The market is cautious at the top and specialist in the middle. Businesses spent 2025 hiring carefully, but demand held up for specific tech skills: AI, data, enterprise applications and cyber security, according to Computer Weekly's tech recruitment outlook for 2026. That pattern sits inside a large and active sector.
The updated digital and technology definition now covers 107,082 companies, or 5.2% of all UK companies, per the government's digital and technologies sector statistics. And the broader professional, scientific and technical activities sector saw the largest volume increase in vacancies, up by 5,000 in August to October 2025, in the ONS vacancies bulletin for November 2025. So the appetite is there; it's just being aimed more precisely.
The junior end tells the harder story. The UK tech sector cut graduate jobs by 46% in the past year, with a further 53% drop projected, according to figures from the Institute of Student Employers reported by The Register. Adzuna has recorded a 30% drop in entry-level postings since ChatGPT launched, leaving graduates with the toughest market since 2018, per techUK's analysis of entry-level and graduate jobs.
When you charge per unit of usage, your business model runs on data. Every API call, gigabyte and active seat becomes revenue you have to measure, forecast and defend. That changes who you need in the room.
Three role clusters rise. First, data and analytics people who can model usage, spot churn early and price accurately: the specialist skills already named as hotspots in Computer Weekly's 2026 outlook. Second, cloud and platform engineers who keep the cost of serving usage below the price of it, so growth doesn't quietly erode margin. Third, reliability and security specialists, because metered products live or die on uptime and trust; the UK cyber workforce reached roughly 143,000 people with growth accelerating to 5% in 2024, per the government's cyber security skills report for 2025.
There's also a route for building this talent rather than only buying it. Apprenticeships rose from 3% of AI hires in 2020 to 19% in 2025, according to the government's AI labour market survey for 2025. With the graduate pipeline squeezed, structured early-career hiring is one of the few ways to grow specialist skills in house.
Start by writing the role around the revenue metric, not the job title. Ask what usage signal this person will move: onboarding time, cost per request, retention. That single question sharpens your shortlist and filters out generalists who look right on paper but can't tie their work to the meter.
Then move quickly, because specialists don't wait. Skills shortages are widespread across technical fields: 76% of engineering employers struggle to recruit for key roles, per the IET's 2025 skills survey. A slow, multi-week process loses the exact people usage-based teams depend on. Keep interviews focused, give a clear decision date, and test for judgement about trade-offs, not just tool knowledge.
Finally, build as well as buy. With entry-level postings down 30% in techUK's data and the apprenticeship route growing in the AI labour market survey, pairing a few senior hires with a deliberate early-career pipeline gives you specialist depth that's hard for competitors to poach.
We search 15 million candidates to find the specialists a usage-based model needs, from data and analytics to cloud and reliability. Our recruitment agent manages recruitment end to end for 8% on a successful hire, with no monthly fee and no upfront cost. If you're building a team around what users actually use, Reed.ai can start your shortlist today.
