The era of the "peanut butter raise"—where companies spread compensation increases evenly across all employees like jam on toast—is rapidly fading. In its place, a new compensation philosophy is taking hold: rewarding performance, particularly proficiency with artificial intelligence.
The Data: Equal Raises Were Always a Minority Play
Despite early optimism that employers might embrace across-the-board raises in 2026, the numbers tell a different story. A recent Mercer survey reveals that only **4% of U.S. employers** actually implemented uniform raises this year—far below earlier projections from Payscale suggesting 44% were considering the approach.
Why the disconnect? The accelerating integration of AI into daily workflows appears to be a decisive factor.
AI Is Redefining "Value" at Work
Technology now sits at the core of business strategy for nearly 60% of leaders, according to Baker Tilly. That strategic priority is translating directly into how employees are evaluated and compensated:
- **Google** has begun factoring AI usage into performance reviews for software engineers, leaving managers to determine measurement criteria.
- **Accenture CEO Julie Sweet** recently stated that AI fluency is now a prerequisite for promotion.
- **AI "super users"**—employees who deeply integrate AI tools into their workflows—are three times more likely to have received both a promotion and a raise in the past year, per Workplace Intelligence.
The Great AI Divide: Adoption vs. Resistance
Not everyone is on board. A WalkMe survey of over 3,700 global professionals found:
- **54% of workers** actively bypass company-approved AI tools to complete tasks manually
- **One-third** hesitate to use AI because it complicates their workflow
This resistance creates a widening gap. While some employees lean into AI to amplify their output, others—whether due to skepticism, skill gaps, or workflow preferences—fall behind. In a compensation environment increasingly tied to measurable impact, that gap has financial consequences.
Why "Fair" Doesn't Always Mean "Equal"
Proponents of peanut butter raises argue they reduce bias and subjectivity inherent in merit-based systems. But as workplace contributions become more differentiated by tech fluency, many HR leaders say uniform raises risk demotivating top performers.
> "If you're being rewarded the same way as everybody else… you're going to feel that it's equal, but not fair, if you're contributing more to the outcomes," says Hannah Yardley, Chief People and Culture Officer at Achievers.
Mark Bowling, a senior principal at Mercer, adds that compensation fairness involves multiple dimensions: individual performance, market rates, and internal equity. "Equal treatment" alone rarely captures that complexity.
The Path Forward: Differentiation with Transparency
Experts agree that as AI reshapes work, compensation strategies must evolve—but not without intentionality:
✅ **Tie rewards to measurable impact**, not just tool usage
✅ **Recognize and spotlight** employees who drive value through innovation
✅ **Communicate clearly** why certain contributions are prioritized
✅ **Invest in upskilling** to help all employees bridge the AI fluency gap
As Yardley puts it: "Not all work is created equal. Organizations should differentiate to set the standard for what value really means in how you deliver."
The workplace isn't just adopting AI—it's being reorganized around it. Compensation is following suit. For employees, the message is clear: developing AI fluency isn't just about staying relevant; it's increasingly tied to career advancement and earning potential. For employers, the challenge is balancing performance-based incentives with inclusive development—ensuring the shift to pay-for-performance doesn't leave valuable talent behind.
In an AI-augmented economy, fairness may no longer look like equality. It may look like an opportunity: clear pathways for every employee to grow, contribute, and be rewarded accordingly.