Interactive, hands-on sessions designed for skill-building and real-time practice. Workshops should include a clear learning objective, live demonstration(s), guided participant activities, and take-home resources such as prompts, templates, worksheets, or step-by-step workflows that attendees can reuse.

Short, practical presentations focused on real-world AI use. Case studies should explain the problem you aimed to solve, the tool(s) you used, how you implemented the solution (workflow/steps), and what outcomes you achieved—along with lessons learned and reusable resources attendees can take home (prompts, checklists, templates, policies).

Formal research presentations that advance AI theory, methods, evaluation, or applied practice. Proposals should clearly state the research question(s), approach or methodology, key findings (or expected contributions), and relevance to real-world challenges or opportunities. Interdisciplinary and community-engaged research is welcome.

Poster presentations are ideal for works-in-progress, pilot programs, prototypes, early findings, or emerging research questions. Presenters should be prepared to briefly explain their work, answer questions, and gather feedback from attendees during the poster session.

Curated conversations that help audiences compare perspectives, surface practical insights, and identify next steps across sectors. Panel proposals must include speaker and moderator names and clearly explain the structure of the session (format, timing, and guiding questions).

Panels may include a “Tell Us What You’re Doing” Lightning Talk Panel format, where each speaker gives a 5–7 minute practical share-out on how they are using AI in their work, followed by moderated discussion and audience Q&A. If proposing a lightning talk panel, submissions should outline the panel flow and what kinds of use-cases or groups will be featured (business, education, nonprofit/community, public sector, etc.).