End of Season 2

This episode explains why most compensation and HR teams are not getting real results from AI, and what to fix first. You will learn how to tell where your organization actually sits on the AI adoption curve, why inconsistent data fields like location and cost center quietly break AI analysis, how token-based pricing may change what HR software costs over the next few years, and what questions to ask a vendor before signing a multi-year deal. The conversation also covers how to choose a small set of data fields to clean instead of trying to fix everything, why a dashboard is not the same as an answer, and why data governance is becoming a job rather than a side task. Useful for compensation leaders, HR technology owners, and rewards teams of one who are being asked to do more with AI without a bigger budget.

Chapters

00:00 – Milestone episode and what keeps a weekly show running 06:00 – Rapid fire questions with the producer and the guest 12:30 – A career path from pre-med to compensation systems 17:00 – Where companies actually sit on the AI adoption curve 21:00 – Why AI hype still outpaces real capability 25:00 – AI mandates and measuring AI use in incentive plans 29:00 – How token pricing works and who absorbs the cost 34:00 – Why messy HR data blocks AI results 39:00 – Choosing which data fields to fix first 44:00 – Dashboards versus metrics that drive action