How AI Can Improve Manager-Employee Pay Conversations

Compensation professionals can spend months developing salary structures, evaluating market data, conducting pay equity analyses and allocating merit budgets, according to Sean Luitjens, the vice president of product strategy and partnerships at Salary.com, a compensation software, data and services company.

“But employees experience these efforts through a conversation with their manager,” he said. “That’s where even the strongest compensation strategy can succeed — or completely fall apart.”

To better equip managers, HR can leverage artificial intelligence (AI) to transform pay conversations with data-backed talking points, unbiased performance summaries and interactive role-play tools. By reducing manual prep work, such technologies can allow managers to focus on delivering clear, empathetic and personalized compensation explanations.

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• Understanding AI’s Role and Impact in Compensation Talks

AI as a Coach

Managers often struggle with compensation discussions because they’re trying to balance market data, internal equity, performance, budget constraints and individual circumstances all at once, said Ruth Thomas, a chief compensation strategist at compensation software and data company Payscale.

Instead, AI can help synthesize that information into something tangible that managers can use in their pay conversations with employees.

“For example, AI can generate tailored conversation guides that explain where an employee sits within their pay range, summarize relevant market movement, highlight the employee’s rewards package and suggest responses to common questions,” Thomas said. “That gives managers more confidence and consistency while still allowing the conversation to remain personal.”

AI also can help elevate pay discussions from reactive debates about numbers to more informed conversations about value, performance, growth and rewards, said Tom McMullen, a senior client partner at consulting firm Korn Ferry.

“Employees are increasingly using AI tools to research salary benchmarks, compensation practices and even scripts for negotiating raises before they ever speak with their manager,” he said. “HR can leverage AI in the same way — equipping managers with conversation guides, explanations of pay structures, summaries of market trends and answers to frequently asked compensation questions.”

A manager also might use AI to explain why a high performer is positioned below a range midpoint, how rewards extend beyond base salary or why external market data may differ from internal compensation decisions.

“The goal is not to replace human judgment, but to help managers communicate with greater consistency, confidence and transparency,” McMullen said.

AI as a Role-Play Partner

AI can serve as a practice partner, allowing managers to role-play challenging scenarios, such as responding to questions about market competitiveness, pay equity or salary increase decisions — and then receive feedback on their messaging, said Jennifer Hassrick, the vice president of career and compensation strategies at Segal, an HR and benefits consulting firm.

“AI will continue to become more deeply embedded in compensation processes, allowing HR teams to move faster,” she said. “As a result, the technical ‘math’ of compensation will become easier, shifting greater focus to the ‘art’ of compensation — communicating decisions, building trust and helping employees understand the rationale behind pay programs.”

McMullen noted the future of pay transparency isn’t about more data — it’s about better explanations and conversations about pay.

“The biggest shift coming is that compensation knowledge is becoming democratized,” he said. “What was once considered insider HR knowledge — market pricing, salary ranges, reward philosophy and pay structures — is now available to employees in seconds through AI.”

McMullen said, as a result, HR leaders should expect employees and candidates to arrive at compensation discussions more informed, more confident and more willing to challenge pay decisions.

Hassrick agreed, noting how employees are increasingly asking “why” questions — not just about their own pay, but about broader pay practices.

“This presents a valuable opportunity to build trust and credibility,” she said. “AI can support that effort by helping managers prepare for compensation discussions, anticipate questions and deliver more consistent, personalized explanations while reinforcing the organization’s compensation philosophy.”

AI as a Translator

AI can help translate compensation jargon into language employees understand, added Luitjens.

“HR professionals are comfortable discussing concepts like compa-ratio, salary range penetration or market positioning,” he said. “But AI can convert technical language into plain English, helping managers explain not just what the decision was, but more importantly, why it was made.”

When one manager clearly connects compensation to performance, growth and the organization’s pay philosophy but another manager struggles to answer basic pay questions, Luitjens said perceptions of fairness can quickly erode.

Thomas said a recent Payscale report found 70% of managers reported an increase in employees referencing salary information sourced from generative AI tools, but she noted how these tools often pull from inconsistent or unvalidated data. In this landscape, explainability is becoming just as important as accuracy.

“Ultimately, employees don’t want AI to explain why they didn’t receive a raise,” Thomas said. “They want a manager who understands the context, can explain the decision clearly and can outline what success looks like going forward.”

Editor’s Note: Additional Content

For more information and resources related to this article, see the pages below, which offer quick access to all WorldatWork content on these topics:

• Employee Compensation
• Organizational Performance