Integration of Global Gig Economy with Artificial Intelligence: A Bibliometric Approach Utilizing the Scopus Database - Leena Kapse, Amit Kumar; Sampada Mashirkar, Sunita Vaibhav Gujar; Ashima Joseph-Varghese (Journal of Informatics Education and Research, 2025)
Purpose: This study focused on the potential role of artificial intelligence to revolutionize the gig economy by enhancing the efficiency of workers and production. Methodology: The researchers extracted two phrases "Gig Economy" and "Artificial Intelligence" to evaluate works of publication in the Scopus database from 2017 to 2025, and assessed 328 papers using a bibliometric analysis methodology. Research Questions: Performance metrics, was used to answer first 5 research questions pertaining to citation analysis, publications by prominent authors, annual cumulative publications, contributions from premier universities, and countries. Scientific mapping was conducted to answer last 5 research questions on citation of documents, co-citation of cited references, bibliographic coupling of journal sources & countries, and co-occurrence of author keywords using VOSviewer. Key findings: The paper discovered significant studies, emerging research fields, and important trends in the gig economy with AI, revealing that participation on gig platforms calls for digital skills. The gig economy has disrupted conventional employment and improved job possibilities by offering flexibility. AI-driven training systems can aid gig workers in identifying the requisite competencies they need to develop and in formulating personalized learning strategies. Future research should focus on addressing ethical concerns, improving AI transparency, and fostering innovation in AI applications for the global gig economy.