AI is changing how organizations analyze compensation, identify risk, and make pay decisions. But greater intelligence does not automatically lead to better outcomes.
For Compensation and Total Rewards leaders, the opportunity is significant. AI can surface patterns across complex workforce data, strengthen decision-making, and help organizations move from periodic pay equity reviews toward more proactive oversight. Yet the same technology can also reinforce historical inequities, introduce new risks, and make already complex pay decisions harder to explain.
This session explores the intersection of AI and pay equity, including where AI can create meaningful value, where human judgment remains essential, and what organizations need to put in place to use AI responsibly. Attendees will gain a practical framework for evaluating AI through the lens of equity, transparency, and defensibility as compensation becomes increasingly technology-driven.
As the Executive Vice President of Products and Revenue at Trusaic, Anuj is one of the company’s principal product strategists and oversees ongoing expansion efforts into global markets. His vast experience in customer service and data analytics has enabled him to help develop a comprehensive Pay Equity software solution with the customer experience at its core.
He holds a Bachelors of Engineering degree in Computer Science, and a Masters of Science in Financial Engineering from Claremont Graduate University.
Mark is responsible for evolving Trusaic’s analytics regarding pay, diversity, and data consolidation processes as the company continues to scale and expand its robust data and analytic solutions. He brings over two decades of experience in statistical analysis to Trusaic, both as a faculty member at UCLA and within class-action litigation, where he provided oral and written testimony regarding statistical modelling.
Mark was formerly a Senior Economic Consultant for the Harris Economics Group, where he provided written and oral expert testimony regarding the interpretation of empirical analyses. He directed data cleaning and the construction of empirical models, among other responsibilities. Mark also worked as a Senior Economist for Econ One Research, Inc., and taught Econometrics as an Assistant Professor at UCLA.
He earned a Ph.D. in Economics from the University of Rochester, an M.A. in Finance from The Wharton School, and a B.A. in Physics from the University of Pennsylvania. He is a member of the American Economic Association and the Econometric Society.
