• Building better scheduling prompts to interrogate updates, meeting notes, reports, and schedule data
• Using AI agents to simplify complex information, support analysis, and surface relevant actions faster
• Identifying practical use cases for reducing manual reporting, spotting schedule impacts, and improving risk visibility

Practical Takeaway: Attendees will leave with practical insight into how peers are experimenting with prompts, AI agents, and automation in real scheduling workflows,  giving them ideas they can take back to their own firms to save time, surface risk earlier, and improve schedule decision-making.