Average Yearly Raise: What to Expect & How to Get More in 2026
By
Ethan Fahey
•
Jan 21, 2026
Looking ahead to 2026, most U.S. employers are planning modest merit-based raises, generally in the low single digits once you factor in promotions, cost-of-living adjustments, and market corrections. Tech and AI roles often land a bit higher than average, but the era of broad 5–6% annual increases is largely over. For hiring managers, that means compensation planning has to be far more deliberate than it was during the peak growth years.
This puts fast-growing tech companies in a tough spot. Budgets are tighter, growth is more measured, yet competition for experienced AI, ML, and senior engineering talent hasn’t eased. Underpay, and candidates walk. Move too slowly, and they accept another offer. That’s where tools like Fonzi AI come into play. By matching companies with pre-vetted, high-signal AI and engineering candidates quickly, Fonzi helps teams stay competitive on pay without overspending or dragging out hiring cycles. For recruiters and talent leaders planning 2026 budgets, the combination of realistic raise benchmarks and faster, more precise hiring can make the difference between landing top talent and losing them to a better-prepared competitor.
Key Takeaways
Standard raises are stabilizing at 3-4%, but high performers earning “exceeds expectations” ratings average 5% raises, while promotion-based increases average 8.7%, more than double the typical merit bump.
Inflation and market cooling from 2022-2024 are reshaping expectations, with organizations pulling back on sign-on bonuses in tech while maintaining competitive base salary increases for critical AI and engineering roles.
Engineering and AI talent still command above-average raises, with job-switchers in these fields often seeing 10-20% increases when moving to high-growth startups, even as broader wage growth normalizes.
Competing for top engineers in 2026 requires salary transparency, faster hiring cycles, and structured evaluation: 83% of employers claim they want to target compensation toward high-demand skills, but actually implement equal-distribution policies across the organization.
Fonzi AI helps tech hiring leaders align compensation with market reality by using multi-agent AI to pre-vet candidates, compress hiring timelines through Match Day events, and provide real-time visibility into what elite engineers actually expect.
What Is the Average Yearly Raise in 2026?
An average yearly raise is the typical percentage increase to base salary that an employee receives over a 12-month period, usually determined during an annual review cycle.
Current benchmarks from multiple authoritative surveys show strong convergence around the same numbers:
Source | Merit Increase Budget | Total Increase Budget |
iMercer | 3.1% | 3.5% |
Mercer QuickPulse | 3.2% | 3.5% |
Conference Board | 3.4% | 3.4-3.5% |
Pearl Meyer | 3.7% | 3.7% |
Pave | 3.5% (median) | — |
Most employers are clustering around 3.1-3.5% for merit-only increases, with high performers receiving 5-7% and promotion moves delivering 8-12% within the same company. For job switchers, especially in tech, average pay increases often range from 10-20%, with some AI/ML specialists seeing even more when moving from legacy firms to high-growth startups.
What counts as a “good” raise depends heavily on role (individual contributor vs manager), company stage (startup vs enterprise), and geographic location (SF Bay Area vs mid-market U.S. cities). A 4% raise might be excellent at a bootstrapped startup, but below market at a well-funded Series C company competing for the same talent pool.
Key Drivers of Average Yearly Raises in 2026
2026 raise budgets will be shaped by a mix of macroeconomics, labor market dynamics, and company-specific strategy. Understanding these drivers helps you set realistic expectations and allocate compensation dollars where they’ll have the highest impact on retention and recruitment.
The four main drivers to consider:
Inflation and cost of living: How purchasing power concerns translate into raise expectations
Location and remote work: How geo-pay bands and distributed teams affect salary increases
Industry, role, and skills: Why AI and engineering roles command premium raises
Company performance and funding: How runway and revenue growth constrain or enable compensation strategy
Inflation and Cost of Living
The elevated inflation from 2021-2023 led to higher cost-of-living adjustments (often 4-6%), but 2024-2025’s moderating inflation is pushing budgets closer to 3-4% again. Many employers conflate cost-of-living raises (meant to maintain purchasing power) with merit raises (meant to reward performance) into a single pool, which can create confusion during review conversations.
Here’s the practical reality: a 3% raise in a 4% inflation year is effectively a pay cut in real terms. Forward-looking 2026 planning should assume modest inflation but retain flexibility for spikes. The Federal Reserve’s target of 2% inflation may or may not hold, but rising costs remain a concern for employees who feel their wages aren’t keeping pace with rising prices.
For hiring leaders, the key is communicating clearly when raises are meant to offset inflation versus recognize performance. Employees who don’t understand the distinction will interpret a “meets expectations” 3% raise as a signal that they’re undervalued, when it may actually reflect standard pay adjustments across the organization.
Location, Remote Work, and Geo-Pay
The shift to remote and hybrid work has made geographic pay differentials more explicit. Some companies have adopted formal geo-pay bands (paying 10-25% premiums for high-cost hubs like San Francisco, New York, and Seattle), while others are moving toward more location-agnostic salary ranges.
For distributed teams, average raises can vary by region. Fast-growing tech hubs like Austin, Toronto, Berlin, and Bangalore sometimes show above-average percentage increases as companies fight to establish competitive wages in emerging talent markets. Meanwhile, engineers in traditional high-cost hubs may see tighter raises because their base pay is already at the upper end of salary ranges.
Leaders should regularly recalibrate location-based bands using current market data and be transparent with candidates and employees about how geographic location affects both offers and annual raises.
Industry, Role, and Skills (With a Focus on AI & Engineering)
Average yearly raises differ sharply between sectors. Tech, finance, and healthcare typically offer higher merit and promotion increases than government or non-profit organizations. Energy and Insurance lead at 3.3% merit budgets, while Healthcare and High-Tech sit at 3.0%, paradoxically lower despite ongoing talent shortages.
AI, machine learning, data engineering, and senior full-stack roles remain structurally constrained talent pools. These high-demand industries often command above-average raises: 6-8% for top performers and 15-25% on job changes. Several factors determine whether a candidate can command these premiums, including specific skill clusters like LLM fine-tuning, MLOps, and distributed systems.
Early-stage AI startups may offer more modest base raises but compensate with equity, while larger tech firms emphasize higher base pay with more structured raise cycles. Talent leaders should track and raise expectations not just by title but by critical skill clusters to stay aligned with the hottest segments of the market.
Company Performance, Funding, and Headcount Strategy
In 2023-2024, many tech companies responded to tighter funding and slower growth with hiring freezes or downsizing, while still protecting high performers’ raises to avoid regretted attrition. This pattern of selective generosity within overall constraint is likely to continue.
For 2026, leaders should tie raise budgets to realistic revenue, burn rate, and runway assumptions. Across-the-board freezes might save short-term budget, but demoralize top engineers who have plenty of options in the current job market. A smarter approach uses targeted market adjustments (8-10% for severely under-market engineers) alongside standard 3-4% budgets to correct pay inequities and address retention risks.
AI-enabled compensation analytics through HRIS and talent platforms can help identify where raises yield the highest ROI in retention and productivity, moving beyond gut-feel decisions to data-driven allocation.
Types of Raises: How They Compare and When to Use Each
Most employers blend multiple raise types in a single annual review cycle, but documenting them separately improves transparency and perceived fairness. Understanding the four main raise categories helps you communicate more effectively with employees and allocate budget strategically:
Cost-of-living (COLA): Adjustments to maintain purchasing power against inflation
Merit/performance: Rewards for job performance and impact
Promotion: Significant salary increase tied to advancement in level or scope
Market adjustment: Corrections when an employee’s current salary has drifted below market rates
Many organizations conflate these categories, leading to confusion when an employee interprets a COLA adjustment as a merit increase or vice versa. Clear documentation of which type of raise an employee receives and why reduces friction during review cycles.
Raise Type | Typical Range (2025-2026) | When It’s Used | Best For |
Cost-of-Living (COLA) | 2-4% | Annually, often applied company-wide | Maintaining purchasing power, broad fairness |
Merit/Performance | 3-7% | Annual review based on performance ratings | Rewarding high performers, differentiating contribution |
Promotion | 8-15% | When an employee moves to a higher level | Career advancement, retention of top talent |
Market Adjustment | 5-15% (variable) | When internal pay falls behind external market rates | Retention, pay equity corrections |
Example: A senior ML engineer stepping into a staff-level role might receive a 10% promotion raise, while a solid mid-level backend engineer meeting expectations receives a 3.5% merit increase. Combining a modest COLA with targeted merit and promotion raises preserves budget while rewarding measurable impact.
Key best practices:
Separate COLA from merit in your documentation so employees understand what each raise recognizes
Reserve promotion-level increases for genuine scope changes, not just tenure
Use market adjustments proactively to correct drift before competitors make offers
Average Raises by Job Level and Job Changes in Tech
Raise patterns differ significantly between junior ICs, senior ICs, engineering managers, and VP-level leaders. Understanding these patterns helps you benchmark internal practices against market conditions.
Typical yearly raise expectations by level:
Level | Typical Raise Range | Notes |
Junior Engineers (0-2 years) | 3-5% | Higher early-career growth, often tied to skill development |
Senior/Staff Engineers | 4-7% | Performance-driven, may include equity refreshers |
Engineering Managers | 4-6% | Often tied to team metrics and business outcomes |
VP/Director | 3-5% base + bonus | Smaller base increases, larger bonus/equity components |
The gap between staying at the same company (2-4% annual raises) and switching jobs (10-20% increases) fuels significant turnover in tech. Engineers who remain at their current company for several years often find their total compensation drifting below what they could command on the open market.
Talent leaders should periodically benchmark internal raises against external offer patterns to anticipate which engineers are most at risk of leaving for a new job at a prospective employer offering better pay.
Individual Contributors vs People Managers
High-impact ICs (staff/principal engineers, lead ML scientists) often expect raises and bonuses tied to measurable technical outcomes, system reliability improvements, shipping critical features, or reducing infrastructure costs by a specific dollar amount. Managers’ raises more often reflect team and business-level metrics like delivery velocity, retention, and hiring success.
Strong ICs in hot AI roles may see 6-8% yearly raises plus equity refreshers, while managers might receive similar percentages but with different bonus structures tied to the company’s success.
Best practices:
Define separate performance frameworks for IC vs manager tracks
Ensure “average” and “top quartile” raises are clearly differentiated and defensible
Emphasize transparency around pay progression for both tracks to avoid pushing great ICs into management purely for compensation reasons
Internal Raises vs Job-Switch Raises
Internal annual raises typically fall in the 3-4% range for solid performers, with 5-7% reserved for top contributors. Job-switch raises often land between 10-20% in competitive tech markets, and sometimes higher for candidates with high-demand skills.
Concrete scenario: A backend engineer at a mature SaaS company earning $140k base moves to a growth-stage AI startup at $165k-$175k base plus equity, representing a 15-25% jump. The original employer essentially subsidized their competitor’s hiring by allowing pay to drift below market over several years.
To narrow this gap:
Conduct stay interviews with critical talent to identify flight risks
Use proactive market adjustments rather than reactive counteroffers
Benchmark your salary ranges against current market trends, not historical data
How AI Is Changing Raise Expectations and Hiring Economics
The rise of generative AI and LLMs has increased demand for specialized talent while simultaneously enabling new efficiencies in the hiring process. This creates a fascinating tension: raises and salary expectations are rising fastest in AI-heavy roles, while recruiting teams face bandwidth constraints, long hiring cycles, and inconsistent candidate quality.
AI in recruiting can lower cost-per-hire and time-to-hire, making it easier to fund competitive wages and offers for the right candidates. When you spend less time and money on inefficient hiring processes, you free up budget for what matters: paying well and retaining your best people.
The Hiring Challenges Behind 2026 Raise Pressure
The common pain points are familiar to any talent leader:
Slow hiring cycles: 8-12 week processes are common, with back-and-forth scheduling, inconsistent interview standards, and drawn-out decision-making. When hiring takes too long, you either overpay to close quickly or lose your preferred engineer to a faster-moving competitor.
Recruiter overload: Many employers are asking recruiting teams to do more with less headcount, leading to rushed screening and missed candidates. This bandwidth problem directly impacts compensation strategy, as when you can’t thoroughly evaluate candidates, you’re more likely to mis-hire or make salary decisions based on incomplete data.
Inconsistent evaluation: Unstructured interviews lead to pay inequities where similar candidates receive different offers or raises. This becomes harder to justify during annual review season and creates legal and cultural risks.
Better process and better data, supported by AI, make it easier to align raises with real impact and market reality instead of guesswork.
How Fonzi AI Uses Multi-Agent AI to Improve Hiring, Not Replace Humans
Fonzi AI operates as a curated talent marketplace with a structured “Match Day” event, combining AI agents with human recruiters to pre-vet and match top engineers with startups and high-growth tech companies.
AI-supported tasks include:
Automated screening of resumes and profiles to surface high-signal candidates
Fraud and identity checks to eliminate fake credentials
Structured work-history verification and bias-audited evaluation frameworks
Intelligent matching based on skills, experience, and candidate preferences
Crucially, recruiters and hiring managers remain fully in control of final decisions, interviews, and offers. AI handles the repetitive, error-prone work and generates higher-signal shortlists—but humans make the calls that matter.
Match Day compresses hiring timelines dramatically. Many roles see offers made within approximately 48 hours of the event, letting companies move quickly on strong candidates without the lengthy back-and-forth that typically extends hiring to weeks or months.
Salary transparency is built in: Participating companies commit to salary ranges upfront, helping both sides anchor expectations around realistic numbers. This eliminates the awkward dance of discovering late in the process that the offer expectations don’t match the budget.
From Better Hiring to Better Raises and Retention
When companies use Fonzi AI’s structured, AI-assisted process, they gain clearer visibility into the true market value of AI and engineering roles at the moment they hire. This upfront clarity makes future raise conversations easier, managers can reference objective market benchmarks, structured performance data, and consistent evaluation criteria rather than relying on outdated assumptions.
Reducing mis-hires and churn through better matching frees up budget to offer more competitive raises and growth paths to high performers. It’s worth noting that the cost of a bad hire often exceeds the salary bump you’d need to retain your best engineer.
Leaders should treat AI-informed hiring data as a continuous input into compensation strategy, not just a one-time artifact of offer creation.
How to Design a Raise Strategy for 2026 That Attracts Top Engineers
This section provides a practical playbook for tech talent leaders: how to plan raise budgets, structure ranges, and communicate expectations in ways that attract and retain elite engineers.
A simple framework:
Define your compensation philosophy
Benchmark against current market data
Align raise bands with performance tiers
Use AI-enabled tools like Fonzi to validate and refine
Set a Clear Compensation and Raise Philosophy
Decide where you aim to pay versus market (for example, top 25% for critical AI roles, market median for support functions), and translate that into yearly raise targets. Codify how you balance base salary versus bonuses versus equity in raise and promotion decisions, especially for engineering and AI roles.
Consider publishing an internal “compensation principles” document that spells out:
How cost-of-living, merit, and promotion raises are considered each year
What market percentile you target for different role types
How job duties and scope changes trigger promotion-level raises
This clarity reduces friction and suspicion during review cycles, making average raises feel more predictable and fair. Employees maintain trust when they understand the system.
Use Structured Performance and Market Data, Not Gut Feel
Base raises on a combination of structured performance ratings, objective impact metrics, and current salary benchmarks for each role and level. Avoid relying on gut feel or manager discretion alone; this leads to inconsistent pay adjustments and potential equity issues.
Refresh market data at least annually, with explicit focus on AI, ML, and senior engineering benchmarks that move faster than general tech roles. Platforms like Fonzi AI provide real-time insight into what top-tier engineers are actually being offered across startups and growth companies.
Warning: Pre-2022 benchmarks likely understate current expectations in hot AI segments, even if the broader market has cooled. Using outdated data means you’ll consistently underbid on your best candidates.
Align Raise Bands With Performance Tiers
Outline a simple tiered approach:
Performance Rating | Typical Raise Range | Notes |
Meets Expectations | 2-4% | Standard annual increase |
Exceeds Expectations | 5-7% | Reserved for clear high performers |
Significantly Exceeds | 7-10% or promotion-level | Exceptional impact, may include promotion |
Tie each tier to specific, documented behaviors and outcomes. For engineers, this might include ownership of critical systems, shipping key features on time, mentoring junior team members, or driving measurable reliability improvements.
Bias-audited evaluation frameworks, like those used in Fonzi’s process, can inspire similar rigor in internal performance reviews. During review conversations, explain both the performance rating and the corresponding raise band to reduce ambiguity.
Communicate Expectations Early and Often
Brief managers well before review cycles on expected average raise budgets, constraints, and messaging. Share transparent ranges with employees (e.g., “most raises this year will be between 3-5%, promotions higher”) to reduce surprise and frustration.
Document the rationale for raises and make it accessible for future talent planning and retention discussions. Clear communication helps engineers distinguish between a normal year and a constrained year (post-funding crunch, for example) and contextualizes their own raise within broader market conditions.
How Candidates Can Earn Above-Average Raises (and What Employers Should Expect)
While this article is written primarily for hiring leaders, understanding candidate behavior, like job switching and negotiation tactics, is essential for building realistic raise and retention strategies.
Platforms like Fonzi AI tend to attract ambitious, top-decile engineers who are more likely to push for raises above the 3-4% norm. These candidates come prepared with data, competing offers, and clear evidence of impact. Leaders should anticipate this and design accordingly.
Performance, Impact, and Negotiation
Candidates who consistently drive measurable impact, such as revenue gains, cost savings, reliability improvements, or product velocity, are the most credible in asking for a raise of 6-10% or securing a promotion jump. They’ll bring market data, competing offers, and quantified achievements to the table.
Hiring managers should be prepared with their own data and guardrails. Train managers on compensation conversations so they can recognize when above-average raises are warranted versus when expectations are misaligned with employee performance.
Structured hiring inputs (case studies, take-home projects, performance history from previous roles) help predict who is likely to seek and deserve stronger raises later. The best candidates often reveal their standards during the interview process.
Job Switching and the 10-20% Raise Expectation
In tech, especially for AI, ML, and senior engineering roles, job switches regularly come with 10-20% base pay increases plus equity refreshers or sign-on bonuses. Many candidates now view changing jobs every 2-3 years as a core strategy for staying ahead of the narrow percentage range of internal annual raises.
This pattern creates a structural challenge: your best engineers can significantly increase their earnings by leaving for a new company, while traditional raises keep them at roughly the same purchasing power.
Recommendations:
Proactively identify top performers at risk of being poached
Consider market adjustments or accelerated promotions rather than waiting for a counteroffer scenario
Recognize that Fonzi AI’s Match Day format concentrates highly qualified, actively looking engineers, and offers need to align with these higher raise expectations to convert them
Conclusion
Looking ahead to 2026, most companies are planning for average annual raises in the low single digits, with larger bumps reserved for top performers, promotions, and job changes, especially in AI and engineering. That may feel like a return to pre-pandemic norms, but the competition for truly exceptional technical talent hasn’t cooled off. Paying everyone the same modest increase isn’t what wins; being intentional about where compensation dollars go is.
The real edge comes from tying pay decisions to structured performance evaluation and current market signals, not gut feel or outdated benchmarks. That’s where AI-enabled hiring helps. By shortening time-to-hire, improving match quality, and avoiding costly mis-hires, teams create more room to reward the people who actually move the business forward. Fonzi AI is built around this idea, giving recruiters fast access to pre-vetted AI and engineering talent with clear role scope and salary expectations. If you want to head into 2026 with a compensation strategy that’s competitive and sustainable, booking a Match Day with Fonzi is a practical place to start.
