A Research on Business Process Optimisation Model Integrating AI and Big Data Analytics
Di Liao, Ruijia Liang, Ziyi Ye

TL;DR
This paper presents a novel AI and big data integrated business process optimization model that enhances efficiency, reduces costs, and supports real-time management in enterprise digital transformation.
Contribution
It introduces a three-layer architecture model combining AI and big data analytics for comprehensive process optimization, a novel approach in enterprise management.
Findings
Shortened process time by 42%
Improved resource utilization by 28%
Reduced operating costs by 35%
Abstract
With the deepening of digital transformation, business process optimisation has become the key to improve the competitiveness of enterprises. This study constructs a business process optimisation model integrating artificial intelligence and big data to achieve intelligent management of the whole life cycle of processes. The model adopts a three-layer architecture incorporating data processing, AI algorithms, and business logic to enable real-time process monitoring and optimization. Through distributed computing and deep learning techniques, the system can handle complex business scenarios while maintaining high performance and reliability. Experimental validation across multiple enterprise scenarios shows that the model shortens process processing time by 42%, improves resource utilisation by 28%, and reduces operating costs by 35%. The system maintained 99.9% availability under high…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Digital Transformation in Industry · Robotic Process Automation Applications
