How AI is changing the compensation game for VC-backed startups

Authors: Kevin Dowd, Ashley Neville
Read time: 7 minutes
Published date: 8 April 2026

The startup compensation market is bifurcating between companies that are AI-native and those that aren’t. For both groups, however, AI is changing the way executives think about how many people they need to hire, who they need to hire, and how those hires should be compensated.

Headcount growth has slowed

In December 2025, there were more job departures than new hires at venture-backed companies on Carta, the first time monthly headcount growth has gone negative since March 2024. Up until mid-2022, it was common for net headcount to increase by more than 10,000 people per month, peaking at monthly headcount growth of more than 50,000 in January 2022.

Not all of the recent downturn in headcount growth can be attributed to AI—hiring numbers were likely going to decline after the 2021 venture bull market regardless of what new technologies emerged. But AI has clearly accelerated the process. Investors increasingly want their startups to operate more leanly and to accomplish more with less. And the “less” part of that equation includes less hiring.

Startups are prioritizing different positions

Over the past few years, finding top talent in roles related to AI, machine learning (ML), and data science has become more important than ever. At the same time, the exact nature of the roles in those areas for which startups are hiring has undergone a shift.

Today, nearly every software engineer uses AI in their work. But that doesn’t necessarily make them true AI engineers, a title that typically refers to those who are involved in building AI models or otherwise crafting the infrastructure of AI platforms and tools.

Early-stage equity packages are ballooning

For smaller startups, the biggest adjustment so far has been a major increase in the size of equity packages granted to new hires. For startups valued between $1 million and $10 million, the median equity grant for AI/ML engineers increased by 59% from January 2024 to February 2026.

Median salaries for AI/ML engineers have also increased among smaller startups, but not to the same degree.

AI natives pay top dollar for top engineers

At an AI-native startup valued at more than $500 million, an AI/ML engineer compensated at the 80th to 95th percentile would earn $320,000 in annual salary and be granted 0.146% of the company’s total equity. At a startup with the same valuation that is not AI-native, those same benchmarks drop to $285,000 in salary and 0.1% of total equity.

When hiring for AI/ML engineers, hiring managers should know the quality of the talent they’re pursuing, as well as what sorts of companies they’re competing against.

AI natives pay more for GTM roles, too

Once all those new AI/ML engineers build their cutting-edge products, someone has to take them to market. At the top end of the market, those sales and marketing professionals are receiving better compensation at AI-native companies.

How AI informs the data

All the compensation data included in this article is culled directly from companies. Even when it comes straight from the source, however, compensation data for private companies—particularly data on equity grants—is notoriously complex and opaque. For the past five years, Carta has been applying AI models to gather, clean, and analyze this data, making sure our clients have the best, most relevant information at their fingertips to inform their hiring decisions.