Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.08934 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909899238146048 |
|---|---|
| author | Liao, Di Liang, Ruijia Ye, Ziyi |
| author_facet | Liao, Di Liang, Ruijia Ye, Ziyi |
| contents | 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 concurrent loads. The research results have important theoretical and practical value for promoting the digital transformation of enterprises, and provide new ideas for improving the operational efficiency of enterprises. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_08934 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Research on Business Process Optimisation Model Integrating AI and Big Data Analytics Liao, Di Liang, Ruijia Ye, Ziyi Artificial Intelligence 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 concurrent loads. The research results have important theoretical and practical value for promoting the digital transformation of enterprises, and provide new ideas for improving the operational efficiency of enterprises. |
| title | A Research on Business Process Optimisation Model Integrating AI and Big Data Analytics |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2511.08934 |