TY - JOUR A1 - Axmann, Bernhard A1 - Pujar, Sanket T1 - Artificial Intelligence in Knowledge Management: Overview and Selection of Software for Automotive Reporting JF - Tehnički glasnik N2 - 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. UR - https://doi.org/10.31803/tg-20250313154901 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250313154901 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59480 SN - 1848-5588 VL - 19 IS - si1 SP - 130 EP - 135 PB - University North CY - Koprivnica ER - TY - CHAP A1 - Hohenadl, Tom A1 - Axmann, Bernhard ED - ER, Mahendrawathi ED - Gal, Avigdor ED - Grisold, Thomas ED - Santoro, Flavia ED - Weske, Mathias ED - Dijkman, Remco M. ED - Karastoyanova, Dimka ED - Aysolmaz, Banu ED - Bandara, Wasana ED - Revoredo, Kate T1 - The Future of RPA in the Context of Automation Platforms T2 - Business Process Management: Responsible BPM Forum, Process Technology Forum, Educators Forum, BPM 2025 RBPM, PT, and Educators Forum, Seville, Spain, August 31 – September 5, 2025, Proceedings UR - doi.org/10.1007/978-3-032-02936-2_18 Y1 - 2025 UR - doi.org/10.1007/978-3-032-02936-2_18 SN - 978-3-032-02936-2 SP - 247 EP - 262 PB - Springer CY - Cham ER - TY - JOUR A1 - Agostinelli, Simone A1 - Asatiani, Aleksandre A1 - Axmann, Bernhard A1 - Hannibal, Glenda A1 - Modlinski, Artur ED - del-Río-Ortega, Adela ED - Marrella, Andrea ED - Reijers, Hajo A. ED - Wilde, Adriana T1 - Trust Calibration for RPA JF - Dagstuhl Reports N2 - This working group focused on foundational issues of trust in RPA: How we can conceptualize trust between users and software robots and specify it in a way that, eventually, we can measure that trust empirically. UR - https://doi.org/10.4230/DagRep.14.7.52 Y1 - 2025 UR - https://doi.org/10.4230/DagRep.14.7.52 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64681 SN - 2192-5283 VL - 14 IS - 7 SP - 61 EP - 64 PB - Schloss Dagstuhl CY - Dagstuhl ER - TY - CHAP A1 - Axmann, Bernhard A1 - Cvetić, Biljana A1 - Macowski Durski Silva, Vanina A1 - Trstenjak, Maja T1 - AI Office and Automation Software: Cross Country Survey on Utilization in Logistics T2 - 2025 15th International Conference on Advanced Computer Information Technologies: ACIT’2025, Conference Proceedings UR - https://doi.org/10.1109/ACIT65614.2025.11185844 Y1 - 2025 UR - https://doi.org/10.1109/ACIT65614.2025.11185844 SN - 979-8-3315-9544-9 SP - 261 EP - 266 PB - IEEE CY - Piscataway ER -