Karina Mann, Author at TRG.

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.

[DESIGN – Pull quote / callout]

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.

Most scale-ups have stopped waiting for the hiring market to ease. They’ve worked out that it isn’t going to.

The UK skills gap is no longer cyclical. It is structural.

Across engineering, AI, digital infrastructure, and specialist technical hiring, demand continues to outpace supply. ManpowerGroup’s 2026 Global Talent Shortage Survey found that 73% of UK employers report difficulty filling roles, above the global average of 72%.

For scale-ups, that turns hiring from a recruitment issue into a board-level growth constraint. It affects delivery timelines, product development, operational scale, and long-term growth.

Why the UK skills gap is now a growth constraint

The UK technology market has matured quickly over the last decade.

More VC-backed companies are competing for the same experienced talent pools across engineering, AI, data, and leadership hiring. At the same time, experienced technical talent remains limited.

That imbalance is now a structural constraint on growth.

The challenge is not generating applications. Most companies can do that. The challenge is hiring people with the technical capability, leadership experience, and operational fit required to scale a business.

That gets harder when hiring plans change quarter to quarter, when leadership teams are hiring roles they have not hired before, when internal recruitment capability is stretched, and when hiring partners focus on speed over alignment.

This is where growth slows. Not because companies lack ambition or investment. Because hiring infrastructure has not kept pace with the business.

The strongest companies treat hiring as infrastructure

From what we’ve seen in the market, the strongest scale-ups treat hiring as a growth function.

Instead of: “How quickly can we fill this role?”
They ask: “What capability do we need to build over the next 12 to 24 months?”

They plan earlier, hire against business priorities, build long-term talent relationships, and move decisively when the right people become available.

That approach changes how businesses scale, directly affecting delivery speed, technical capability, operational stability, and long-term growth.

This is how stronger hiring decisions create a competitive advantage.

Why transactional recruitment breaks down in specialist markets

Transactional recruitment models struggle in structurally constrained markets, especially across AI and machine learning, engineering leadership, platform and infrastructure hiring, specialist software engineering, and technical product and data functions.

The issue is rarely sourcing volume. The problems show up later:

Technical capability is overstated
Role scope shifts mid-process
Hiring managers are misaligned
Assessment processes fail to test real capability
Candidates disengage because the process lacks clarity

In specialist markets, hiring quality depends on understanding the business, not just the role. That means understanding the technical environment, knowing how the business is scaling, identifying where capability gaps exist, and positioning the opportunity properly to experienced candidates.

This is why more scale-ups are moving toward embedded hiring partnerships instead of rotating agencies.

How UK scale-ups will win the hiring race in 2026

The businesses building strong teams over the next few years will not be the ones spending the most. They will be the ones making better hiring decisions earlier.

That means building structured hiring plans, aligning recruitment with business goals, creating stronger technical assessment processes, improving hiring speed without lowering standards, and treating workforce planning as part of operational strategy.

Access to experienced technical talent is now one of the defining factors behind whether a company can scale effectively. The companies that recognise this early build stronger teams while competitors are still reacting to hiring pressure.

Speak to TRG

TRG operates inside the London high-growth technology ecosystem, supporting startups and scale-ups through critical hiring stages. The focus is long-term capability building, not short-term CV delivery.

We help companies hire for where they are going, not where they are.

If hiring is slowing your growth, get in touch.