AI and Labour Markets in early 2026

This event is organized as part of ITU's AI for Good Series.

Investments in Artificial Intelligence are advancing at an unprecedented pace, raising fundamental questions about how this technology might reshape work, employment and skills. A new wave of empirical studies is beginning to shed light on these developments, but the evidence remains early and incomplete. Some of the first large scale findings, such as those from the “Canaries in the Coal Mine” study in the United States and a similar analysis from the United Kingdom, suggest that exposure to Large Language Model (LLM) capabilities may already be affecting employment patterns, hiring behaviour and the structure of job opportunities.

This session takes these emerging results as a starting point for a broader discussion on the state of knowledge about AI and labour markets. Following the evidence on early labour market impacts, the conversation will turn to the question of AI adoption: what it actually means for enterprises and workers to adopt AI, how adoption is measured, and why these distinctions matter for interpreting economic effects. The session will then explore how AI capabilities are changing, how this evolution may alter the relationship between tasks and technology, and what this implies for the risks of substitution versus the potential for genuine augmentation of labour and human abilities.

Looking ahead to 2026, the session will discuss key priorities for research, from improving measurement to understanding broader economic effects across different types of economies.

Speakers

Bharat Chandar


Bharat Chandar is a postdoctoral fellow at the Stanford Digital Economy Lab, where he studies the labour-market impacts of artificial intelligence and emerging technologies. His influential paper with Erik Brynjolfsson and Ruyu Chen, “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence,” provides some of the earliest large-scale evidence that AI may be beginning to have a disproportionate impact on entry-level workers in the American labour market. His work contributes to a growing empirical literature documenting how AI reshapes employment, skill needs and career trajectories.

Bouke Klein Teeselink


Bouke Klein Teeselink is an Assistant Professor in Economics at King’s College London, and is Afiliated Researcher at the AI Objectives Institute and King’s Institute for Artificial Intelligence. He is working at the intersection of behavioural economics, political economy and the economics of Artificial Intelligence. He is a co-author of “Generative AI and Labor Market Outcomes: Evidence from the United Kingdom,” which shows that firms highly exposed to Large Language Model capabilities reduce employment and curtail new hiring, particularly in junior, technical and creative roles, and experience substantial declines in job postings, with effects concentrated in high-wage segments. His broader research uses large datasets to understand how technological change transforms work, skills, and economic behaviour.

Moderator
Pawel Gmyrek
Senior Researcher, Research Department, ILO