Total rewards is quietly becoming an AI story, and most HR organizations are not ready for what that means at the manager level. Korn Ferry’s newly released Global Total Rewards Pulse Survey, drawing on responses from 5,512 organizations across 135 countries, finds that AI is reshaping how companies think about pay, skills, and job architecture even as the people responsible for explaining those changes to employees remain the weakest link in the chain.
The gap is not strategy. It is communication.
Korn Ferry’s July 2026 survey does not describe a company that lacks a rewards strategy. It describes one where the strategy exists on paper and dissolves the moment a manager has to explain it to a direct report. The firm’s own framing is blunt: “Reward communication remains a major weakness, with manager capability emerging as a critical success factor.” AI-driven changes to compensation structures, role definitions, and skills requirements are moving faster than the training managers receive to talk about them.
That distinction matters because it reframes the failure. This is not a data problem or a design problem inside compensation teams. It is a frontline enablement problem, and it sits squarely in HR’s lap because managers are not going to become better translators of AI-driven pay logic without deliberate investment from the function that owns reward strategy.
AI is becoming the operating context for pay, not a bolt-on
The survey’s central finding is a shift in framing: AI is described as “the new operating context for pay, skills, mobility, and job architecture,” not a discrete tool layered on top of existing reward systems. That is a meaningful distinction for HR technology buyers. It suggests that AI’s effect on compensation will not arrive as a single new module in an HCM suite. It will show up as continuous pressure on how jobs are leveled, how skills are priced, and how mobility paths are defined, all of which touch total rewards infrastructure that most organizations built for a slower-moving world.
Korn Ferry also found that most organizations remain in the early stages of maturity in adapting to that shift, even as adoption expands. That gap between AI’s reach into job architecture and the operational readiness of the systems meant to price and communicate that work is where the manager-capability problem originates.
Retention language is shifting from pay to marketability
A second finding reframes what retention conversations sound like inside companies navigating AI-driven skills change. Korn Ferry describes the shift as one from “pay me more” to “make me more marketable,” with career development now weighing as heavily as compensation in how organizations think about keeping talent. That is a direct consequence of AI compressing the shelf life of specific skills: employees increasingly gauge an employer’s value not just by salary but by whether the role keeps their capabilities current.
For reward teams, that means the conversation a manager needs to be equipped to have is no longer just “here is your raise.” It increasingly needs to cover how a role’s skill requirements are evolving, what development paths exist, and why. Few managers are trained for that conversation today, and Korn Ferry’s data suggests few organizations have built the enablement to change that quickly.
Optimism on revenue, restraint on pay
The survey surfaces a tension that reward teams will have to manage directly. Ninety percent of the organizations Korn Ferry surveyed expect revenue growth despite ongoing economic uncertainty, yet projected salary increase budgets for 2027 are flat to slightly lower than 2026 levels. That combination, rising business confidence paired with restrained pay budgets, is exactly the environment where a manager’s ability to explain the reasoning behind a modest raise or an AI-influenced role change becomes decisive for retention.
It also explains why Korn Ferry frames career development as a genuine substitute lever rather than a consolation prize. If budgets will not stretch to match revenue optimism, the credible alternative for keeping people engaged is proof that their skills and role are advancing, which again routes back to whether a manager can articulate that story convincingly.
What this means for the HR leader
Three implications follow directly from the survey. First, manager enablement on reward communication needs to be treated as its own workstream, not an afterthought bundled into a broader compensation rollout. Korn Ferry’s finding that just over four in ten organizations believe managers sufficiently understand reward strategy to communicate it is a signal that most companies are publishing pay guidance managers cannot credibly deliver.
Second, job architecture and skills taxonomy work should be treated as reward infrastructure, not a separate people-analytics project. As AI reshapes what a role actually requires, the systems that price and level that role need to keep pace, or reward decisions will increasingly be made against outdated job definitions.
Third, retention strategy needs an explicit marketability component. If Korn Ferry is right that development is now weighed alongside pay, reward teams that continue to frame retention purely in compensation terms will be answering a question employees are no longer asking in isolation.
What to do next
HR and total rewards leaders evaluating this data should start with an honest audit of manager readiness: not whether pay bands exist, but whether the managers delivering them can explain the “why” behind AI-influenced changes to a skeptical employee. That audit, more than any new compensation platform, is the fastest way to close the gap Korn Ferry has identified. Separate 2027 salary budget data from WTW shows employers are already redirecting flat compensation pools toward specific priorities rather than broad increases, which only raises the stakes for managers who have to explain those tradeoffs clearly.
Source: Korn Ferry
