AI Can Inform Your Compensation Strategy, But It Can’t Own It
Authors
Compensation decisions carry real consequences for employees and employers, and as AI tools become more accessible, leaders are right to ask how they fit into compensation planning. But access alone doesn't equal readiness, and enthusiasm shouldn't outpace judgment. So where does AI genuinely add value, and where does human expertise remain non-negotiable? Two of our compensation experts weigh in.
Lisa McKeown
Director, Total Rewards, Nonprofit Practice, OneDigital
Our 2026 Total Rewards Nonprofit Practices Survey shows that organizations are curious about the role artificial intelligence can play in compensation, however adoption remains very limited. Only 2% of employers report actively using AI or advanced analytics to support compensation decisions, and just 10% are piloting tools. A larger share, 32%, is exploring AI’s potential, but more than half of organizations 56% are not using or even considering AI in this space.
The reality is that compensation is too nuanced to be driven by AI alone. Pay decisions require a blend of reliable and relevant market data, internal equity considerations, organizational culture and business insights, and most importantly human judgment. AI can support parts of this process, such as identifying patterns, highlighting potential inequities, or modeling scenarios, of which current analytical tools do incorporate, however it cannot fully account for the organizational culture, leadership philosophy, or individual circumstances that shape responsible pay decisions. Tools that attempt to “suggest” raise amounts often oversimplify these complexities, which is why most employers are not ready to rely on AI as a standalone decision mechanism.
For that reason, organizations considering AIdriven compensation tools should use them alongside existing analytical platforms and proven methodologies. Many established tools, such as CompAnalyst and other marketpricing and payequity platforms, already incorporate AI or machinelearning capabilities in a controlled, transparent way. For example, a platform may use machine learning to improve marketdata matching, identify outliers or inconsistencies, flag potential payequity issues or predict market movement based on historical trends. But AI is operating within strict parameters. It’s not generating raise amounts or overriding compensation philosophy. The organization still controls the rules, the data inputs, and the decisionmaking framework.
Organizations drive compensation strategy by using multiple reliable third-party market data sources that align to their organization makeup, transparent methodologies, and defensible frameworks, elements that are essential for compliance and employee trust. AI can enhance your analysis by offering faster insights and surfacing trends, but it must operate within a structure that ensures fairness, explainability, and accountability. Without that balance, employers risk introducing bias, eroding trust, or making decisions that cannot be clearly justified.
AI does have potential to strengthen compensation practices, but it has not matured to the point of replacing the analytical rigor and human judgment that compensation work demands. The organizations moving most effectively in this space are treating AI as a complement, not a substitute, for the tools and expertise that underpin sound, equitable pay decisions.
Chris Barrientes
Managing Consultant, Compensation, OneDigital
In general, AI tools are a great way to answer some of the broader questions when it comes to compensation such as average merit budgets for a given year or creating a start to a job description. This gives you the information you need to start with the planning process and provides sources for you to dig a little for closer if needed.
For more strategic questions, such has specific compensation philosophy strategies and benchmarking, AI can only deliver part of answer. Organizational specific information as well as pay equity within roles will always be a key part of compensation strategy that goes beyond what AI alone can tell us.
AI is only as good as what information we provide to it. In benchmarking, we all know that job descriptions do not always capture everything that we do. Nuance is needed in talking with management and other in the organization to determine how to benchmark the role and provide the correct peer matching based on what the position does.
Employers using AI in their compensation design provides them with a great starting point and can give them ideas on strategies they may not have considered otherwise. However, a one size fits all approach typically does not work for every company. It is important to tailor the compensation philosophy and tools around your company since every company is different and requires an individual review.
Compensation strategies are a blend of art and science. AI is starting to make the science part more streamlined and provide leaders with a great starting point, but that is only half the battle. The art piece is still only provided by compensation experts who can tailor solutions to understand the specifics of the organization and how to best motivate and incentivize the employees based on specific company goals and values.
AI can enhance your compensation analysis, but only within the right framework. OneDigital’s Compensation Consultants are here to help you move forward with confidence.