T2: Information Systems Modeling and Business Models

It appears that “digital” is all around us, both in our personal and work lives. The growing popularity of approaches like model-driven development and low-code development, which involve code generation and model interpretation or generation by AI, has made modeling more relevant than ever in information systems development.

Professionals have sometimes been reluctant to create models as part of their work but that attitude is slowly changing. In agile information systems development, the traditional reluctance to use software models has been replaced by a more practical approach, recognizing the value that models derived from user stories and other requirements artifacts can provide in ensuring the timely delivery of high-quality systems. Data scientists are also increasingly using domain models to make sense of the data in their pipelines, which are used to build, train, evaluate, and deploy machine learning models. Overall, there is a renewed appreciation for the role of information system models, including business models, conceptual or domain models, requirements models, and software models, leading to the question of how these modeling approaches can be improved or innovated to better support new approaches to information systems development.

Track topics include (but are not strictly limited to):

• Model-driven information systems development
• Conceptual modeling for information systems development
• The use of models in agile ISD
• Domain modeling for data analytics applications
• Business models
• Information systems requirements modeling
• The transformation of models into code
• The transformation of text into models
• Dialogic approaches to information systems modeling
• Naturalistic information systems modeling environments
• Ontology-driven conceptual modeling
• Enterprise modelling
• Reference models for information systems development
• Generic information system models
• Reusing information system models
• Storing information system models in repositories
• Assessing the quality of information system models
• IT Governance and ICT Service Business Models
• IT Governance and ICT Service Business Models
• Micromobility Business Model
• Social Media Business Model
• Industry 5.0 for Business Model 5.0
• Cloud Computing Business Models
• Digital Revenue Model
• AI/ML-based Business Models
• Business Models for Metaverse, VR and AR
• Business Model for Drone Swarm Management
• ISD in Crisis preparedness and management

T3: Lean and Agile Software Development

The objective of LASD is to enhance the state-of-the-art in lean and agile software development and disseminate best practices, accompanied by stories of both successful and challenging transitions and adaptations to the evolving work environment and advancements in technology.

Since its inception in 2017 as part of the FedCSIS Conference Series, LASD has grown into a prominent research forum for the Agile community. During the pandemic, LASD operated as a standalone online conference, and in 2023, it became an official track within ACM SAC. In 2024, LASD expanded its international reach by being held twice — at SAC and later at ISD — further establishing itself as a bridge between the Software Engineering and Information Systems communities.

Agile and lean software development are industry standards, but transitioning to an Agile mindset remains challenging. Projects often require tailoring Agile methods to fit specific contexts, but this process is complex due to the interdependent nature of practices in frameworks like Scrum. The pandemic-driven shift to remote and hybrid work has added new challenges, forcing co-located teams to adapt to their communication and collaboration methods. Organizations must now innovate beyond traditional Agile practices, which lack explicit remote work guidelines, to maintain team effectiveness in virtual environments. Furthermore, the ongoing return-to-office debates and the stabilization of hybrid work models have created new research opportunities around optimizing Agile ceremonies and collaboration patterns for permanently distributed workforce configurations.

Scaling Agile to large, distributed, and multi-team projects continue to be a pressing topic. While frameworks like SAFe, LeSS, and Nexus have emerged to address the challenges of scaling, their adoption is often fraught with difficulties. Organizations frequently report issues such as framework misalignment with company culture, disruptions to management structures, and the inability to fully implement all elements of predefined frameworks. These challenges underscore the need for both practical guidance and theoretical research to support large-scale Agile transformations.

The emergence of AI-powered autonomous coding agents and multi-agent systems presents new paradigms for human-AI collaboration within Agile teams, raising questions about pair programming with AI, the evolving role of developers as orchestrators, reviewers, and accountable decision-makers, and the governance mechanisms needed to integrate agentic work into Agile planning, quality assurance, and continuous delivery. As organizations move from experimentation with AI assistants toward more systematic adoption, further research is needed on how Agile teams can balance speed, autonomy, transparency, trust, and human responsibility in increasingly AI-mediated software development practices.

Track topics include (but are not strictly limited to):

• LLMs and Agentic AI for improved efficiency of Agile teams
• Agile tools for AI-assisted software development and testing
• Agentic AI and autonomous coding assistants for Agile teams
• Human-AI collaboration in Agile teams
• Prompt engineering and AI integration in Agile workflows
• Agile teams in the post-COVID era
• Distributed teams in Agile Software Development
• Scaling agile methods
• Tailoring agile methods
• Balancing agility and discipline
• Lean and agility at the enterprise level
• Value stream management and flow-based delivery
• Challenges of agile project management
• Innovation and creativity in agile teams
• Agile approaches for requirements engineering and UX research
• Collaborative games in Software Process Improvement
• Challenges of migrating to lean and agile methods
• Lean and agile coaching
• Agile gamification
• Measurement and metrics for agile projects, agile processes, and agile teams
• Integrating DevOps, Agile, and CI/CD for end-to-end software development and deployment
• Agile development for safety systems
• Agile approaches for sustainable and green software development
• Governance, verification, and trust in AI-assisted and agentic Agile software development
• Human oversight, review practices, and quality assurance for AI-generated software artefacts
• Socio-technical implications of AI-mediated Agile work, including developer roles, skills, and team autonomy

T4:  AI and Data Science for ISD

One of the key issues related to Information Systems Development (ISD) is the effective transformation of large amounts of data into useful knowledge, consistent with the declared objectives and the expected, measurable outcomes. The central role in addressing this issue is played by modern information systems, providing a variety of intelligent services for that purpose.

Considering a perspective of ISD, the main concern of this track is to focus on the use of data science (DS), machine learning (ML), artificial intelligence (AI), data mining (DM), data analysis (DA) and related paradigms as an integral part of the ISD life cycle. These paradigms are to be treated as a coherent set of theories, methodologies, processes, architectures and technologies that guide the analysis, design, implementation and evolution of modern information systems. Their systematic integration within ISD enables the transformation of raw data into meaningful and useful information and knowledge embedded in system functionality, thereby improving information management, decision support and value creation in business and research organizations.

The main goal of this track is to address open questions and real potential for various applications of modern DS & ML approaches in ISD, particularly to design, develop, and deploy effective software services that support information management across different organizational information systems. Within contemporary ISD practice, many information systems are explicitly developed to deliver DS & ML–based services that enable data description, analysis, clustering, classification, evaluation, prediction, and visualization. These services encompass DS & ML approaches applied to both structured and unstructured data, including text, images, time-series, and multimedia data, as well as computer vision and natural language processing methods.

The development of information systems increasingly relies on advances in AI. DS & ML approaches can be widely applied in software engineering and ISD, supporting the analysis and evaluation of complex software, development processes, and system configurations, predictions related to software quality and project management. As a result, solutions employing DS & ML methods are becoming an integral part of modern ISD practices, contributing to more reliable, efficient, and cost-effective software development processes.

Track topics include (but are not strictly limited to):

• LLMs – theoretical aspects, architectures and applications supporting ISD
• DS & ML – theoretical and practical aspects applied to ISD processes
• DS & ML – applications in System Engineering across various problems and research domains
  • Business analytics and decision making
  • Customer support and service management
  • Quantitative finances and operations
  • Quality management and standardization
  • Business process automation
  • Project management
  • Production management
  • Software engineering and testing
  • IT operations and managing IT infrastructures
  • Information Systems
  • Research projects
  • Interdisciplinary applications of information systems integrating AI-driven insights across multiple domains
• Ethical and regulatory implications of AI in ISD
• ISD as a process in DS & ML complex projects

T5: IS for Digital Transformation

The track places a particular emphasis on issues related to Digital Transformation and Information Systems Methodologies. The primary objective is to foster scholarly discussion on a diverse set of theoretical, methodological, and practical challenges associated with digital transformation, with special attention given to developments emerging in the era of artificial intelligence. Contributions that address methodological perspectives in information systems research, including novel approaches, frameworks, and empirical methods as well as legal and ethical aspects are especially encouraged and welcomed this year.

The thematic focus of the track encompasses the application of digital transformation across multiple domains, including public administration, crisis preparedness and management, private and non-profit organizations, and enterprises undergoing significant technological and organizational change. Particular interest lies in examining how digital technologies, data-driven approaches, and AI-enabled solutions are shaping organizational processes, governance structures, and innovation practices.

Track topics include (but are not strictly limited to):

• Artificial Intelligence–Driven Digital Transformation
• Advanced Data Ecosystems and Big Data Architectures
• Augmented Business Intelligence, Analytics, and Intelligent Data Platforms
• Digital Transformation Strategies for Small and Medium-Sized Enterprises (SMEs)
• Cloud-Native, Edge, and Serverless Computing
• Cybersecurity, Privacy, and Trustworthy Digital Systems
• Data Lakes, Lakehouses, and Real-Time Data Platforms
• Applied Data Science for Digital Transformation
• Deep Learning and Foundation Models
• Digital Services, Platforms, and Service Ecosystems
• Digital Twins and Cyber-Physical Systems
• AI-Enabled Government 4.0 and 5.0
• Industry 4.0 and 5.0: Smart, Sustainable, and Human-Centric Manufacturing
• Internet of Things (IoT), Edge Intelligence, and Sensor Networks
• Machine Learning Applications in Digital Transformation, Including Sentiment and Emotion Analysis
• Mobile, Ubiquitous, and Context-Aware Applications
• Intelligent Process Management and Automation in the Digital Era
• Process Science, Process Mining, and AI-Augmented Process Analytics
• Digital Project and Product Management in Agile and AI-Driven Environments
• Smart, Sustainable, and Resilient Cities
• Social Media Analytics, Online Communities, and Digital Engagement
• Social Networking Platforms and Digital Collaboration Technologies
• Web Intelligence, Knowledge Discovery, and Large-Scale Text and Web Mining
• Human-Centered User Experience (UX) and Interaction Design
• Extended Reality (XR): Virtual, Augmented, and Mixed Reality
• Innovation, Value Creation, and Organizational Transformation with Generative AI
• Intelligent and AI-Driven Information Systems for Healthcare and Medicine
• Legal and Ethical Aspects of ISD
• Digital transformation of crisis preparedness and management

T6: Learning, Education, and Training for ISD

This track focuses on a broad area of information systems (IS) development for education and training. The goal is to create a forum of discussion and dissemination of novel, relevant, and rigorous research, as well as professional and practical experiences that address the challenges and opportunities in the education of IS specialists. As in previous years, we strongly encourage contributions to advance the foundations of IS teaching and learning methodologies.

The track invites submissions on (1) theoretical foundations and best practices related to the design, implementation, evaluation, adoption, and use of IS in formal and informal educational contexts in IS development; (2) theoretical and empirical contributions to understanding and shaping methodological and educational aspects of IS development; and (3) methodological contributions to IS development and education.

Track topics include (but are not strictly limited to):

• Activity theory approaches to IS development education
• Computer-supported collaborative learning
• Creativity and innovation in IT-based education
• Curriculum development, including local implementation of AIS/IEEE/ACM model curricula
• Digital literacy
• IS Education Management
• Generative AI and AI assisted tools in IS education
• Educational systems design, development, and evaluation
• HCI issues in IS development for education
• Integrated IS applications in education
• Learning platforms including mobile apps and MOOCs
• Longitudinal and comparative studies of learning
• Open educational resources in IS development education
• Serious games, gamification, and virtual worlds for learning
• Social and crowd computing in educational contexts
• Social media-supported learning
• Socio-constructivism in IS development education
• User-generated content in IS development education
• Work-integrated learning

T7: Game Design, Game Development, and Game Management in ISD

Worldwide the digital games industry is huge. In Sweden the countery of the organizers of ISD2027 there are more than 1000 companies dealing with games with a turnover of over 35 billion SEK (approximately 3.2 billion EURO [20290929]). Several efforts, such as the Game Development Research Center (https://www.his.se/en/about-us/collaboration/game-development-research-centre/) a research project financed by The Knowledge Foundation (https://www.kks.se/en/article/sweden-establishes-research-hub-for-game-development/) highlights the need for research on game development including dissemination of results.

The track invites submissions on game design, development and management in relation to artificial intelligence, graphics, tools and business development including business management.

Track topics include (but are not strictly limited to):

• Tool efficiency and tool development for game development
• Player testing and automated testing in the development process
• Technical and non-technical debt
• Agentic AI and autonomous coding assistants for game development teams
• Human-AI collaboration in game development
• AI coding and game development
• Balancing creativity and coding practices
• Scaling game development teams
• Player-centric development techniques and methods
• Usability/Accessibility evaluation methods to guardrail game development
• Design after use (player involvement post-launch, feedback loops)
• Involvement of players in idea generation and processes for idea management 
• Ownership issues and player-centric design and development methods 

T8: General Topics in ISD

The information systems scientific area continues to change at an almost instantaneous pace, making it challenging to keep up with the latest trends. Nevertheless, understanding these latest technological trends is significant for businesses and individuals who want to stay in the vanguard. The dynamic scientific area of Information Systems (IS) is full of new technologies, tools, software frameworks, and innovative ideas. Being so, it is important for researchers as well as for professionals to be informed of these recent emerging trends and all that they entail.

Today, the IS discipline faces new challenges. Emerging technologies as well as matured approaches to the social, technical, and developmental role of IS in new areas provide a new context for the evolution of the discipline over the next few years.

We look forward to receiving research papers from multidisciplinary areas that intersect with IS, specifically, but not restricted to, main trends in the context of Information Systems development and application field:

• Edge computing
• Quantum information science
• Distributed ledger technology
• Augmented reality in the ISD context
• Metaverse-related ISD
• Low-code development platforms
• Ontologies and Knowledge Graphs in ISD
• Systems of systems perspective in ISD
• Socio-cyber-physical systems
• Digital Twins in the ISD context
• ISD in Geospatial contexts
• Information Technology acceptance
• Generative AI in ISD
• SysML v2 in IS engineering
• Systems engineering tools for IS design, implementation, and maintenance
• Advanced programming languages for ISD
• Multi-domain integrated Information Systems
• Multi-mode Information Systems
• ISD in the context of capability management
• ISD in the context of knowledge management
• ISD in organizational networks
• ISD for mergers and acquisitions
• ISD in developing economies
• ISD for Social Good
• Legal aspects of ISD
• Information systems requirements standardization
• Competence frameworks for ISD
• Current challenges regarding the role of ISD in organizations

International Steering Committee

Former Members