Impacts of generative artificial intelligence on the future of labor market: A systematic review

Nader Salari · Mahan Beiromvand · Amin Hosseinian Far · Fateme Babajani · Masoud Mohammadi

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Labor market dynamics and wage inequality Ethics and Social Impacts of AI Digital Economy and Work Transformation

Abstract

Background Generative AI (GenAI) has the ability to autonomously collect and process data to generate contents, inform decisions, solve problems, and perform tasks that typically require human reasoning. This Systematic Review is conducted to examine the impacts of GenAI on the future of employment, focusing on concerns about rising unemployment, and the positive and negative perspectives outlined within exiting studies. The findings from this review can help identify research gaps, guide organizational planning, and improve AI governance frameworks and policies. Methods To identify relevant studies, the PubMed, Scopus, Web of Science, Embase, ScienceDirect and Google Scholar databases and repositories were systematically searched using the keywords: ‘Future of work’, ‘Job market’, ‘Generative AI’, ‘Generative AI’, and ‘ChatGPT’. Additionally, the reference lists of the identified related articles were reviewed for grey literature. Results Following the PRISMA guidelines, a total of 14 articles were selected for analysis. Selected studies have examined the positive and negative viewpoints on GenAI, together with pertinent challenges and opportunities. Accordingly, GenAI, when compliant with security and ethical issues, has the potential to increase efficiency whilst reducing costs and time. Conclusion Considering the rapid growth and adoption of AI technologies, examining the impacts of GenAI on the future of labor market is crucial. GenAI is likely to create new roles in some sectors yet reduce opportunities in others. A nuanced assessment of the impacts, and ongoing monitoring are vital for effective preparation and adaptation to the evolving work landscape in the presence of advanced AI technologies.

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2016The future of employment: How susceptible are jobs to computerisation?2003The Skill Content of Recent Technological Change: An Empirical Exploration 2019Robots and Jobs: Evidence from US Labor Markets 2023Experimental evidence on the productivity effects of generative artificial intelligence 2020GPT-3: Its Nature, Scope, Limits, and Consequences 2020The Fall of the Labor Share and the Rise of Superstar Firms*2019Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World 2017Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace

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