Keynotes
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Keynote #1. Hybrid AI: AI systems that collaborate with people instead of replacing them
Date: Thursday, October 8th, 9:30-10:30AM. Abstract: Frank van Harmelen’s talk on hybrid intelligence focuses on AI systems that collaborate with people instead of replacing them. He discusses the importance of building AI systems that can adapt to changes in the team and environment by employing a “theory of mind”, instill moral values, and be explainable. The talk outlines a research agenda for hybrid intelligence (which is substantially different from the research agenda for autonomous AI), presents early results from researchers worldwide into hybrid intelligence and presents a variety of use-cases for Hybrid Intelligence in different sectors of society. Speaker: 
Frank van Harmelen is professor of Artificial Intelligence at the Vrije Universiteit Amsterdam.
In earlier years, Frank contributed significantly to Linked Data and Semantic Web techniques: he is one of the co-designers of the Web Ontology Language OWL, he co-authored the first academic textbook of the field (the Semantic Web Primer), and he was one of the architects of Sesame, one of the first RDF storage and retrieval engines and earning the 10-year impact award at ISWC 2012. Since 2020, Frank has been co-leading the Hybrid Intelligence Centre, a 10 year, 20m€ collaboration across 7 Dutch universities where 75 PhD students and an equal number of academic staff investigate Hybrid AI systems that collaborate with people instead of replacing them.
Frank is a fellow of the European AI Society EurAI, a member of the Academia Europaea, and a member of the Dutch Royal Academy of Sciences (KNAW). He received the EurAI Community Services Award, and he is a guest professor at the Wuhan University of Science and Technology (WUST) in China.
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Keynote #2. AI or Not AI: From Uncertainty To Fact and the Role of Conceptual Modeling.
Date: Thursday, October 8th, 1:00-2:00PM. Abstract: In many areas of science and practice, generative AI is currently regarded as a paradigm shift. This means that existing boundaries are being overthrown or must at least be reconsidered. However, this comes at the cost of uncertainty and the necessity to validate generated results. In this talk, we will analyze these developments from the perspective of business informatics and examine the implications and trade-offs. Our analysis will encompass two distinct dimensions: training and education, as well as research and product innovation, and will be conducted from the perspectives of academia and industry. By revisiting the emergence of uncertainty in the history of abstraction, we aim to identify potential anchors of stability and illustrate the potential role of conceptual modeling in this context. Speaker: 
Hans-Georg Fill is a full professor for business informatics and vice president of the department of informatics at the University of Fribourg, Switzerland. He has received his PhD and habilitation from the University of Vienna, Austria. He has more than 15 years of experience in conceptual modeling and enterprise modeling both in academia and industrial research projects. He is supporting editor-in-chief of Enterprise Modeling and Information Systems Architectures – International Journal of Conceptual Modeling and speaker of the SIG Modeling of Enterprise Information Systems (MobIS) as well as deputy speaker of the Cross-sectional Technical Committee on Modeling (QFAM) of the German Informatics Society (GI). His current research interests include conceptual modeling and generative AI, spatial conceptual modeling, and information systems engineering for resilience.
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Keynote #3. Model your Business. Architect its Intelligence. How Enterprise Digital Twins Close the Contextual AI Gap.
Date: Friday, October 9th, 9:00-10:00AM. Abstract: Organisations are facing enormous pressure to change — faster, smarter, and with fewer resources. Volatile markets, shrinking margins, ever-tightening regulation, and the disruptive force of Generative AI are reshaping industries simultaneously, leaving little room for decisions based on gut feeling or fragmented information. This is exactly where enterprise models prove their worth — and where their role is growing, not fading. A model-based Digital Twin of the Organisation — integrating Business Process Management, Enterprise Architecture, and Governance, Risk & Compliance — serves as the shared language connecting human judgment with intelligent systems, and business strategy with IT reality. Built on this foundation, organisations can move beyond static documentation: modelling the enterprise as it is, analysing the impact of change before it happens, simulating alternatives, and ultimately predicting outcomes with confidence. At the same time, AI amplifies every step — assisting in model creation, enriching context, and generating decision-relevant insight at a scale no human team could match alone. The implications for enterprise modeling are clear: Hybrid Intelligence does not emerge from AI alone — it emerges from the shared language of enterprise models, where human insight and machine reasoning find a common structure to think, decide, and transform together. Speaker: 
Dr. Christian Lichka is a board member of BOC Group, an international leader in Enterprise Management Systems, where he spearheads global marketing, partner ecosystems, specialized compliance products and cloud-integration innovations. As founder of BOC Switzerland, he scaled the start-up into a market-shaping provider of Business Transformation, IT Management, and Compliance solutions. Holding a PhD in Business Informatics from the University of Vienna, Christian has spent two decades teaching executives and graduate students across Europe, blending strategy, process management, GRC, and agile leadership. Beyond academia, he regularly shares and challenges transformation insights in client engagements at national and international levels. His current work focuses on steering organizations through large-scale change, balancing entrepreneurial drive and technological innovation with modern compliance demands – insights he will distil in his keynote.
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Keynote #4. How to combine humans and AI smartly.
Date: Friday, October 9th, 1:00-1:45PM. Abstract: AI is changing work and hence human behavior at work. As research shows, the impact on human work behavior can be negative. For example, humans tend to accept suboptimal results from AI without critically questioning them. As they stop thinking, their own thinking skills are no longer trained, and hence their expertise erodes. To notice this is difficult for them, since work is completed more quickly with AI and the results appear more professional. As a consequence, the subjective sense of competence increases, while the actual competence declines. At work, this causes an increase in errors. AI can also hollow jobs, i.e. erode the essence of work, as for example coders report. When AI takes over the creation of programs and humans are left only to supervise and monitor, the job loses its essence. Yet it is this essence that makes the job interesting in the first place. It involves solving novel problems and developing implementation strategies. As a result, those affected report a loss of motivation, cognitive overload, and a decline in job satisfaction. This, too, contributes to an increase in error rates. Companies must prevent such negative effects of AI if they rely on the motivation and commitment of their employees as well as on their professional expertise and practical experience. This can only be achieved if humans, technology, and organization are considered in mutual interdependencies and jointly optimized by design. For this, the School of Applied Psychology FHNW is developing criteria and methods. The keynote presentation reports from corresponding projects as e.g. AI4SME. Speaker: 
Prof. Dr. Toni Wäfler is lecturer and researcher at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW), School of Applied Psychology (APS), where he established the Institute “Humans in Com-plex Systems (MikS)”. The Institute conducts research projects in the domain of human factors, soci-otechnical system design, occupational health, safety, and security. After studying psychology, busi-ness, and computer sciences at University of Zürich, he worked as a researcher at ETH Zürich. His main research topics include sociotechnical system design, human-machine function allocation, hu-man-AI teaming, and digital transformation.
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