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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.21823 |
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| _version_ | 1866916868863819776 |
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| author | Azarijafari, Mohammad Mich, Luisa Missikoff, Michele |
| author_facet | Azarijafari, Mohammad Mich, Luisa Missikoff, Michele |
| contents | Artificial Intelligence agents represent the next major revolution in the continuous technological evolution of industrial automation. In this paper, we introduce a new approach for business process design and development that leverages the capabilities of Agentic AI. Departing from the traditional task-based approach to business process design, we propose an agent-based method, where agents contribute to the achievement of business goals, identified by a set of business objects. When a single agent cannot fulfill a goal, we have a merge goal that can be achieved through the collaboration of multiple agents. The proposed model leads to a more modular and intelligent business process development by organizing it around goals, objects, and agents. As a result, this approach enables flexible and context-aware automation in dynamic industrial environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_21823 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Agentic AI for a New Paradigm in Business Process Development Azarijafari, Mohammad Mich, Luisa Missikoff, Michele Artificial Intelligence Artificial Intelligence agents represent the next major revolution in the continuous technological evolution of industrial automation. In this paper, we introduce a new approach for business process design and development that leverages the capabilities of Agentic AI. Departing from the traditional task-based approach to business process design, we propose an agent-based method, where agents contribute to the achievement of business goals, identified by a set of business objects. When a single agent cannot fulfill a goal, we have a merge goal that can be achieved through the collaboration of multiple agents. The proposed model leads to a more modular and intelligent business process development by organizing it around goals, objects, and agents. As a result, this approach enables flexible and context-aware automation in dynamic industrial environments. |
| title | An Agentic AI for a New Paradigm in Business Process Development |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2507.21823 |