Transforming Economic Research Through Generative AI

Economic research has continuously evolved with advances in technology, from early computing tools to sophisticated statistical software. The latest transformation is driven by Generative Artificial Intelligence (AI), particularly large language models, which are capable of generating text, summaries, code, and analytical support based on learned data patterns. This paper examines how Generative AI is reshaping economic research across various stages, including literature review, research design, data collection, data cleaning, analysis, modelling, and report writing. It highlights key benefits such as time efficiency, cost reduction, enhanced accessibility for young researchers, improved creativity, and stronger support for evidence-based policy research. At the same time, the study critically discusses major challenges and risks associated with Generative AI, including data and algorithmic bias, hallucination and incorrect outputs, ethical concerns related to plagiarism and authorship, over-dependence on AI tools, and unequal access to advanced technologies. The paper emphasizes the need for transparent, ethical, and responsible use of Generative AI under strong human supervision. It concludes that Generative AI is a transformative force in economic research, capable of significantly enhancing productivity and analytical depth, provided it is used as a supportive tool rather than a replacement for human judgment and scholarly responsibility.