Autonomous Business Transformation Through Generative AI Integration

Abstract

Generative Artificial Intelligence (GenAI) is rapidly transforming enterprise operations by automating content generation, knowledge management, and decision support. However, existing research primarily focuses on isolated GenAI applications such as conversational assistants, document generation, or task-specific automation, while limited attention has been given to developing a unified framework that enables autonomous business transformation through coordinated integration of Generative AI, enterprise knowledge repositories, intelligent workflow orchestration, and governance mechanisms. Furthermore, current studies rarely incorporate confidence-driven autonomous decision-making, human-in-the-loop validation, and continuous organizational performance monitoring within a single enterprise architecture. To address these research gaps, this paper proposes an Autonomous Business Transformation through Generative AI Integration (ABT-GAI) framework that combines Retrieval-Augmented Generation (RAG), enterprise knowledge management, confidence-based decision execution, workflow automation, and continuous learning to support intelligent and trustworthy business operations. The proposed framework is evaluated using a quantitative simulation-based methodology involving enterprise workflow datasets across customer service, finance, human resources, operations, and knowledge management. Experimental results demonstrate that the proposed approach achieves a task completion rate of 97.6%, workflow automation of 91.3%, response accuracy of 95.4%, and a 63.6% reduction in average business process execution time compared with conventional enterprise operations. The confidence-based governance mechanism limits low-confidence autonomous decisions by selectively routing uncertain cases for human validation, thereby improving decision reliability while maintaining organizational accountability. Statistical analysis confirms that the observed improvements are significant (p < 0.001) across all evaluated performance metrics. The findings indicate that integrating Generative AI with enterprise knowledge systems and intelligent workflow orchestration enables scalable, efficient, and responsible autonomous business transformation. The proposed ABT-GAI framework provides a practical foundation for next-generation intelligent enterprises by balancing automation, governance, operational efficiency, and human oversight.