AI for Compensation Professionals: Practical AI Applications in Total Rewards
Discover how compensation professionals can leverage AI to work smarter, not harder. This interactive session explores practical applications of generative AI across market pricing, job architecture, salary structures, and employee communications, while addressing key risks and governance considerations.
Presented by Our Panel
Brian Smith (Moderator)
Senior Vice President, Talent Business Line
Gallagher
Brian Smith is a Senior Vice President with Gallagher's Talent Business Line. Brian helps clients navigate human capital strategy and organizational change. With 18 years of Human Capital Consulting experience, Brian has developed deep technical expertise in Compensation, Employee Engagement, HR Technology, Leadership Development, Talent Acquisition Strategy, Mobility, Workforce Transformation and Change Management services.
As a frequent speaker, you can often find Brian on a stage discussing the Future of our Global Workforce, the latest trends in compensation, and best practices in developing a consumer-grade Employee Experience.
Brian holds a B.A. from Indiana University and is deeply involved in multiple charities including Purple Pansies End Pancreatic Cancer and Charlie’s Army Foundation.

Cheryl Strong
Director of Compensation
Insight Global
Cheryl Strong is Director of Compensation Management at Insight Global, bringing more than 25 years of compensation experience to her work as a leader, strategist, and trusted business advisor.
Throughout her career, Cheryl has helped organizations translate complex compensation challenges into practical, business-focused solutions. Her experience spans compensation strategy, job architecture, market analysis, program design, and the development of compensation professionals and teams.
Cheryl is particularly passionate about making compensation easier to understand. She believes great compensation professionals do more than analyze data—they understand the story behind the numbers, ask the right questions, and communicate recommendations in language business leaders can actually use. Known for combining analytical rigor with a practical, people-centered leadership style, Cheryl focuses on helping compensation professionals move beyond simply providing data to becoming confident, thoughtful advisors to the business.
As a speaker, Cheryl brings authenticity, energy, and more than two decades of real-world experience to conversations about compensation, leadership, and the evolving role of the compensation professional.
Shaun Drawdy
Director of Compensation
Saia
Shaun Drawdy is the Director of Compensation at Saia, a national less-than-truckload carrier, where he leads broad-based compensation strategy and programs supporting a workforce of more than 14,000 employees nationwide. In his role, Shaun oversees compensation initiatives across job architecture, salary structure design, incentive compensation, and enterprise compensation programs. Prior to joining Saia in 2023, Shaun held compensation roles with HD Supply, BJ's Wholesale Club, EnerNOC, and J.Jill and holds CCP, CSCP, CECP, and CSRP certifications through WorldatWork.
Gabe Lowy
Senior Manager, Compensation & Organization Design
Lazer Logistics
Gabriel Lowy is Senior Manager of Compensation & Org Development at Lazer Logistics, where he focuses on modernizing how the organization designs and evaluates pay. He holds a Master's degree in Data Analytics and spent three years at Mercer before joining Lazer, bringing a technical, numbers-first lens to compensation work.
Within Lazer's Compensation & Org Development function, Gabriel has applied AI to modernize core comp processes. He is building automated market-benchmarking workflows to speed up pricing cycles, developing a framework for evaluating and improving starting-rate competitiveness against financial constraints, and designing the career-leveling structure supporting Lazer's job architecture initiative. He is also leading a redesign of the company's merit process, introducing a weighted-share methodology in place of a prepopulated matrix, across both corporate and operations populations.
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