AutoMeet: a proof-of-concept study of genAI to automate meetings in automotive engineering

• URL: http://arxiv.org/abs/2507.16054v1
• Date: Mon, 21 Jul 2025 20:44:53 GMT
• Title: AutoMeet: a proof-of-concept study of genAI to automate meetings in automotive engineering
• Authors: Simon Baeuerle, Max Radyschevski, Ulrike Pado,
• Abstract summary: Generative Artificial Intelligence (genAI) models like Large Language Models (LLMs) exhibit an impressive performance on spoken and written language processing.<n>This motivates a practical usage of genAI for knowledge management in engineering departments.<n>We implement an end-to-end pipeline to automate the entire meeting documentation workflow.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In large organisations, knowledge is mainly shared in meetings, which takes up significant amounts of work time. Additionally, frequent in-person meetings produce inconsistent documentation -- official minutes, personal notes, presentations may or may not exist. Shared information therefore becomes hard to retrieve outside of the meeting, necessitating lengthy updates and high-frequency meeting schedules. Generative Artificial Intelligence (genAI) models like Large Language Models (LLMs) exhibit an impressive performance on spoken and written language processing. This motivates a practical usage of genAI for knowledge management in engineering departments: using genAI for transcribing meetings and integrating heterogeneous additional information sources into an easily usable format for ad-hoc searches. We implement an end-to-end pipeline to automate the entire meeting documentation workflow in a proof-of-concept state: meetings are recorded and minutes are created by genAI. These are further made easily searchable through a chatbot interface. The core of our work is to test this genAI-based software tooling in a real-world engineering department and collect extensive survey data on both ethical and technical aspects. Direct feedback from this real-world setup points out both opportunities and risks: a) users agree that the effort for meetings could be significantly reduced with the help of genAI models, b) technical aspects are largely solved already, c) organizational aspects are crucial for a successful ethical usage of such a system.

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