{"author":[{"first_name":"Katharina","last_name":"Brennig","full_name":"Brennig, Katharina"}],"related_material":{"link":[{"relation":"confirmation","url":"https://aisel.aisnet.org/amcis2025/sig_svc/sig_svc/11/"}]},"title":"Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes","citation":{"ieee":"K. Brennig, “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes,” presented at the Americas Conference on Information Systems, Montréal, 2025.","chicago":"Brennig, Katharina. “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes.” In <i>AMCIS 2025 Proceedings. 11.</i>, 2025.","apa":"Brennig, K. (2025). Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes. <i>AMCIS 2025 Proceedings. 11.</i> Americas Conference on Information Systems, Montréal.","short":"K. Brennig, in: AMCIS 2025 Proceedings. 11., 2025.","ama":"Brennig K. Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes. In: <i>AMCIS 2025 Proceedings. 11.</i> ; 2025.","mla":"Brennig, Katharina. “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes.” <i>AMCIS 2025 Proceedings. 11.</i>, 2025.","bibtex":"@inproceedings{Brennig_2025, title={Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes}, booktitle={AMCIS 2025 Proceedings. 11.}, author={Brennig, Katharina}, year={2025} }"},"user_id":"51905","date_updated":"2025-08-20T07:06:16Z","status":"public","date_created":"2025-08-20T07:03:37Z","_id":"60958","department":[{"_id":"196"}],"main_file_link":[{"url":"https://aisel.aisnet.org/amcis2025/sig_svc/sig_svc/11/"}],"language":[{"iso":"eng"}],"keyword":["Process Mining","Large Language Model","Knowledge Management","Knowledge-Intensive Process","Tacit Knowledge"],"type":"conference","year":"2025","publication":"AMCIS 2025 Proceedings. 11.","conference":{"location":"Montréal","name":"Americas Conference on Information Systems","end_date":"2025-08-16","start_date":"2025-08-14"},"abstract":[{"lang":"eng","text":"Large Language Models (LLMs) excel in understanding, generating, and processing human language, with growing adoption in process mining. Process mining relies on event logs that capture explicit process knowledge; however, knowledge-intensive processes (KIPs) in domains such as healthcare and product development depend on tacit knowledge, which is often absent from event logs. To bridge this gap, this study proposes a LLM-based framework for mobilizing tacit process knowledge and enriching event logs. A proof-of-concept is demonstrated using a KIP-specific LLM-driven conversational agent built on GPT-4o. The results indicate that LLMs can capture tacit process knowledge through targeted queries and systematically integrate it into event logs. This study presents a novel approach combining LLMs, knowledge management, and process mining, advancing the understanding and management of KIPs by enhancing knowledge accessibility and documentation."}]}