Cut wasted office hours with AI scheduling, occupancy & workflow automation

Executive Summary

Many hybrid organizations waste office hours because there is poor visibility into who will be in the office and manual, error-prone scheduling; facilities managers, HR teams, and team leads at companies of 50–10,000 employees face underutilized desks, double-booked rooms, and time lost coordinating ad-hoc visits. Client pilots and academic studies often show 10–30% of potential in-office productivity is lost to these frictions — searching for space, resolving conflicts, and handling last-minute maintenance. You could build an AI-first platform that fuses low-cost IoT occupancy sensors and badge/calendar feeds with an LLM-driven workflow engine to automate desk/hot-desk allocation, room booking, maintenance dispatch, and predictive capacity planning, exposed via natural-language admin flows so non-engineer staff can create and tune automations. Targeting the $25B global workplace and facility software TAM (roughly 5M potential office customers x $5K ACV) makes this a commercially meaningful opportunity today, and the opportunity is reinforced by a market score of 92/100 and revenue potential of 88/100 given hybrid work norms, cheaper sensors, and capable LLMs. To stand out you’ll need three concrete differentiators: privacy-preserving sensor fusion and edge processing to address data sensitivity, turnkey integrations with major calendar/badge systems to minimize deployment friction, and an automation-first UX that executes actions (reassigning desks, notifying staff, dispatching cleaning) rather than just surfacing analytics. Be honest about challenges: enterprise sales cycles, hardware logistics, integration complexity, and the need to prove ROI (expect 12–18 months to close larger deals) are real barriers, but with rigorous metrics for occupancy uplift and hours reclaimed, a focused team can validate product‑market fit and capture a defensible slice of this medium-competition market.