Track description n°23

Enterprise Modelling in the Age of Generative and Agentic AI

Track Chairs

Hans-Georg FILL

University of Fribourg, Switzerland

Hans-Georg Fill is full professor for business informatics at the University of Fribourg, Switzerland and head of the Digitalization and Information Systems Group. Prior to his engagement at the University of Fribourg he held positions in Germany and Austria. He holds a PhD and a habilitation in business informatics from the University of Vienna, Austria. He is co-editor of the Department Enterprise Modeling and Enterprise Engineering of the BISE Journal and supporting editor in chief of EMISAJ – Enterprise Modeling and Information Systems architectures – The International Journal of Conceptual Modeling. He has co-chaired Enterprise Modelling tracks at ECIS’2018, ECIS’2019, ECIS’2020, ECIS’2021, ECIS’2022, ECIS’2023.

Robert Buchmann

University Babeș-Bolyai, Romania

robert.buchmann@ubbcluj.ro

Robert Buchmann is a Professor of Business Informatics and Scientific Director of the Business Informatics Research Center at Babeș-Bolyai University in Cluj-Napoca, Romania. He holds a PhD from the same university. He spent three years as a postdoctoral researcher at University of Vienna where he specialized in Enterprise Modelling and Knowledge Engineering. Robert Buchmann has been a program chair for several conferences in these fields – KSEM 2014 and 2023, ISD 2022, BIR 2020/2021, PoEM 2018 – as well as workshop organizer at conferences such as CAISE 2023-2025, BIR 2024-2025 and BIS 2015-2016.

He’s been involved in ECIS either as Associate Editor or as Track Chair for the Enterprise Modelling track between 2018-2023.

Jennifer Horkoff

University of Gothenburg and Chalmers University of Technology

jenho@chalmers.se

Jennifer Horkoff is an Associate Professor at the Interaction Design and Software Engineering division in the Computer Science and Engineering Department shared by Chalmers University of Technology and the University of Gothenburg, Sweden. Dr. Horkoff is currently involved in projects investigating non-functional requirements for machine learning (supported by the Swedish Research Council – Vetenskapsrådet), and the role of requirements engineering and conceptual modeling in automotive perception systems. She is co-editor of the Department Enterprise Modeling and Enterprise Engineering of the BISE Journal. Jennifer has been a co-program chair of RE, REFSQ, ER and PoEM, and has served on program committees and organizing committees of several international conferences (e.g., ICSE, RE, ER, MODELS, CAiSE), and has been a (co-) organizer of several international workshops.

Enterprise Modelling is a standard practice for the design and management of information systems. It aligns business and technical perspectives using a range of conceptual modelling languages that either focus on specific aspects of information systems such as business models, business processes, data, or IT architectures, or enable an integrated view of business and technical aspects, e.g. to design, analyse, and manage an enterprise architecture. Enterprise models may today adhere to international standard formats such as ArchiMate, CMMN, DMN, BPMN or UML, or may be represented using custom-developed frameworks and languages such as 4EM, i-star, Heraklit, MEMO, or e3Value.

Previously, manual and automated approaches have been used to elicit and mine enterprise models from knowledge and data, and to process these models in decision-support, knowledge management or digital transformation use cases. With the advent of generative artificial intelligence and corresponding foundation models, new powerful techniques have emerged that can be integrated with traditional enterprise modelling tasks. These include new approaches for the generation of model fragments from textual descriptions or data, the interpretation of existing models through natural language interaction, or the transformation of models to executable artifacts and actionable decisions. Recent work in this area focuses on agentic artificial intelligence, which uses advanced planning and reasoning to solve problems in a multi-step approach, e.g., for the automated derivation of complex workflows. Applications of combining enterprise modelling with these AI techniques can be found today in many areas, including digital twins, robotics, enterprise architecture and business process management, or systems engineering.From the viewpoint of information systems research, these new developments in enterprise modelling constitute a new perspective on the convergence of traditional enterprise systems and AI agents, which may be investigated using design-oriented, empirical or mixed methods. Therefore, we solicit in this track innovative contributions that address the conference theme from the viewpoint of enterprise modelling in general and in combination with generative or agentic AI. Given the wide utilisation of enterprise modelling, it is anticipated that submissions to this track will contribute significantly to the advancement of knowledge concerning the future impact of AI-based technologies on businesses, management, and society at large.

Track topics

Possible topics include but are not limited to:

Creation and interpretation of enterprise models using generative AI
Conceptualization of new or adaptation of existing enterprise modelling methods for business, management, and the society
Digital innovation and digital transformation driven by enterprise modelling methods
Enterprise modelling for sustainability and human-value driven digitalization
Enterprise architecture management using generative AI
Multi-level enterprise modelling
Enterprise modelling for emerging technologies such as digital twins, blockchain, immersive web, and artificial intelligence
Enterprise modelling for agentic AI
Model transformations and deployments using generative and agentic AI
Neuro-symbolic approaches in enterprise modelling
Evaluating generative and agentic AI in enterprise modelling
Best practices, use cases, and case studies

The topic of enterprise modelling and its interplay with recent achievements in the field of artificial intelligence has recently been successfully covered in workshops (LLM4Modeling’2024, LLM4Modeling@ER’2024, KG4SDSE@CAISE 2023-2025) and in special issues in the BISE journal (https://www.bise-journal.com/?p=2206), the EMISA journal ( https://emisa-journal.org/emisa/article/view/332) and the DKE journal (https://www.sciencedirect.com/special-issue/314222/large-language-models-and-knowledge-graphs-for-semantics-driven-systems-engineering), which attracted quite a number of submissions on this emerging topic. All three track chairs are very engaged in the enterprise modelling community with Hans-Georg Fill and Jennifer Horkoff acting as co-editors of the BISE department Enterprise Modelling and Enterprise Engineering, Robert Buchmann acting as co-editor for the special issues in EMISAJ and DKE and all of them are active in the programme committees (and occasionally in chairing positions) for Information Systems conferences that lean towards enterprise modelling and business informatics: PoEM, ISD, ER, BIR, EMMSAD, CBI.

Therefore, we consider a track on this topic at ECIS’2026 well suited to attract an audience for submitting to this track. Besides interest in academia on this topic, we expect also that the track is attractive to practitioners given the high relevance of enterprise modelling in the age of generative AI.

Publishing Opportunities in Leading Journals

Best papers will be invited to submit extended versions to the BISE Department Enterprise Modelling and Enterprise Engineering. Further accepted papers may be invited for extended versions in EMISAJ – International Journal of Enterprise Modelling and Enterprise Architectures – International Journal of Conceptual Modelling.