Organizations face increasing pressure to make faster, more informed decisions while maintaining confidence in the numbers behind them. This webinar series examines the people, processes, and technologies shaping the future of estimation. Browse the recordings below to learn how leading organizations are approaching AI, enterprise-scale estimation, and estimation maturity. This page will be updated periodically as the monthly series continues.
The Cost of Getting the Number Wrong
Every major program decision depends on a credible estimate, yet the knowledge required to produce one often resides with a small group of experts. As organizations face workforce transitions and increasing pressure to move faster, AI presents both an opportunity and a risk. In this session, Courtney Smith and Helen Bowen discuss why estimating is fundamentally a decision-making discipline, how organizations can preserve and scale estimating expertise, and what it takes to ensure AI-supported analysis remains transparent, explainable, and defensible.
How Much Should Your AI Development Efforts Cost?
As organizations invest in AI-enabled capabilities, understanding what those initiatives should cost has become a critical business challenge. In this webinar, Brian Glauser and Arlene Minkiewicz explore why traditional software estimating approaches fall short for AI development, the emerging methodologies being used to estimate AI costs, and the key factors that drive investment decisions. The discussion also examines how AI is reshaping the software development lifecycle and what organizations need to produce credible, defensible estimates for AI initiatives.
