# 1. Introduction

Public attention to Generative AI (GenAI) has been on the rise since the introduction of the conversational models, such as ChatGPT, Bard or Gemini. The impressive abilities of the Large Language Models (LLM), followed by other neural network-based AI systems capable of generating image and even video from simple text prompts have raised a range of important ethical and security questions for national policy makers and international cooperation structures. However, the topic that captures most daily attention of regular citizens is the potential impact of these quickly advancing tools on jobs.

In the United States (US), over half of all adults are more worried than excited about AI in daily life, citing the “loss of human jobs” as their most important concern (Faverio and Tyson, 2022; Pew Research Center, 2023; Rutgers, 2024). In Switzerland, a 2023 survey focused specifically on GenAI revealed that of 1,000 respondents already working with a computer, almost half (43%) were concerned about losing their job in the next five years, with those frequently using GenAI at work being disproportionately (69%) more concerned (Grampp et al., 2023). This suggests a rapid departure from more positive assessments of AI in surveys collected by OECD prior to the arrival of publicly accessible chatbots in late 2022 (Lane et al., 2023; OECD, 2023).<sup>2</sup> Not surprisingly, the potential transformation that might result from the interaction of GenAI with labor markets has also attracted growing attention among scholars. Main research questions have centered around the impact on employment, emerging occupations, productivity and job quality.<sup>3</sup> A recent paper from the IMF provides a comprehensive overview of this literature, at the same time highlighting the scarcity of studies that go beyond high-income countries (HICs) (Comunale and Manera, 2024).

Bridging this research gap, our study provides new evidence on the potential impacts of GenAI across labor markets in the Latin America and the Caribbean (LAC) region. Building on the approach developed by Gmyrek, Berg and Bescond (2023) – GBB hereafter – we provide new evidence on AI exposure between and within countries by leveraging harmonized household and labor force surveys for LAC from the World Bank (WB) and the International Labour Organization (ILO). By building on the comparative strengths of the datasets from both institutions, we develop a complete regional overview, accompanied by country-level estimates of the potential occupational exposure, with further breakdowns by detailed demographic and labor market characteristics.

An important contribution of this study is to provide a first attempt at adapting measures of jobs’ exposure to GenAI to the context of developing countries, where even workers in occupations that are generally expected to benefit from GenAI may not be able to reap its benefits due to poor access to digital infrastructure. We implement this adjustment by estimating measures of computer

> 2 In OECD’s survey of workers “ _four in five workers said that AI had improved their performance at work and three in five said it had increased their enjoyment of work_ ” (...) “ _Workers were also positive about the impact of AI on their physical and mental health, as well as its usefulness in decision making_ ” (OECD, 2023).

> 3 E.g., see Brynjolfsson et al., 2023; Hui et al., 2023, Beraja et al., 2023, Adams-Prassl et al., 2023.

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