{"ID":2889216,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.21823","arxiv_id":"2507.21823","title":"An Agentic AI for a New Paradigm in Business Process Development","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2507.21823","url_pdf":"https://arxiv.org/pdf/2507.21823v1","authors":"[\"Mohammad Azarijafari\",\"Luisa Mich\",\"Michele Missikoff\"]","published":"2025-07-29T13:58:24Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}