The True Cost of AI Talent in 2025

The True Cost of AI Talent in 2025: What HR Needs to Know Before Budget Season

AI engineers are on your roadmap. But are they in your budget?

If you're still pricing AI/ML roles like they're just high-end software engineers, you're likely underestimating both the compensation required and the long-term implications for your team.

At Compensara, we recently carried out a deep-dive analysis on the state of AI/ML compensation. We combined insights from multiple industry reports, including recent publications from leading data providers, with our own internal benchmarking data across thousands of tech companies. To validate the trends, we also spoke directly with compensation experts, talent leaders, and HR teams at both public and private companies. The goal: to understand not just what companies are paying AI talent, but why, and what’s changing beneath the surface.

Here’s what HR and comp leaders need to know before heading into 2026 planning.

Base Salary Is Just the Start

Yes, AI/ML roles pay more, but how much more depends on level, company type, and location.

• In private companies, base salary premiums for AI/ML engineers range from +2% to +15% over software engineering roles.

• In public companies, the gap widens, with +10% to nearly +20% premiums at mid-to-senior levels.

But those numbers only tell part of the story. The real differentiator? Equity.

Equity Is Where the Competition Heats Up

Equity is no longer just a retention tool, it’s become the primary way companies win over scarce AI talent.

• Annualized new hire equity grants for AI/ML engineers are 20–30% larger than for SWE roles at the same level.

• 71% of AI/ML engineers at private companies receive retention grants with 4-year vesting schedules, compared to just 53% of SWE counterparts.

• Public companies are also stretching vesting durations on new hire grants, partly to boost perceived value, partly to lock people in.

For companies competing in a tight labor market, equity has become both the bait and the anchor.

Churn: The Hidden Budget Line Item

Even with generous pay packages, retention remains a major challenge:

• Annual churn for AI/ML individual contributors is 28%, significantly higher than SWE (17%) or Data Science (19%).

• In public companies, the attrition rate for AI/ML roles spikes to 32%, the highest among any group we analyzed.

This level of churn adds pressure to backfill roles quickly, inflates total hiring costs, and destabilizes core engineering teams.

If your budget assumes these hires will stick around for 3–4 years, it’s time to revise your model.

What HR and Comp Teams Should Do Now

Here’s how to prepare for 2026 and avoid surprises:

• Don’t force AI/ML into your existing SWE levels. These roles often warrant dedicated tracks, especially at higher levels.

• Assume higher churn when modeling total cost of ownership. If 1 in 4 AI hires leaves each year, that has serious budget implications.

• Expect sign-on bonuses. AI/ML candidates receive sign-ons nearly 2.5x more often than other roles.

• Adjust your equity planning. Longer vesting schedules may improve retention, but only if the rest of the package holds up.