Sales Compensation has historically been viewed as a transactional function. Teams build plans, calculate commissions, dispute forecasts, and payout sellers. However, as organizations increase plan complexity, expand plans globally, and tie compensation to critical business outcomes, getting paid accurately is no longer enough. Businesses must have visibility into the risks, behaviors, decisions, and business outcomes

Global organizations are often challenged with a Sales Compensation conundrum. Should incentive plans be standardized across the globe or built locally within each country? The answer is typically neither. Fully centralized plans offer consistency, governance, and scalability. However, they lack awareness of local market conditions. Fully decentralized plans offer flexibility, but create unequal KPIs, fragmented

Most organizations begin their AI journey in Sales Compensation thinking about automation. They want AI to automate commission calculations faster, eliminate manual labor, detect payout errors, or respond to compensation questions with instant answers. Those are all great places to start, but they are just the beginning of what AI can do in Sales Compensation.

Artificial intelligence isn’t going to solve every problem in Sales Compensation. At least not the way many organizations are using it today. Many Comp teams are looking to AI for automation. The ability to instantly calculate commissions across hundreds or thousands of sellers. But that’s just scratching the surface of what AI could do. Automation