new social contract—one that ensures AI and automation enhance rather than erode human dignity.
The stakes are high. If left unchecked, AI could deepen inequality, displace millions, and dismantle existing labour rights frameworks. But with strategic foresight, inclusive policies, and bold investments, AI can become a force for economic justice, not technological determinism.
Labour Day is no longer just a celebration of hard-won rights; it is a call to defend and extend those rights into the digital frontier.
Key References:
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World Economic Forum. (2023). The Future of Jobs Report 2023. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
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McKinsey Global Institute. (2022). The Future of Work After COVID-19. https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-after-covid-19
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International Labour Organization (ILO). (2022). ILOSTAT Database.
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UNESCO. (2023). Education Progress Report.
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European Commission. (2021). Proposal for the Artificial Intelligence Act.
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Government of Finland. (2018). Elements of AI Programme.
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Government of Uruguay. (2020). Digital Labour Legislation.
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Government of India. (2020). Code on Social Security.
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France Stratégie. (2021). Towards a Universal Activity Income.
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GiveDirectly (2020). Kenya UBI Pilot.
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Carnegie Mellon University Africa. (2023). AI Talent in Africa.
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German Federal Ministry of Education and Research. (2020). Vocational Education and Training in Germany.
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International Trade Union Confederation (ITUC). (2021). Just Transition Centre – Digitalisation.
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