Demystifying AI for Frontline Work

You still manage your single largest controllable cost with phone trees, spreadsheets, and gut calls, the same way you did twenty years ago, while every other line on the P&L got an intelligence layer years ago.

Join Mohammad Akbarpour, the Walter and Elise Haas Professor of Economics at Stanford’s Graduate School of Business, Professor of Computer Science (by courtesy) at Stanford’s School of Engineering, and Co-founder and Chief Scientist of ReadyOn, for a working session on what AI actually changes in frontline labor operations, and what’s just a prettier version of the same static schedule.

We’ll cover the real difference between machine learning, optimization, and LLMs, where each one belongs in your tech stack, and what it looks like when they run together: forecasting demand before it hits, filling a call-out the moment it happens, building your flex bench instead of renting one, and matching the right mix of full-time, part-time, and flex labor automatically.