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Pequity CEO, Kaitlyn Knopp recently hosted a fireside chat featuring two industry leaders from Roblox: Supriya Bahri, VP of People Operations & Total Rewards, and Swati Bakshi, Director of Compensation Programs, Operations, and Systems. In this conversation, we explored how compensation teams can leverage AI to make their work more efficient and impactful. If you’re wondering how to use AI in compensation and total rewards, here are actionable insights for your team.
Watch the Recording
If you missed the conversation, you can access the on-demand recording here.
1. Start with Clean Data and Strong Foundations
No matter how advanced AI tools become, they’re only as good as the data you provide. Both Supriya and Swati stressed the importance of data governance, structure, and quality control. Before using AI in compensation analysis or automation, make sure your data is clean and well-organized.
2. Use AI for Compensation Analytics
AI-powered compensation analytics tools are one of the easiest ways to start using AI on your comp team. These tools can visualize pay trends, answer questions in real-time, and help HR leaders make faster decisions. However, human oversight is still essential to ensure accuracy and relevance.
3. Continuous Benchmarking with AI
One of the most tedious tasks for compensation professionals is market benchmarking. AI can help automate this process by pulling data from various sources, highlighting significant market shifts, and recommending adjustments. Supriya shared that while this dream solution is still developing, forward-thinking teams are already building parts of it.
4. Comp Cycle Planning Automation
AI can assist with comp cycle planning by suggesting salary adjustments based on eligibility, performance, and market data. Swati noted that while AI can handle the repetitive tasks, human judgment will still be needed for strategic alignment and addressing edge cases.
5. Continuous Learning for Compensation Teams
AI will continue to evolve, and compensation teams need to stay ahead. At Roblox, the comp team invests in learning SQL and Python to automate processes and analyze large datasets. Whether you’re a small or large team, dedicating even an hour a week to learning new skills can make a huge difference.
6. Be Cautious When Choosing AI Vendors
Compensation data is highly sensitive. Supriya and Swati advised using only contracted vendors with strict security protocols. Always test tools with dummy data first and ensure AI services function as agents that interact with your data — not absorb it into external databases.
7. Focus on Real, Repetitive Use Cases
The best applications of AI for compensation teams aren’t flashy — they’re practical. From pay equity monitoring to reducing manual work during comp cycles, AI should solve real problems and free your team for more strategic work.
Conclusion: AI in Compensation is Here — But Human Judgment Matters
AI will undoubtedly change how compensation teams operate, but strategic thinking, data integrity, and continuous learning remain critical. If you’re ready to explore how your compensation team can leverage AI with Pequity, get your demo today.