AI-Driven Task Modeling for Workforce Optimization
Oct 01, 2025 at 11:00AM - Oct 01, 2025 at 12:00PMVirtual
Description In this session, Pierre Bouquet will present a workforce management tool developed at the MIT Center for Transportation and Logistics (CTL) that helps organizations assess how artificial intelligence can enhance workforce productivity and reduce costs. The tool enables a detailed decomposition of job roles into tasks, quantifies their associated costs, and models the impact of AI on task execution. By combining task-level exposure analysis with financial data, this framework identifies high-cost activities that are prime candidates for AI acceleration. Drawing on case studies in the transportation sector, Pierre will demonstrate how the tool supports targeted AI implementation and delivers measurable return on investment (ROI). The research provides a structured, data-driven roadmap based on tangible financial metrics, enabling organizations to adopt AI not as a disruption but as a strategic productivity lever.