Management & AI community in Osaka
Management & AI Commons Osaka
Hosted by Toshimichi Homma (Faculty of Business Administration, Osaka University of Economics)
A community in Osaka for people interested in AI, management, organizations, and strategy, connected through monthly lightning talks and work sessions.
What we do
Management & AI Commons Osaka welcomes researchers, students, engineers, and people working in industry— regardless of affiliation or background.
The aim is to create a place where people can share not only finished outcomes but daily trial and error, tools recently tried, themes under exploration, and informal notes.
We meet in Osaka, centered on one lightning-talk session and one focused work session each month.
History
- November 2025: Founded the predecessor community, OUE Unofficial Meetup
- June 2026: Renamed to Management & AI Commons Osaka
Operating principles
Keep participation accessible
Remain open beyond campus and make first-time participation easy.
Welcome work in progress at lightning talks
Share trial and error and unfinished ideas—not only polished results.
Connect across boundaries
Bring together university, industry, tech communities, students, and working professionals.
Continue at a manageable pace
Find conditions for the space to continue without overloading organizers.
Background
The starting point was a sense that Osaka could use a community oriented toward management and organizational theory—not only following generative AI as a technological development, but discussing its effects on work and learning. Part of the motivation was also a wish that universities specializing in the social sciences might still create a little public value beyond teaching and research.
The stronger driver, though, is the simple appeal of such spaces. I have learned a great deal from joining external communities and wanted to make that kind of encounter more accessible—people from different backgrounds sharing trial and error on equal footing.
Researchers, students, engineers, and entrepreneurs bring what they are trying, what failed, and what they do not yet understand. A distinctive aim is to reinterpret changes brought about by generative AI and other new technologies through the lenses of organizations, people, management, and organizational behavior.
Much of the above is retrospective meaning-making. At the outset, it was closer to “this might help research and teaching”—and after watching from the sidelines, I simply wanted to try it myself.