The data from the businesses building closest to the technology tells a clearer story than the headlines do.

Eighty percent of AI-native startups expect employment in their sector to grow. Among startups not currently using AI, that figure drops to 30%. The split comes from a recent survey of 95 early-stage startups, and it points to a structural shift in how AI businesses think about hiring.

The survey covers US-based startups, but the patterns map closely to what we’re seeing across the UK and European markets.

This matters whether you’re a founder making decisions about your next ten hires, or a candidate trying to work out what AI means for your career. The companies building with AI aren’t shrinking their teams. They’re rebuilding them, and they’re hiring differently.

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80% of AI-native startups expect job growth in their sector. Among startups not currently using AI, that figure drops to 30%.”

Source: Technical.ly’s 2026 RealLIST Startups survey with secondary stat from Mercury’s 2025 early-stage leaders report.

What AI-native actually means

AI-native businesses are companies where AI is part of the core product or operating model, not a tool added on later. In the surveyed group, more than a third use AI both internally and inside customer-facing products. Another 16% are building AI directly into what they sell.

These businesses think about team design differently from the start. They aren’t using AI to reduce headcount. They’re using it to increase output, speed up delivery, and scale faster than their team size alone would allow.

That changes what they hire for, and when.

How AI is changing team structure

The roles AI-native teams hire haven’t disappeared. Engineers, operators, product leaders, and commercial teams are still on the org chart. What’s changed is what each of those people needs to be able to do.

Founders are now hiring people who can:

• Work fluently inside AI-assisted environments
• Adapt as tooling evolves, often quickly
• Improve delivery and reduce friction through automation
• Operate across functions, not inside fixed lanes

Some tasks are becoming automated. Repetitive or process-heavy work is the obvious example. At the same time, new categories of work are growing fast: AI infrastructure, implementation, governance, oversight, and workflow optimisation.

AI-native teams are built around new capabilities, not fewer people.

The hiring decisions founders are facing now

The question for AI-native businesses isn’t whether to adopt AI. Most already have. The question is which decisions to make next:

• Which roles need AI fluency built in from the job spec?
• Where does human expertise still create the most value?
• What should automation handle internally, and what shouldn’t it?
• Which technical hires will matter most over the next two years?

These are the conversations we’re having with founders every week. The teams making these decisions early, and with clarity, are the ones moving fastest.

A separate survey of 1,500 early-stage leaders found that 68% of AI-using startups are actively growing their workforce. That isn’t a story about replacement. It’s a story about confidence.

What this means if you’re hiring talent

For founders and hiring leaders, the work isn’t just filling roles. It’s redesigning how the team operates around the technology.

The companies adapting fastest are doing four things differently:

• Hiring earlier, with more clarity about what each role needs to deliver
• Redesigning workflows around AI tooling rather than retrofitting AI into old processes
• Strengthening technical teams that can operate across functions
• Building in governance and oversight from the start, not bolting it on

The hires that matter most are people who can grow with the technology. Adaptability, technical depth, and operational thinking are weighing more heavily in hiring decisions than they did 18 months ago.

What this means if you’re the talent

For candidates, the picture is more positive than the headlines suggest, but the rules of the game have changed.

AI fluency is becoming a baseline expectation, not a specialist skill. The candidates who stand out are the ones who can show how they’ve actually used AI inside their work, what they’ve built or improved with it, and where they’ve spotted its limits.

New role categories are opening up around AI infrastructure, implementation, and oversight. Some of these didn’t exist as defined roles two years ago. The candidates moving into them are often coming from adjacent technical or operational backgrounds, not specialist AI training.

AI is not removing jobs. It is reshaping them. The work to do is understanding which direction your skill set is pointing in, and where the demand is concentrating now.

Where TRG fits in

We work with startups and scale-ups across engineering, AI, machine learning, data, and leadership. From what we’re seeing across the market, the businesses making the strongest hires are doing it with a clear view of what they’re building, not just what they need to fill.

We help companies understand what to hire next in an AI-driven market.

If your business is making those decisions now, we should talk.

Speak to TRG.