Business process management and enterprise modelling for AI-based digital innovation
Track 7
Track chairs
Robert Buchmann
University Babeș-Bolyai
Djordje Djurica
Vienna University of Economics and Business
Jennifer Haase
Humboldt University of Berlin
Track description
This track invites contributions that explore the dynamic and increasingly interdependent relationship between Business Process Management (BPM), Enterprise Architecture Management (EAM) and Digital Innovation (DI). As digital technologies reshape markets, institutions, and cross-organisational processes at an unprecedented scale, BPM and DI sit at the very heart of how organisations navigate the digital borders that emerge between actors, systems, and societies. We are also looking at how the emerging paradigm of agentic AI reshapes, or benefits from, enterprise modelling and its knowledge engineering methods providing semantically rich contextualisation to business processes.
We particularly welcome studies that investigate how emerging digital technologies—such as process mining, robotic process automation (RPA), generative / agentic AI, blockchain, and the Internet of Things (IoT)—are transforming exploitative and explorative BPM or EAM activities. How do these technologies change the way we design, automate, analyse, and evolve business processes? How do they support organisations in simultaneously optimising existing processes and creating innovative digital solutions? How do they ensure traceability and support decision-making in managing enterprise architectures and their multi-perspective dependencies?
Central concerns of this track are the human-centricity of digital innovation in business process contexts and how the human-AI collaboration can contribute to enterprise engineering, either from design-time or execution-time perspectives. We are keen to attract studies that examine novel forms of hybrid work and co-creation between human actors and non-human, AI-based agents. This includes ethical, regulatory, and design challenges that arise at the intersection of digital innovation and social inclusion. Who benefits from process automation and AI-enabled workflows, and who is excluded? How do algorithmic decision-making, data governance, and platform architectures define participation in digitally-mediated processes? These questions are sharpened by recent regulatory developments such as the EU AI Act, and reflect the broader imperative to critically examine whose interests digital borders serve and whom they disadvantage.
We invite both conceptual and empirical research, including case studies, design science research, and theory-driven investigations, that offer novel insights into the mutual shaping of BPM and DI, or EAM and DI, in the current AI-aware context. Interdisciplinary work that integrates perspectives from Information Systems, Organisational Studies, and Management Science is particularly encouraged, as this helps develop a more holistic understanding of business process innovation or enterprise systems transformations in digitally-enabled organisations.
The conference theme of Bridging Digital Borders resonates directly with this track. Business processes are key mechanisms through which organisations negotiate access, participation, and value creation in digital ecosystems. Enterprise architectures are the engineered contexts in which these business processes run, possibly involving domain specificities in their dependencies and taxonomies of resources. In the age of agentic AI, these can inscribe new barriers: in how platforms are architected, in how automation distributes work, and in how data governance frameworks define who can contribute and who benefits. This track creates a dedicated space to examine both the bridging and bordering functions of BPM, EAM and DI, while opening the discussion towards the transformation brought by agentic AI.
The rise of generative AI, ongoing shifts toward data-centric and automated operations, and the regulatory push toward ethical, human-centered innovation (e.g., EU AI Act) create fertile ground for rethinking how processes are designed, managed, and transformed. Furthermore, as businesses navigate uncertainties stemming from geopolitical tension, environmental concerns, and societal expectations, BPM, EAM and DI jointly offer crucial tools for building resilient and future-ready organisations.
Topics of interest
We welcome submissions on a range of topics, including but not limited to:
- How do digital borders arise through BPM and DI practices, and whose participation and interests do they enable or constrain?
- How does the digital age, in particular DI and digital transformation, challenge established BPM assumptions?
- How can BPM contribute to sustainable digital futures and address grand societal challenges?
- How can organisations design human-centric digital process innovation and innovation processes?
- How can processes be designed to support hybrid co-creation between human and AI agents?
- How can business processes balance efficiency with other value propositions such as sustainability, resilience, or ethics?
- What roles do digital technologies play in enabling digital innovation and transformation in BPM contexts?
- How do technologies like process mining, RPA, and AI support explorative BPM?
- How do we need to rethink the concept of a “business process” in digital platform and ecosystem contexts?
- How can BPM support innovation management and digital transformation processes?
- How can BPM act as a boundary-spanning practice between IS, Management, and Organisational Research?
- How do individuals (designers, managers, workers) interact with digital innovation in BPM contexts?
- How can BPM enhance organisational resilience and adaptability in response to crises or disruption?
- What does ambidextrous BPM look like in practice—and how can it be achieved?
- How do data-driven approaches reshape the way organisations design, test, and scale processes?
- How can Enterprise Modelling support AI-based digital innovation and digital transformation?
- How can Enterprise Modelling support AI-aware governance, risk management and compliance?
- How can Enterprise modelling incorporate sustainability and human-centricity as first class concerns from a knowledge engineering perspective?
- How can agentic AI systems be supported by Enterprise Modelling and model-driven automation?
- How can enterprise models be created, interpreted, implemented or evaluated using generative AI
- What Design Science artifacts (methods, tools) can contribute to the interplay between Enterprise Modelling and agentic AI?Submissions addressing other novel or emerging themes at the intersection of BPM, EAM and DI are also welcome.
Associate editors
Thomas Kreuzer
Universität Bayreuth
Inge van de Weerd
Utrecht University
Daniel Beimborn
University of Bamberg
Adela del Rio Ortega
University of Seville
Claudio Di Ciccio
Utrecht University
Henrik Leopold
Kühne Logistics University
Brian Pentland
Michigan University
Ralf Plattfaut
University of Duisburg-Essen
Luise Pufahl
Technical University of Berlin
Michael Rosemann
Queensland University of Technology
Niels Martin
Hasselt University
Irene Vanderfeesten
KU Leuven
Simone Agostinelli
Sapienza Università di Roma
Jana Rehse
University of Mannheim
Thomas Grisold
Vienna University of Economics and Business
Timo Strohmann
University of Münster
Sandra Zilker
Technische Hochschule Nürnberg Georg Simon Ohm
Banu Aysolmaz
Eindhoven University of Technology
Sandro Franzoi
University of Münster
Anna Maria Oberländer
University of Bayreuth
Iris Beerepoot
Utrecht University
Stephan AIER
University of St. Gallen, Switzerland
Saïd ASSAR
Institut Mines Telecom Business School, France
Ana-Maria GHIRAN
University of Babeș-Bolyai, Romania
Xavier BOUCHER
Ecole Nationale Supérieure des Mines St. Etienne, France
Dominik BORK
Technical University of Vienna, Austria
Peter FETTKE
DFKI, Saarland University, Germany
Aurona GERBER
University of Pretoria, South Africa
Georg GROSSMANN
University of South Australia, Australia
Julius KÖPKE
Alpen-Adria-University Klagenfurt, Austria
Agnes KOSCHMIDER
University of Bayreuth, Germany
John KROGSTIE
Norwegian University of Science and Technology, Norway
MOONKUN LEE
Chonbuk University, South Korea
Andreas OPDAHL
University of Bergen, Norway
Oscar PASTOR
Universitat Politècnica de València, Spain
Erik PROPER
Technical University Vienna, Austria
Kurt SANDKUHL
University of Rostock, Germany
Stefan STRECKER
FernUniversität in Hagen, Germany
Susanne LEIST
University of Regensburg, Germany
Hans-Georg FILL
University of Fribourg, Switzerland
Regina HEBIG
University of Rostock, Germany
Daniel STRÜBER
Chalmers University of Technology and the University of Gothenburg, Sweden
Florian JOHANNSEN
University of Applied Sciences Schmalkalden, Germany
Jennifer HORKOFF
University of Gothenburg and Chalmers University of Technology, Sweden
