PoEM2026

Preliminary Call For Papers

Mytilene, Lesvos, Greece, 1 – 3 December, 2026

Abstract registration deadline: July 6, 2026

Submission deadline: July 13, 2026

This year’s theme Rethinking Enterprise Modeling in the Era of AI, encourages reflection on how the field is evolving as AI becomes increasingly intertwined with EM. In particular, it highlights the dual relationship between EM and AI: modeling for AI, where EM supports the design of AI enterprise solutions and modeling with AI, where AI technologies augment the creation of enterprise models. Together, these directions open new opportunities while also raising important questions about trust, responsibility, and sustainability. 

Building on the human-centric perspective of Industry 5.0 and Society 5.0, PoEM 2026 encourages submissions that examine how both emerging and established modeling methods and tools can contribute to responsible, sustainable, and socially aware enterprise systems, as well as report on the current state-of-research and state-of-practice.

List of Topics

PoEM 2026 welcomes submissions that relate to the whole spectrum of enterprise modeling practice. The list of topics includes, but is not limited to:

Foundations of Enterprise Modeling

  • Modeling Theory
  • Tool Development and Support
  • Modeling with AI solutions
  • Meta-Modeling
  • Model Life-cycle Management
  • Quality and Validation of Enterprise Models
  • Active and Smart models
  • Enterprise model explainability and transparency
  • AI-assisted Enterprise Modeling
  • LLMs-enhanced Enterprise Modeling practices
  • AI (LLMs) and Human (Engineers) collaboration for Enterprise Modeling

Enterprise Modeling for Software Development

  • Requirements Engineering
  • Model-Based Software Engineering (MBSE)
  • Agile Systems Development
  • Modeling for AI solutions
  • LowCode and NoCode tools

Enterprise Modeling Languages and Ontologies

  • Conceptualizations, Notations, and Ontologies
  • Multi-Perspective and Multi-Level Enterprise Modeling
  • Business Process Modeling
  • Business Rules Modeling
  • Ontology-driven Enterprise Modeling
  • Knowledge Graphs and Enterprise Modeling

Human Factors of Enterprise Modeling

  • Human-Model Interaction
  • Participatory and Collaborative Modeling
  • End-user modeling
  • Inclusive modeling for digital wellbeing
  • Ethics, fairness and social responsibility

Enterprise Engineering

  • Digital Ecosystems
  • Business intelligence and Data-driven Enterprises
  • Digital Twins 
  • Cyber-physical Systems and IoT
  • Robotics and Advanced Manufacturing Systems
  • AI-driven Enterprises
  • Enterprise Transformation
  • Enterprise Architecture Management
  • Enterprise Strategy
  • Performance and Capability Management
  • Knowledge Management & Engineering

Enterprise Modeling for Resilience and Sustainability

  • Privacy, security and trust
  • Regulatory Compliance & Governance
  • Resilience and Sustainability
  • Green IS
  • Twin Transition (digital + green transformation)

Empirical Aspects of Enterprise Modeling

  • Modeling Practices
  • Case Studies
  • Action Research
  • Experiments
  • Experiences of teaching enterprise modeling

Submission Guidelines

All submissions must be unpublished and not be under review elsewhere. Submissions will be reviewed by at least three members of the Program Committee. At least one author of an accepted paper should register for the conference and present the paper.

Submission page on EasyChair: https://easychair.org/conferences/?conf=poem2026

The papers should be submitted in the Springer LNBIP format, 15 pages maximum (excluding references).

Arrangements are being made to invite selected papers to submit extended versions for a Special Section in SoSym (International Journal on Software and Systems Modeling), published by Springer. 

Policy on the use of Generative AI (adapted from Springer Nature’s AI Authorship Policy)

  • Large Language Models (LLMs), such as ChatGPT, cannot be listed as authors. 
  • The use of an LLM should be properly documented in the Acknowledgements, or in the Introduction of the manuscript. 
  • The use of an LLM (or other AI-tool) for “AI assisted copy editing” purposes does not need to be declared.
  • There must be human accountability for the final version of the text and agreement from the authors that the edits reflect their original work. 
  • This reflects a similar stance taken on the AI generative figures policy.
  • Authors should carry out due diligence to ensure that any AI-generated content in their work is correct, appropriately referenced, and follow the standards as laid out in Springer Nature’sBook Authors’ Code of Conduct.