University of Qom Journal of Data Analytics and Intelligent Decision-making 3115-8161 2 2 2026 06 30 The Impact of Artificial Intelligence on Medical Science vision and Labor Market Processes In Medical Occupational Groups 48 66 4585 10.22091/jdaid.2026.15999.1057 EN Hamed Rastegarnia Lecturer at Melli Maharat, University of Zanjan, Zanjan, Iran, Email: hamed.rastegar@znu.ac.ir Mohammad Bigdeli Corresponding Author, Master of Public Administration, Department of Management and Accounting, Faculty of Humanities Sciences, University of Zanjan, Zanjan, Iran. Email: mohammadbigdeli@znu.ac.ir 0009-0004-5011-285X Zahra Morshedi Graduate Student in Business Administration, Sufi Institute of Zanja Zanjan, Iran. Email: z.morshedi6206@gmail.com Journal Article 2026 01 17 The rapid development of artificial intelligence (AI) technology and its major effects on the economy and productivity of countries have made policymaking and regulation in this area more urgent than ever. One of the issues that is important for decision-making, regulation, and legislation in artificial intelligence is the capacity of artificial intelligence to impact various jobs and productivity growth, particularly how AI will reshape jobs, limit and create employment opportunities, and ultimately affect productivity. The purpose of this study is to investigate the impact of artificial intelligence on the medical science landscape and labor market processes in medical occupational groups. This study collected data using the library method, drawing on reliable scientific and research sources. Data gathered from scientific articles, theses, and reputable sources available in databases such as Google Scholar, PubMed, and Scopus were analyzed. The results show that artificial intelligence can significantly increase the accuracy and speed of disease diagnosis by employing machine learning algorithms and analyzing complex medical data. In addition, AI can play an effective role in predicting and preventing diseases by analyzing health data collected from millions of patients. https://jdaid.qom.ac.ir/article_4585_9ad09eb77a8f6b886a68f1e183439f0e.pdf