Generative AI is altering work processes, task composition, and organizational design, yet its effects on employment and the macroeconomy remain unresolved. In this review, we synthesize theory and empirical evidence at three levels. First, we trace the evolution from aggregate production frameworks to task- and expertise-based models. Second, we quantitatively review and compare (ex-ante) AI exposure measures of occupations from multiple studies and find convergence towards high-wage jobs. Third, we assemble ex-post evidence of AI's impact on employment from randomized controlled trials (RCTs), field experiments, and digital trace data (e.g., online labor platforms, software repositories), complemented by partial coverage of surveys. Across the reviewed studies, productivity gains are sizable but context-dependent: on the order of 20 to 60 percent in controlled RCTs, and 15 to 30 percent in field experiments. Novice workers tend to benefit more from LLMs in simple tasks. Across complex tasks, evidence is mixed on whether low or high-skilled workers benefit more. Digital trace data show substitution between humans and machines in writing and translation alongside rising demand for AI, with mild evidence of declining demand for novice workers. A more substantial decrease in demand for novice jobs across AI complementary work emerges from recent studies using surveys, platform payment records, or administrative data. Research gaps include the focus on simple tasks in experiments, the limited diversity of LLMs studied, and technology-centric AI exposure measures that overlook adoption dynamics and whether exposure translates into substitution, productivity gains, erode or increase expertise.

The report covers the extent and consequences of the labour market disruption caused by overlapping economic and geopolitical crises and analyzes global patterns, regional differences and outcomes across groups of workers. The report pays particular attention to the impact of the different crises on productivity, job quality and job opportunities and how these trends risk undermining social justice around the world.

AI is transforming labor markets around the world. Existing research has focused on advanced economies but has neglected developing economies. Different impacts of AI on labor markets in different countries arise not only from heterogeneous occupational structures, but also from the fact that occupations vary across countries in their composition of tasks. We propose a new methodology to translate existing measures of AI impacts that were developed for the US to countries at various levels of economic development. Our method assesses semantic similarities between textual descriptions of work activities in the US and workers' skills elicited in surveys for other countries. We implement the approach using the measure of suitability of work activities for machine learning provided by Brynjolfsson et al. (Am Econ Assoc Pap Proc 108:43-47, 2018) for the US and the World Bank's STEP survey for Lao PDR and Viet Nam. Our approach allows characterizing the extent to which workers and occupations in a given country are subject to destructive digitalization, which puts workers at risk of being displaced, in contrast to transformative digitalization, which tends to benefit workers. We find that workers in urban Viet Nam, in comparison to Lao PDR, are more concentrated in occupations affected by AI, which requires them to adapt or puts them at risk of being partially displaced. Our method based on semantic textual similarities using SBERT is advantageous compared to approaches transferring AI impact scores across countries using crosswalks of occupational codes.

This Chapter provides an overview of the current state of productivity growth across regions of the world. It showcases the generalized nature of the global productivity slowdown and the close relationship between productivity and various social justice indicators. It explores some of the drivers behind the observed stagnation, including labour market factors. Finally, a number of policy messages stemming from the analyses presented are provided.

Labor provisions are integral to regional trade agreements (RTAs). Critics argue that they are a protectionist measure by reducing trade flows. Efforts to test that argument by employing various economic gravity models to trade agreements with labor provisions have failed to apply clear legal criteria and updated estimation methods. Drawing from the law of transnational contracts, we apply clear legal criteria to labor clauses and estimate a Poisson regression by pseudo maximum likelihood with high-dimensional fixed effects and controls for other "deep" agreement provisions associated with trade. We estimate the relationship between labor provisions and bilateral trade by classifying labor clauses found in all World Trade Organization-notified RTAs from the 1990s through February 2016. Contrary to previous efforts, our concise typology, updated estimation methods, and controls for additional trade-agreement variables find no robust evidence that labor provisions impact, much less reduce, trade flows (JEL F1, C5, F14, F66).

We analyze the relationships of three different types of patented technologies, namely artificial intelligence, software and industrial robots, with individual-level wage changes in the United States from 2011 to 2021. The aim of the study is to investigate if the availability of AI technologies is associated with increases or decreases in individual workers' wages and how this association compares to previous innovations related to software and industrial robots. Our analysis is based on available indicators extracted from the text of patents to measure the exposure of occupations to these three types of technologies. We combine data on individual wages for the United States with the new technology measures and regress individual annual wage changes on these measures controlling for a variety of other factors. Our results indicate that innovations in software and industrial robots are associated with wage decreases, possibly indicating a large displacement effect of these technologies on human labor. On the contrary, for innovations in AI, we find wage increases, which may indicate that productivity effects and effects coming from the creation of new human tasks are larger than displacement effects of AI. AI exposure is associated with positive wage changes in services, whereas exposure to robots is associated with negative wage changes in manufacturing. The relationship of the AI exposure measure with wage increases has become stronger in 2016-2021 in comparison to the 5 years before.JEL Classification: J24, J31, O33.

Appendix A provides a literature review on the effects of trade on local labor markets. Appendix B explores the construction of databases used to study entangled workers and shared prosperity in South Asian labor markets. Appendix C lists examples of trade agreements, what they implemented, and their consequences for workers and firms for a selection of developed economies, including the United States, Denmark, Canada, and Germany. Appendix D lists examples of trade agreements, what they implemented, and their consequences for workers and firms for a selection of developing economies, including Mexico, Morocco, India, Indonesia, Sri Lanka, Vietnam, Brazil, Bangladesh, and Pakistan.

The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job loss and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a widespread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policies are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy, and help share the benefits of productivity growth through the combination of profit sharing, (digital) capital taxation, and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from AI, provided that policymakers and social partners take the particular characteristics of these new technologies into account.

Explores how much of an impact higher exports would have on South Asia's labor markets and which groups of workers would benefit most, in particular estimating the relationship between exports and wages, employment, informality, and inequality for different groups—with the focus on the local labor markets. Higher demand from Organisation for Economic Co-operation and Development (OECD) countries for imports from India would lead to higher wages for India's export workers, but would not necessarily mean more jobs. If the value of India's exports increases, annual wages would increase—with the biggest beneficiaries being college graduates, urban workers, and males—though the effects vary greatly among states. Rising exports also associate with falling informality in India—especially for unskilled workers, who benefit less from wage increases compared to others. For Sri Lanka, the same pattern holds, with higher demand from OECD countries for Sri Lankan imports boosting wages, but not necessarily creating more jobs.

Asserts that South Asia's growing youth workforce offers a major demographic dividend, but only if the region can create enough good jobs to employ everyone—and that means increasing wages, reducing informal employment, and promoting equality. Exporting holds the potential to improve labor market outcomes, but South Asia has a relatively low engagement with global markets: its merchandise exports account for less than 10 percent of gross domestic product (GDP), compared to over 20 percent in East Asia and Pacific, and 30 percent in Europe and Central Asia. Making matters worse, exports remain concentrated in a few goods and destinations (Europe and the United States), with export firms concentrated in a few geographical areas. In Bangladesh and Sri Lanka, labor-intensive export industries (like textiles and apparel) have benefited workers, but the benefits of India's capital-intensive export industry (like chemicals and fabricated metals) for workers remain less obvious.

Develops three policy options that may help South Asia to spread the gains from exports to wider parts of the population. If South Asia sharply increases its exports to the levels of competitors like Brazil or China, it could achieve higher wage gains and lower informal employment. If the region focuses on boosting exports in labor-intensive industries, it could significantly lower informality for groups like rural and less-educated workers. And if it increases the skills of workers and participation of women and young workers in the labor force, it could make an even bigger dent in informal employment. South Asian countries could spread the labor market gains more widely by focusing on (1) boosting and connecting exports to people (for example, by removing trade barriers and investment in infrastructure); (2) eliminating distortions in production (for example, by more efficient allocation of inputs); and (3) protecting workers (for example, by investing in their education and skills).

Suggests that South Asian economies face what some may perceive as a paradox: decades of very high and impressive growth rates have done (too) little to create inclusive job growth, and critical challenges, like low-quality jobs, remain. At the same time, decades of exponential trade growth have left the region's economies less linked to international trade than economies in other regions. All of these developments prove especially worrisome given that South Asia remains characterized by persistent—and, in places, extensive—poverty, a burgeoning youth population, and high levels of informal jobs. A greater export orientation could prove one way to improve the labor market picture—and the academic literature shows a strong link between trade and growth—but few studies provide estimates of the relationship between exports per worker and specific labor market outcomes. Developing an innovative approach to estimate the relationship between exports per worker, earnings, and employment in South Asia promises useful results.

South Asia’s economy has grown rapidly, and the region has made a significant reduction in poverty. However, the available jobs for the growing working population remain limited. Policy makers are contending with lingering concerns about jobless growth and poor job quality. Exports to Jobs: Boosting the Gains from Trade in South Asia posits that exports, could bring higher wages and better jobs to South Asia. The report uses a new methodology to estimate the potential impact from higher South Asian exports per worker on wages and employment. The report finds that increasing exports per worker would result in higher wages, mostly for the better-off groups—like the better-educated workers, men, and the more-experienced workers—although the less-skilled and rural workers would benefit from new job opportunities outside of the informal sector. Report findings show that to spread the benefits from higher exports widely, policies are needed to raise skills and get certain groups, such as women and youth, into more and better jobs. Complementary measures include removing trade barriers and investing in infrastructure, and increasing the ability of workers to find higher-paying jobs. Together, these actions would help South Asian countries spread the gains from being closely integrated into the global economy through exporting. This book, which is the product of a partnership between the International Labour Organization and the World Bank, contributes to our understanding of the impact that growing exports can have on increasing well-being, and it bridges the gap between academic research and policy making.

ResumenEste artículo propone un marco analítico y metodológico para examinar la eficacia de las disposiciones laborales de los acuerdos comerciales, ilustrándolo con estudios de casos. Los autores desarrollan la noción de capacidad en tres niveles (jurídico, institucional y político) y diferencian entre resultados inmediatos (jurídicos, institucionales y políticos) y resultados socioeconómicos ulteriores (mejora de los derechos y las condiciones laborales). Analizan las disposiciones laborales de dichos acuerdos como una «combinación de políticas» que ha de evaluarse con métodos cualitativos y/o cuantitativos, dependiendo del aspecto de la capacidad de que se trate y de los datos disponibles. Asimismo, ofrecen algunas recomendaciones de política.

This article puts forward an analytical and methodological framework for examining the effectiveness of labour provisions in trade agreements, illustrated by indicative case studies. Developing the notion of capacity at three levels (state, civil society and firms), the authors differentiate between proximate outcomes (legal, institutional and political) and distant, socio-economic outcomes (improving labour rights and working conditions). They thus consider labour provisions in trade agreements as a multifaceted "policy mix" to be evaluated through qualitative and/or quantitative methods, depending on the aspect of capacity that is of interest, and on the available data. Some policy recommendations are also provided.

RésuméLes auteurs proposent un cadre analytique et méthodologique aux fins de l'évaluation de l'efficacité des dispositions relatives au travail figurant dans les accords commerciaux. Avant d'illustrer leur propos par plusieurs études de cas, ils précisent la notion de capacité à trois niveaux (État, société civile et entreprises) et font la distinction entre résultats immédiats (aménagements juridiques, institutionnels et politiques) et lointains (amélioration des droits au travail et des conditions de travail). Affirmant le caractère multidimensionnel de ces dispositions, ils suggèrent de les évaluer par des méthodes qualitatives et quantitatives, selon la capacité traitée et les données disponibles. Ils formulent aussi quelques recommandations générales.

In recent years, an increasing number of regional and bilateral trade agreements have emerged that include provisions on labor standards. The claimed purpose of these labor provisions is to improve working conditions in developing and emerging economies. However, little is known about whether such provisions actually do impact working conditions. This paper conducts an econometric study on the effectiveness of labor provisions in trade agreements. In particular, we evaluate the impact of the 1999 Bilateral Textile Agreement between Cambodia and the United States (CUSBTA) on both the gender wage gap and discrimination. The agreement combined the incentive of higher exports with the obligation of textile manufacturers to comply with international core labor standards, which include the elimination of discrimination in respect of employment and occupation. Using data from the Cambodia Socioeconomic Survey and applying a difference-in-difference estimation, we find a statistically significant reduction of the gender wage gap in the textile sector that can be attributed to the CUSBTA.