Conference Theme
Human–AI Collaborative Intelligence: Designing Responsible Digital Futures
MWAIS 2027 explores the evolving relationship between humans and intelligent systems, emphasizing collaboration, responsibility, and purposeful design. As artificial intelligence becomes increasingly embedded in organizational, social, and technological infrastructures, the future of information systems depends not only on algorithmic capability but also on human judgment, ethical oversight, and thoughtful design.
This conference highlights advances in human-centered AI, agentic systems, and design science research that shape trustworthy and beneficial digital futures. It invites scholars and practitioners to examine how humans and intelligent technologies co-create value through collaborative decision-making, adaptive systems, and responsible innovation.
MWAIS 2027 will serve as a platform for advancing research and practice on designing AI artifacts, governing intelligent systems, and fostering meaningful human–machine partnerships that are safe, transparent, and socially aligned.
Other Topics
Papers will also be accepted on the major IS themes, including, but not limited to, IS Curriculum and Pedagogy, IS Ethics, Data Analytics, Decision Support and Expert Systems, Enterprise Systems (ERP), Information Security and Privacy, AI, Internet of Things, and Big Data.
Examples of topics of interest include, but are not limited to, the following:
- AI and the Future of Work
- Teaching AI in IS Education
- AI-Based Pedagogy and Learning
- Responsible AI and Governance of AI
- IT-Driven Corporate Leadership & Strategy Transformation
- AI-Driven Process Automation
- AI in Enterprise Systems
- Analytics in IS Education
- Digital Transformation Strategies
- IoT-Enabled Business Innovation
- Data Analytics for Decisions
- Advanced Decision Support Systems
- Information Security and Privacy
- Big Data Management
- Digital Trust and Transparency
- Human–Computer Interaction Design
- Sustainability and Green IT
- Cloud-Based Information Systems