Summary of A Review Of Ai and Machine Learning Contribution in Predictive Business Process Management (process Enhancement and Process Improvement Approaches), by Mostafa Abbasi et al.
A Review of AI and Machine Learning Contribution in Predictive Business Process Management (Process Enhancement and Process Improvement Approaches)
by Mostafa Abbasi, Rahnuma Islam Nishat, Corey Bond, John Brandon Graham-Knight, Patricia Lasserre, Yves Lucet, Homayoun Najjaran
First submitted to arxiv on: 7 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper aims to bridge the gap between academia and industry by exploring the intersection of Artificial Intelligence (AI), Machine Learning (ML), and Business Process Management (BPM). The study performs a systematic review of academic literature, categorizing findings according to the BPM life-cycle, to identify research gaps and future directions. By leveraging bibliometric and objective-oriented methodologies, researchers can optimize processes in an organization and stay abreast of the latest developments. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper reviews how Artificial Intelligence (AI) and Machine Learning (ML) are used to improve business process management (BPM). It looks at lots of academic papers to see what’s working well and where there’s room for improvement. This will help people who make decisions about business processes understand how AI and ML can be used to make things better. |
Keywords
* Artificial intelligence * Machine learning
