Traditionally, compensation has revolved around an annual rhythm. A single salary-benchmarking refresh; one compensation-planning cycle; a handful of off-cycle adjustments squeezed in between.
That all made sense when jobs evolved slowly, but the current workforce moves fast. Artificial intelligence (AI) is reshaping roles, skills are quickly changing in value, and pay data from January may be outdated by June.
So, should compensation become always on? Not in the sense of constant change, but in the sense of constant attention.
Compensation was never really once a year
Pay is often an organization’s largest investment, so leaders have always watched it closely. There’s rarely a month when every employee is satisfied with their pay and no one is considering another offer. What’s changing now is how early teams can get ahead of them.
For years, compensation teams have operated reactively — consider a manager raising some concern; the team pulls data from several systems, reconciles spreadsheets, tracks down missing context, and eventually returns an answer. By then, the decision may already be overdue.
Other examples include a new hire reporting to a tenured employee, which can create pay compression. An employee receives an outside offer, prompting a last-minute counteroffer. Instead of anticipating these issues, teams end up correcting them.
The opportunity now is to spot potential problems before they become urgent.
What does “always on” actually mean?
Always-on compensation keeps the annual merit cycle and adds continuous monitoring, tracking the factors that influence pay and responding when the information calls for it.
Some signals (like market movement, emerging roles, and changes in demand for particular skills) come from outside an organization. Others come from within (such as recruiting challenges, pay compression, internal equity concerns, and evolving job responsibilities).
Take a forward-deployed engineer. If demand and required skills are changing rapidly, waiting 12 months to revisit market pay could leave an organization working with outdated assumptions.
It’s a little like a real estate agent advising clients using last year’s mortgage rates. The information may have been accurate then, but it may not be useful today.
With AI, organizations are adding new capabilities to existing jobs, often before they’ve decided how those skills should affect compensation. That makes it harder to rely on job titles and annual benchmarks alone.
When compensation is a year of decisions, hiring offers, promotions, retention adjustments, and internal moves happen throughout the year—and each decision gets current information and the right context, whether or not it falls within a formal compensation cycle.
Where AI fits — and where it doesn’t
AI is particularly useful at the beginning and end of a process. It can help collect information, organize requests, identify missing details, and support routing and approvals. That gives compensation professionals more time for the work in between: analyzing the information, weighing tradeoffs, and making recommendations.
Anyone who has managed an annual compensation review knows the frustration of finally getting all the data together just as the deadline arrives.
Better-connected systems and automation can change that. According to Payscale’s return on investment (ROI) research, the share of customers able to proactively identify employees at risk of leaving because of compensation concerns doubled after adopting Payscale, from 30% to 60%.
At the same time, tech simply doesn’t account for every circumstance behind an employee’s pay. Someone may have joined through an acquisition, transferred from another function, or received a previous adjustment for reasons not immediately apparent in the data—which is why human judgment remains essential.
AI can make information easier to access and analyze, sure, but compensation professionals still need to understand the people and business decisions behind the numbers.
Before investing in AI, fix the fundamentals
With increased focus on AI and automation, it is tempting to begin with technology. However, it is more effective to understand current workflows first.
This requires establishing a few key fundamentals:
- Data and job architecture: reliable employee information, consistent job definitions, and systems that can share information.
- Governance and decision ownership: clear rules about who can recommend, approve, and implement pay decisions.
- Consistent processes: documented workflows that everyone understands and follows.
A useful exercise is to select an activity that occupies significant compensation team time and trace it from start to finish.
Where does the request originate? How many people touch it? Which systems hold the information? Who makes the final decision? And once it’s implemented, does anyone measure the result?
Mapping the process often reveals where time is lost and which steps could benefit from automation.
So what about internal equity and budgets?
Two concerns have historically made organizations hesitant to move away from annual compensation cycles: maintaining internal equity and controlling budgets.
Both deserve serious consideration.
Internal equity.
When organizations make pay decisions throughout the year, they need to understand how each adjustment affects employees in comparable roles. With better access to internal and external data, teams can evaluate potential compression and equity concerns before approving a decision, rather than discovering them during the next annual review.
Budget discipline.
Annual merit budgets provide a predictable structure. Off-cycle spending adds complexity, especially when managers can make adjustments at their discretion.
Now, instead of treating each pay adjustment as an isolated expense, compensation and finance teams can collaborate to assess where additional investment is justified and what the organization expects to achieve.
And as pay transparency expectations increase, organizations must explain how decisions are made and why employees in similar roles may be paid differently.
The next chapter: connecting pay decisions to outcomes
Looking ahead, the greatest opportunity may not be decision speed, but the ability to measure impact effectively.
Automation and self-service will increasingly address routine questions and administrative tasks. Complex decisions will continue to require experienced compensation professionals collaborating with talent acquisition, HR, and finance.
This makes room for something compensation teams have struggled to do for years: connect pay investments to business outcomes through better compensation analytics.
Did a targeted adjustment improve retention? Did a revised salary range help fill a difficult role? Did changes to a compensation program produce the performance improvements leadership expected?
Historically, answering those questions has been difficult because the relevant information lived in different systems. But more connected data creates an opportunity to follow decisions through to their results and use what teams learn to guide future investments. And that’s where the real value of always-on compensation lies.
Annual planning will still have its place. But compensation teams no longer have to wait for the next cycle to understand what’s happening or decide what to do about it.
Hear the full conversation
Should compensation really become always on? And what would it take to get there?
In this episode of Comp and Coffee, Ruth Thomas (Chief Compensation Strategist at Payscale) and Matt Carson (Senior Director of Compensation Strategy and Analytics at UnitedHealth Group) look at the future of compensation cycles, the increasing role of AI, and how teams can get ready for a more continuous approach.
Enjoy the full conversation here.
Ready to make more confident pay decisions throughout the year? Explore the Payscale Intelligence Cloud and see how connected data, technology, and workflows can support your compensation strategy.
