Impact of generative artificial intelligence on workload, efficiency and labour productivity

In recent years, generative artificial intelligence (GAI) has gained significant importance in production and operations management (POM) due to its potential to enhance worker productivity. This article aims to characterise the impact of GAI on workload, efficiency and labour productivity across various industries. The research question was formulated and, using the CIMO framework (context, intervention, mechanism, outcome), the search and retrieval of articles were conducted in the Scopus and Web of Science (WoS) databases, and yielded 149 articles. After the selection, evaluation and content analysis of each study, 74 articles were ultimately included in the systematic literature review. Seven industries were identified in which GAI has demonstrated impacts on workload, efficiency and labour productivity, with four sectors accounting for 80% of the studies. The impacts of GAI reveal four trends, all of them key in POM: automation and optimisation of workflows; support in decision making; improvement in human-machine interactions; enhancement in communication. To fully apply the potential of this technology, it is necessary to continue researching and addressing the identified issues, including ethical, employment, privacy and information quality challenges.