Harnessing AI for BPM: Streamlining Complex Workflows and Enhancing Efficiency
Keywords:
Artificial Intelligence, Business Process Management, Workflow Automation, Process Mining, Predictive Analytics, Machine Learning, Natural Language Processing, Operational Efficiency, Digital TransformationAbstract
BPM has become crucial in organizations to facilitate the management of elaborate processes within the firms, and the application of AI in business has assist with robust agenda in areas of business processes management with improving competitiveness. The role of AI in BPM is a subject of interest in this paper with specific attention paid to the fact that it can significantly expand the contours of BPM by rendering it work and resource efficient, and capable of real-time decision-making. The quantitative review of AI-BPM solutions features process mining, predictive analytics, natural language processing, and machine learning. By providing examples with real-world cases and examples this study shows how deficiencies of traditional BPM can be addressed through the use of AI. Furthermore, the paper outlines the issues and concerns with integrating AI in an organization, technical, ethical and organizational risks, and recommendations for proper integration of AI as part of innovations. Through analyzing the most recent findings and future developments regarding the application of AI in BPM, this study emphasizes the opportunities that AI can bring to the process, providing practical recommendations for enhancing BPM through AI for organizations interested in integrating AI into process management for effective and efficient long-term performance.
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