The Impact of AI on the Workplace: Evidence from OECD Case Studies of AI Implementation

Abstract

2  DELSA/ELSA/WD/SEM(2023)7 Unclassified OECD Social, Employment and Migration Working Papers www.oecd.org/els/workingpapers OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the author(s).Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to

Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT

“…These disruptive AI-driven tools have precipitated much discussion and emerging research agendas regarding the implications for managers and those trying to represent, educate and train workers (Dwivedi et al, 2023). Such disruptions have sparked interest in how such AI-driven tools may affect workplaces (Milanez, 2023) and ER stakeholders (Ioakimidis & Maglajlic, 2023;Zu, 2023) and HRM (Korzynski et al, 2023).…”

Artificial intelligence and the changing demand for skills in Canada

“…In contrast, every other country in the sample saw demand rise for these skills with the largest increases experienced in the United States, Canada and the United Kingdom. 18 In Canada, 18 As noted previously, the crosswalk from the Lightcast taxonomy to ONET+ differ by country. Canada, the United Kingdom and the United States use the crosswalk of Lassébie et al (2021[3]) and the remaining countries use an ESCO to ONET crosswalk adapted to ONET+.…”

“…4 Other approaches to measuring AI exposure that have been used in the literature do not capture workers without AI skills or are less suited for cross-country comparative analysis. One popular method for identifying AI exposure uses job postings and their associated skill demands for workers with AI skills to infer AI adoption by firm, occupation or industry (Alekseeva et al, 2021[15]; Squicciarini and Nachtigall, 2021 [16]; Calvino et al, 2022[17]; Manca, 2023 [18]; Green and Lamby, 2023 [5]). 5 However, this method misses firms who adopt AI but do not develop or service it in-house, or workers whose abilities overlap with AI advances but who do not need AI skills.…”

AI language models

“…In 2022, Meta launched its Open Pre-Trained Transformer (OPT-175B), which is the first 175-billlionparameter LLM made available to the broader AI research community (Meta, 2022 [54]). The release includes both the pretrained models and the code needed to train and use them.…”