Tehnički glasnik, Vol. 19 No. si1, 2025.
Pregledni rad
https://doi.org/10.31803/tg-20250313154901
Artificial Intelligence in Knowledge Management: Overview and Selection of Software for Automotive Reporting
Bernhard Axmann
orcid.org/0000-0002-0190-6547
; Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany
*
Sanket Pujar
orcid.org/0009-0000-4072-911X
; Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany
* Dopisni autor.
Sažetak
Knowledge Management is essential for modern organizations, enabling the systematic capture, organization, and sharing of knowledge to enhance decision-making and innovation. Traditional Knowledge Management tools, focused on document storage and retrieval, struggle with unstructured data and collaboration, necessitating advanced technological solutions, particularly those incorporating Artificial Intelligence. - Artificial Intelligence-driven Knowledge Management systems revolutionize data handling through automation, and real-time insights. This is particularly valuable in data-intensive industries like automotive, finance, and healthcare. In the automotive sector, annual reports provide critical insights but are complex and time-consuming to analyze and are a complex example and therefore a good test case. Annual reports of 5 major automotive companies BMW, Volkswagen group, Toyota Motors, General Motors and Tesla were selected as the testing dataset. Artificial Intelligence tools, using natural language processing and machine learning, streamline data extraction. - Despite their benefits, organizations face challenges in selecting the right Artificial Intelligence-driven Knowledge Management software due to a lack of standardized evaluation frameworks. This research applies a systematic methodology for assessing such software, considering usability, adaptability, cost-effectiveness, and data privacy compliance, specifically tailored to automotive reporting and gives recommendation for software tools.
Ključne riječi
Artificial Intelligence; Automotive Reporting; Knowledge Management; Software Assessment; Technology Assessment
Hrčak ID:
330655
URI
Datum izdavanja:
1.6.2025.
Posjeta: 605 *