The transformative potential of Generative Artificial Intelligence (GenAI) in business: a text mining analysis on innovation data sources

Objective: This study investigates the transformative potential of Generative Artificial Intelligence (GenAI) within the business domain and the entrepreneurial activity. Methodology: A comprehensive research design is adopted, integrating text-mining techniques to ana-- lyse data obtained from publicly available innovation repositories. A systematic literature review (SLR) is developed based on the literature obtained from all databases indexed in Web of Science (WoS), incorporating preprints from arXiv, alongside industry-related innovation data in the form of patents from Google Patents. This method enables the der-- ivation of valuable insights regarding the impact and prospective developments of GenAI across diverse business sectors and industries by leveraging Natural Language Processing (NLP) and network analysis. Results: The research outcomes highlight the significant potential of GenAI in enabling informed decision-making, enhancing productivity, and revealing new growth opportunities in the business landscape. The continuously evolving business environment is examined, emphasising GenAI's role as a catalyst for data-driven innovation. However, there are still relevant limitations to overcome. Limitations: The selection of data sources and the study period may have excluded relevant or recently published articles and patents within the scope of the present research. The language of the databases analysed is only English. Practical Implications: The practical implications of this study carry significant weight, serving as a valuable resource for decision-makers, researchers, and practitioners navigating the constantly shifting terrain of business innovation through the lens of GenAI. Understanding the potential advantages and challenges associated with GenAI adoption equips stakeholders to make informed decisions and develop future business strategies.