The Open and User Innovation (OUI) Society and the Harvard Business School AI Institute cordially invite you to the 23rd Annual International Conference on Open and User Innovation.

For over two decades, the OUI Conference has served as a leading forum for research on how users, communities, and open systems drive innovation. In 2026, as generative and agentic AI technologies become embedded in the infrastructure of work and creativity, the locus of innovation is undergoing a profound transformation. Innovation is no longer driven solely by individual users or open communities, but increasingly by human–AI collectives that depend on large-scale computational infrastructures with real economic, environmental, and societal consequences.

This year’s conference explores how artificial intelligence is reshaping the foundations of open and user innovation. We invite scholars to examine how AI reshapes collaboration, expertise, and governance across users, communities, firms, and teams. Through keynote talks, paper sessions, and interactive discussions, the conference aims to advance theory, evidence, and methods for understanding innovation in an era where human-AI collaboration is becoming a central organizing principle of creative work and organizational decision-making.

The 2026 OUI Conference places a special emphasis on human–AI co-creation as an extension of long-standing traditions in user and open innovation. As generative AI, AI agents, and automated workflows become more prevalent, individuals and groups are not only adopting new tools but actively shaping how these technologies are designed, applied, adapted, and governed within communities, organizations, and innovation ecosystems. At the same time, these developments are opening up new opportunities for AI-enabled methods and measurement in innovation research. 

We particularly welcome research that examines:

• AI-enabled user innovation and open communities, including how participants integrate AI into collaborative practices, coordinate contributions, and develop shared norms, standards, and governance arrangements.
• Agentic and workflow-based innovation, where individuals, teams, or communities design and experiment with AI systems that support problem-solving, ideation, and refinement, often lowering barriers to participation and expertise.
• Evaluation, judgment, and learning in AI-assisted innovation, including how novelty, feasibility, and quality are assessed when AI-generated alternatives are abundant, and how experience, feedback, and organizational context shape these judgments.
• Openness, governance, and value creation, including evolving questions around openness in AI models and data, attribution and credit in human–AI co-creation, and the distribution of value among users, communities, firms, and platforms.
• AI methods and measurement in innovation research, including the use of computational, experimental, and hybrid human–AI approaches to study creativity, problem solving, evaluation, and innovation outcomes.

Consistent with the OUI tradition, the conference welcomes theoretical, empirical, and methodological research spanning established and emerging topics in open and user innovation. We encourage submissions that introduce novel methods, leverage new data sources, examine innovation within organizations and teams, and explore variation across contexts, sectors, and institutional settings.