The Future of Work Working Group

Aleah (not her real name) is an Amazon “Warehouse Associate”, working at one of the many fulfilment centres based in the UK.1 Associates, also referred to as “Warehouse Operatives” by Amazon, are the workers who receive and stow products, and pick and pack them for customers, before they are sent to another node in Amazon’s supply chain for last-mile delivery. In the words of the company, associates are “essential”; they “literally bring customers’ orders to life, every day”.2 Working in an “on task” role (also referred to as a “direct” role), Aleah and associates like her, are subject to an algorithmically determined, pace-based target, colloquially referred to as the “rate”. Aleah doesn’t really know how the “rate” is calculated. All she knows is that she needs to hit an acceptable pace to avoid coaching and potential disciplinary action, including receiving a negative ADAPT. ADAPT stands for Associate Development and Performance Tracker. According to the limited public information available and data collected for this research, ADAPT is a software used by management to track employee performance and provide positive and negative validation across a range of dimensions including productivity, quality, safety and behaviour. — May 21, 2025

The first Fairwork AI report presents the results of a case study into Sama, a data annotation company that aims to have a positive social impact, which was conducted as part of the Global Partnership on Artificial Intelligence (GPAI) “AI for Fair Work” project. Across the world, there is increasing attention paid to the precarious situation of workers that are part of the AI supply chain. The Fairwork AI ratings presented in this report, which assess the working conditions of workers at Sama in different job roles and performing various tasks, show that fairness at work is not a given, but that by pointing to shortcomings and encouraging meaningful pro-worker change, substantial improvements can be achieved. The key improvements Sama made to the working conditions of its workers through their engagement with Fairwork are the focus of this report. Concretely, as a result of engagement with Fairwork, Sama has made some 24 significant changes in the past year to their operational model and business practices, including guaranteeing the living wage for its workers, eliminating unpaid overtime and extending employment contracts.— May 21, 2025

Launched in 2021, this project is aimed at observing AI at the workplace and analyzing its impact on workers. The project methodology involves recruiting and coaching students’ communities, who conduct interviews with workers in their geographical area. The FoW WG provides the students with a common questionnaire and pays them for the use cases collected. Since this project’s inception, three generations of students have been hired from different countries, and two reports on the impacts of AI on workers have been published. The project continued using the same questionnaire as previous years but, in 2023, saw some modifications in its methodology, by incorporating a new vision focused on gig workers (this year in Mexico). The complete report is available at the link below. It presents three studies, two conducted by the Students’ Communities in Japan and Mexico, and a third from Yann Ferguson, a FoW Expert, that has included the perspective of LaborIA, a French initiative on AI at work.— May 21, 2025

The Observation Platform of AI at the workplace project was born in 2021. To understand the motivations behind this project, we can quote the first 2 sentences of this project's report in this year 2021: “To build a better future for workers collaborating with AI, to be more inclusive on various criteria such as disability, gender, ethnicity... a mandatory initial step is observation. The aim is to capture what is happening in the real context of workplaces: observe AI at the workplace, gather as diverse as possible use cases, conduct qualitative analyses of its impact in different situations, geographies, sectors, users.” And indeed, since then, three generations of students have been hired (in Europe/Canada, Japan and Mexico) and two reports have been published on the impacts that could be observed of AI on the worker's environment.— May 21, 2025

The GPAI Future of Work group has translated the OECD AI principles into concrete workplace standards to inform the practices of employers. This process of standard development initially began with a global stakeholder consultation, which generated a first version. Now, the research team have conducted two in-depth workplace studies to connect these standards to empirical data collected on the frontlines of AI system deployment. This process has allowed for a revision of the principles, conducted in association with research partner Fairwork. The new principles have a stronger focus on pay, conditions, contracts, management and representation, because these fundamental issues were consistently highlighted by research participants. A second report containing the results of the two case studies is to follow in early 2024. — May 21, 2025

n response to the expanding landscape of digital technologies and the growing complexity of AI-based software solutions, we propose a single framework for gathering the best practices related to the development of AI-based solutions. This endeavour is driven by global digitalisation and “AI-tisation”, both horizontally (i.e., covering new industries) and vertically (i.e., infiltrating existing use cases). Let us consider a case study of an autonomous intralogistic platform1 vendor based in Poland: a manufacturer of robots that usually work in warehouses. This company stands as an illustration of the transformative power of intelligent technologies: starting as the producer of Autonomous Mobile Robots (AMR), the company has evolved into a vendor of digital AI-platform supporting the design, implementation, and management of autonomous intralogistic operations for manufacturing facilities and warehouses.— May 21, 2025

Generative AI and the Future of Work remains notably absent from the global AI governance dialogue. Given the transformative potential of this technology in the workplace, this oversight suggests a significant gap, especially considering the substantial implications this technology has for workers, economies and society at large. As interest grows in the effects of Generative AI on occupations, debates centre around roles being replaced or enhanced by technology. Yet there is an incognita, the "Big Unknown", an important number of workers whose future depends on decisions yet to be made In this brief, recent articles about the topic are surveyed with special attention to the "Big Unknown". It is not a marginal number: nearly 9% of the workforce, or 281 million workers worldwide, are in this category.— May 21, 2025

The GPAI Future of Work (FoW) Working Group’s mandate and scope are to: • Conduct critical technical analysis on how the deployment of AI can affect workers and working environments as well as how workers and employers can better design the future of work. • Address how AI can be used in the workplace to empower workers, how employers and workers can prepare for the future of work, and how job quality, inclusiveness, and health & safety can be preserved or even improved. • Include a focus on the education and training needed to prepare the future workforce. The Steering Committee encourages future projects that focus on the education and training needed to prepare people for jobs of the future, as well as on how AI can be leveraged in this education and training. — May 21, 2025

The Future of Work (FoW) Working Group (WG) started its work in 2020 with the objective to analyze how AI affects the worker, and how one can improve the AI/human cohabitation in the workplace. In 2021 the FoW WG launched two projects, (i) the AI observation Platform collecting use cases of AI at work, and (ii) AI for Fair Work, a project aiming to propose principles for a fairer AI at work. With that in mind the AI Living Lab, launched in 2022 and presented below, has found its place in the activities of the WG. The AI Living Lab would make available to a large public the use cases collected in the AI Observation Platform project. These use cases could then be confronted with the principles of the AI for Fair Work project and thus launch discussions on how to make AI fairer at work. — May 21, 2025

The Observation Platform of AI in the Workplace conducts empirical investigations on reallife use cases of Artificial Intelligence systems at work. The objective of this approach is to understand AI systems in national, cultural, sectoral, organizational, professional and individual contexts. This allows us to highlight different processes of "AI socialization", i.e. how the promises and characteristics of AI systems meet and confront systems of norms and values that will give them meaning beyond the functional objectives motivating their integration.— May 21, 2025

Artificial Intelligence (AI) is transforming the way we live. This change is neither good nor bad; nor is it neutral.1 Instead, the ongoing development of AI systems presents us with both opportunities and threats that will emerge in different ways in different contexts. The collective challenge ahead of us is to ensure that our adoption of this new technology maximises the upsides and minimises the downsides. There has been much debate about what ethical principles should guide our collective response to AI in order to achieve this goal. However, the existing academic and policy discourses have largely failed to address an area in which AI is already having a transformative impact: the workplace. Deployments of AI systems in the labour process are affecting an ever-expanding number of people, but most extant ethical frameworks are inadequate to address how we should work with and alongside AI systems. This report presents a set of ten Fair Work principles for AI that address this specific issue, developed through extensive tripartite consultation. — May 21, 2025

The GPAI Future of Work (FoW) Working Group’s mandate and scope are to:  conduct critical technical analysis on how the deployment of AI can affect workers and working environments as well as how workers and employers can better design the future of work.  address how AI can be used in the workplace to empower workers, how employers and workers can prepare for the future of work, and how job quality, inclusiveness, and health & safety can be preserved or even improved. The FoW Working Group is comprised of 34 experts and 1 OECD observer who contribute to the two projects conducted in the GPAI 2021 workplan. As a community, FoW is diverse in terms of stakeholders: 25 experts come from science, 7 from industry, 1 from government and 1 from a trade union. All GPAI members nominated 1 or 2 experts in the working group, thus ensuring the geographical diversity. Finally, gender representation is achieved with approximately 40% female experts and 60% male experts. — May 21, 2025

To build a better future for workers collaborating with AI, to be more inclusive on various criteria such as disability, gender, ethnicity... a mandatory initial step is observation. The aim is to capture what is happening in the real context of workplaces: observe AI at the workplace, gather as diverse as possible use cases, conduct qualitative analyses of its impact in different situations, geographies, sectors, users. The collection of use cases by GPAI ensures it will be neutral and trustworthy. These two last criteria are central as the Observation platform will allow the experts to conduct further research and, for example, analyze the reality of AI in companies through: (1) the impact of cultural specificities in the way AI is implemented at the workplace based on a large number of use cases across geographies and cultural contexts, and (2) the possible changes in the way in which AI systems are implemented from ongoing observations. This will provide insight to GPAI members on an improved human centered approach of AI at the workplace and enlighten decision-makers, whether they are politicians or in the private sector.— May 21, 2025

In the GPAI Future of Work Working Group (FoW), 27 experts with multiple backgrounds and expertise from 15 countries collaborate to support a collective understanding of the impact of AI on work and to build a collective intelligence on this issue. The group has decided to develop its contribution in two directions: one focusing on existing real cases and the second turned toward the future vision. The FoW investigates how the deployment of AI can affect workers and working environments, how job quality, inclusiveness, health and safety in the workplace can be preserved, and how workers and employers can prepare and better design the future of work. As a major activity of the first 5 months, the FoW has gathered and analyzed use cases of AI applications at the company level. For this empirical work, the experts have developed a questionnaire to query the general characteristics of AI use cases together with their underlying motivations and objectives, the participation of workers and representatives in the design and development of AI systems, the role of Human-Machine Interfaces, the ethical aspects involved and the impact on employment, work conditions and organization. From an initial overview of 53 use cases, the group has observed in an exploratory manner some trends that can be summarized as follows: • AI applications can help organizations to produce new knowledge based on data. • Certain AI applications can contribute to the employees’ wellbeing and decent working conditions. • Effective collaboration between AI and humans is essential for success. This refers to AI supporting human work rather than replacing it and to AI requiring human developers, trainers and supervisors. • AI uses in the industry require more dialogue with the social partners1 and a greater awareness and understanding of ethical aspects. • AI can take on certain human work tasks and, therefore, will have an impact on employment, recruitment, and the skills required for future jobs.— May 21, 2025

El presente estudio busca analizar el impacto en el empleo de la incorporación de la Inteligencia Artificial Generativa (IAG) en América Latina mediante la exploración en 5 países de la región (México, Chile, Colombia, Argentina y Costa Rica), de algunos de los sectores a priori más afectados: call centers y atención al cliente, diseño gráfico, arte y fotografía, redacción publicitaria y periodismo y desarrollo de software. Se realizaron más de 60 entrevistas a trabajadores, empresarios, líderes sindicales y representantes de cámaras empresariales. Este trabajo muestra que se está generando una transformación laboral compleja y multifacética, y hasta el momento, no del todo coincidente con los estudios predominantes en la literatura, que son los basados en el análisis de los niveles de exposición a la IAG de las distintas tareas que componen cada puesto laboral. Las entrevistas mantenidas y estudios de diversas fuentes, marcan que, si bien la región está lejos aún de una adopción generalizada, la IAG está comenzando a redefinir tareas, reconfigurar algunos sectores productivos y, fundamentalmente, creando nuevas tensiones entre el potencial de la tecnología y el riesgo de precarización del empleo. — May 13, 2025

The present study aims to analyze the employment impact of the adoption of Generative Artificial Intelligence (GAI) in Latin America through an exploration of five countries in the region—Mexico, Chile, Colombia, Argentina and Costa Rica—and a focus on sectors considered to be among the most affected: call centers and customer service, graphic design, art and photography, copywriting and journalism, and software development. Over 60 interviews were conducted with workers, businesspeople, union leaders, and representatives of business chambers.This research reveals the emergence of a complex and multifaceted transformation of labor, which, up to this point, does not fully align with the prevailing studies in the literature, particularly those based on exposure level analyses that assess how various tasks within job roles may be impacted by GAI. Interviews and findings from various sources indicate that while the region is still far from widespread adoption, GAI is already beginning to redefine tasks, reconfigure certain productive sectors, and, above all, generate new tensions between the technology’s potential and the risk of employment precarization. One key conclusion that emerges from the research is the discrepancy between the widespread fear of massive job displacement due to GAI and the empirical evidence collected across the sectors analyzed. While occupational exposure studies suggest significant vulnerability in certain roles, the concrete experiences of implementation reveal a more nuanced and complex picture. Some sectors, such as software development, stand out as areas where indicators predict high levels of replacement, yet in practice what is observed is complementarity. — May 13, 2025

This report frames the issues relevant to understanding GenAI’s implications for work, provides the most recent research findings and policy developments in this area, and integrates them with insights drawn from the roundtable discussions. It compares the regional perspectives in three main domains: a) approaches for grasping the future of work; b) perspectives on and experiences of GenAI’s impact on employment and job quality; and c) current policies and future policy priorities. The analysis of the roundtable discussions shows that debates tended to focus primarily on impacts on employment levels, with job quality aspects receiving less attention – though European stakeholders voiced the strongest concerns on these issues, especially regarding social dialogue and working conditions. The Asian perspective stood out for its broader emphasis on reskilling, focusing on AI literacy for all citizens (beyond the workforce) and integrating human skills, such as critical thinking, into education from its early stages. Asian stakeholders also raised the point of job and organisational redesign. In Latin America, fears of job displacement were more prevalent, especially in the context of digital divides among the population, and participants highlighted the need for innovative regulatory approaches.— January 1, 2025

This report, Global Workers and AI: Adoption, Usage, and Regional Differences, explores the integration of artificial intelligence (AI) tools into professional workflows across different global regions, focusing on Latin America (LATAM), Japan, and the United States (USA). Through a series of in-depth interviews with freelancers and professionals in various industries, the study examines how workers in these regions adopt and use AI, the challenges they face, and the ethical and cultural considerations shaping their experiences. The findings are framed as preliminary and exploratory, reflecting a qualitative examination rather than definitive conclusions. While patterns and themes emerged from the interviews, conclusions are informed by the authors’ broader contextual and analytical insights, rather than directly derived solely from the data.— December 26, 2024

January 28, 2021

January 28, 2021