A Framework for Implementing Generative AI in Business Processes

The subject of the research is the development of a comprehensive framework for the strategic implementation of generative artificial intelligence (GenAI) in the business processes of organizations of various sizes and industries. Existing approaches to the implementation of traditional artificial intelligence (AI) technologies, GenAI, and digital transformation are analyzed, and their limitations and shortcomings are identified in the context of the specific characteristics of GenAI models, such as the ability to create new content and the associated ethical and legal risks. The necessity of creating a specialized framework that takes into account the unique opportunities and challenges associated with GenAI, as well as the need for adaptation to diverse business contexts, including small and medium-sized businesses, is substantiated. The problem of the lack of structured methodologies that allow organizations to effectively integrate GenAI into their operational activities, maximizing return on investment and minimizing potential risks, is considered. The research is based on a systematic and comparative analysis of scientific literature and practical publications, as well as the synthesis of the conceptual basis of a new framework. A combined approach is used, including methods of qualitative and quantitative data analysis. The scientific novelty lies in the development of a nine-stage framework that, unlike existing approaches, integrates large language models (LLMs) already at the stage of business process diagnostics for semantic analysis of unstructured data (interviews, questionnaires, surveys). This makes it possible to identify hidden relationships and non-obvious optimization needs that are difficult to detect using traditional methods. The framework covers strategic, operational, and technological aspects of implementation, as well as change and risk management principles. The developed framework offers a universal, adaptive, and practically oriented approach to the strategic implementation of GenAI, contributing to improving the efficiency of business processes, minimizing risks, and maximizing the return on investment in GenAI technology. The practical significance is confirmed by approbation at the academy of a large consulting company and a pilot project at MTS PJSC.

generative artificial intelligence, implementation framework, large language models, business processes, strategic analysis, process optimization, risk management, change management, digital transformation, AI transformation