Key takeaways
- AI postings rose 61%, from 112,000 to 180,000, while overall UK vacancies fell 6.6%.
- The AI wage premium hit 34.2%, up from 11%. It peaks at 64% in consumer markets and sits at 12% in the public sector.
- The ratio that matters: AI user roles grew by just under 66,000. Developer roles grew by 2,600.
- Entry-level is being rebuilt higher. AI-exposed entry roles are 7x more likely to demand senior skills, and have grown 35% while others fell 10%.
- The build-or-buy answer follows from the ratio. You cannot hire your way out of a shortage of people who understand your business.
Most AI workforce research is either vendor marketing or a survey of 400 executives telling you what they intend to do. This one is different, and it is worth ten minutes of your attention. PwC analysed more than a billion job advertisements across 27 countries. It measures what employers actually advertised and paid, not what they said they were planning.
What PwC found in the UK
+61%
specialist AI job postings, from 112,000 to 180,000 in 2025, back to 2022 levels
-6.6%
overall UK vacancies across the whole economy over the same period
34.2%
average wage premium for workers with AI skills, up from 11% the year before
Read the first two together, because that is the whole story in two numbers. In a shrinking job market, one category grew by nearly two thirds. Specialist AI roles now make up 2.2% of all UK postings, up from 1.3%.
The labour market did not get better last year. It got more selective. Demand did not disappear, it moved.
The ratio that should decide your strategy
Here is the finding almost every write-up buried, and it is the one that matters most if you are trying to work out what to actually do.
PwC splits AI roles in two. AI developers build the technology. AI users apply it effectively within a field of expertise, so a marketer, a finance analyst, an operations manager or an HR lead who knows how to get real work out of these tools.
Sixty-six thousand against two and a half thousand. User roles now account for the majority of all AI-related demand in the UK, and the pattern holds across sectors. In government and the public sector, 97.3% of AI roles are user roles.
PwC's Chief Technology and Innovation Officer, Claire Reid, put the implication plainly.
"There's a difference between building an AI-literate workforce and expecting everyone to become an AI specialist overnight."
Claire Reid, Chief Technology and Innovation Officer, PwC — 2026 AI Jobs BarometerShe also noted that "the experimentation phase is over and businesses want to scale and embed the technology properly". That is a different job from the one most firms have been doing for two years, and it needs different people.
Build or buy, with actual numbers
Put the ratio and the premium together and the commercial question resolves itself for most employers.
| Buying AI skills | Building AI skills | |
|---|---|---|
| What it costs | A wage premium averaging 34.2%, and up to 64% in consumer markets | Fundable through the Growth and Skills Levy, and fully funded for 16 to 24 year olds |
| Who you compete with | Everyone, in a category that grew 61% in a year | Nobody. They already work for you |
| Domain knowledge | They have to learn your business | They already know it. That is the hard half |
| Time to value | Notice period, then onboarding, then context | Applied to live work from the first months |
| Retention risk | They can be outbid by the same premium that got them | Development is one of the reasons people stay |
| When buying wins | You genuinely need an AI developer, or a capability nobody internally could plausibly reach. Both are real. Neither is where the volume is. | |
We should be straight that we sell the build option, so weigh that. But the argument does not rest on our opinion. It rests on a ratio of roughly 25 to 1 between the roles employers are advertising for and the roles most people assume the shortage is in.
You cannot hire your way out of a shortage of people who understand your business and understand AI. Half of that is already sitting in your building.
The two-track market, and which track your roles sit on
PwC describes a labour market splitting in two, depending on what AI does to a given job.
- Where AI amplifies expertise, removing routine work so people spend more time on judgement and decisions, roles have grown 39% since 2018.
- Where AI simplifies tasks, making a role more accessible to more people, growth has been 17%.
Both are growth. But they are very different propositions for the person doing the job, and for what you should be training them in. The first track pays for judgement. The second track increases competition for the work.
There is a genuine complication worth reporting rather than skating past. Over the longer run, job postings have grown faster in occupations with lower AI exposure: by 2025 the least exposed roles had more than doubled against 2012, while the most exposed were broadly flat. Highly exposed occupations still account for around 3.4 million UK postings, so this is not collapse, but anyone claiming AI exposure is straightforwardly good for a career is overselling it.
What it is doing to entry-level roles
The most uncomfortable finding concerns young people. PwC analysed 2.4 million entry-level roles and found that entry-level jobs most exposed to AI are now seven times more likely to require traditionally senior skills, things like leadership and team building.
Those roles grew 35% since 2019. Other entry-level roles declined 10%.
That analysis is US data, so treat the precise numbers as directional for the UK rather than local. The pattern, though, matches what we see in the British market: the bottom rung is not disappearing so much as being rebuilt higher up the wall. Which is a serious problem if your route in was supposed to be a first job that taught you the basics.
It is also, bluntly, the argument for apprenticeships. A structured route where someone earns while building both the domain knowledge and the judgement is one of the few mechanisms that puts a rung back. We wrote about the other end of the same problem when GCSE resit pass rates fell again this month.
Where the premium is highest, and lowest
Do not take 34.2% as your number. The variation is enormous.
PwC's explanation is neat: premiums run high both where AI skills are scarce and specialised, such as energy and consumer markets, and where they are deeply embedded and strategically vital, such as technology and financial services. Technology, media and telecoms leads on overall AI intensity, followed by financial services and the public sector.
If you are in the public sector, the 12% premium plus 97.3% user roles tells you something useful. Buying is comparatively cheap, but almost nobody is buying developers. Your gap is capability across existing teams, which is exactly what our public sector AI guide covers.
What to do with this
-
Work out which of your roles are users, not developers
Do: list the jobs where AI would remove routine work, then ask whether you need someone to build a tool or use one.
Why: almost every employer overestimates how much genuine developer capability they need, and underestimates the user gap. -
Price the buy option honestly before you dismiss build
Do: take a real salary from a real role, add your sector's premium, and add recruitment cost and time to competence.
Why: "training is expensive" survives mainly because nobody costs the alternative properly. -
Decide which track each role is on
Do: for each role, decide whether AI amplifies the expertise or simplifies the task, and train accordingly.
Why: amplified roles need judgement and decision-making. Simplified roles need differentiation, or the competition for them widens. -
Fix your entry-level route deliberately
Do: if your junior roles now demand senior-sounding skills, decide how anyone is supposed to acquire them at your organisation.
Why: "three years' experience" for an entry-level job is not a hiring standard, it is an admission you have stopped developing people. -
Check what your levy would actually cover
Do: look at your Growth and Skills Levy position, including that 16 to 24 year olds are fully funded even once an account is exhausted.
Why: most employers underspend the levy while paying market premiums for the same skills. Both problems have one solution.
A 25-minute call, no obligation, covering three things:
- Which of your roles are user roles and which genuinely need a developer
- What buying would cost you at your sector's premium, against what building costs from the levy
- Which route fits, from a short Level 5 leadership unit to the AI & Automation Practitioner Level 4
If the honest answer for a particular role is "hire someone", we will say that.
Book a skills conversation →What we would not claim from this data
Three honest caveats, because a report this useful gets misquoted quickly.
- These are job postings, not hires. They measure advertised demand and advertised pay. Some of those roles will not have been filled, and posted salaries are not the same as paid salaries.
- The 34.2% premium is an average across wildly different sectors. Quoting it at a public sector employer where the figure is 12% would be misleading.
- The entry-level analysis is US data. The direction is instructive. The precise multipliers are not a UK measurement.
None of that undermines the core finding. It just means you should use the numbers for your own sector rather than the headline.
The honest summary
The AI skills market did something unusual last year. It grew 61% inside an economy where vacancies fell, and it repriced the people who have those skills by a third. That is what a genuine shortage looks like when it arrives.
What it is not is a shortage of people who can build models. The shortage is people who can apply AI properly inside a real business, with the domain knowledge to know what is worth applying it to. Those people are mostly not on the market. They are on your payroll, doing a different job, and they are cheaper to develop than to replace.
The employers who work that out first will spend the next two years hiring less and getting more out of who they already have.
Frequently asked questions.
What is the AI wage premium in the UK?
PwC's 2026 AI Jobs Barometer puts the average UK wage premium for workers with AI skills at 34.2%, up from 11% the previous year. It varies enormously by sector, peaking at 64% in consumer markets and standing at 12% in government and the public sector. The figure is drawn from analysis of more than a billion job advertisements across 27 countries.
Is AI hiring growing or shrinking in the UK?
Growing sharply, and against the trend. Specialist AI job postings rose 61% in 2025, from 112,000 to 180,000, returning to levels last seen in 2022. Over the same period overall vacancies across the UK economy fell 6.6%. Specialist AI roles now account for 2.2% of the job market, up from 1.3%.
What is the difference between an AI user role and an AI developer role?
An AI developer builds the technology. An AI user applies it effectively within a field of expertise, for example in finance, marketing, operations or HR. PwC found user roles grew by 65.8% in 2025, just under 66,000 additional roles, and now make up the majority of AI-related demand. Developer roles grew 21.6%, around 2,600 roles. For most employers the shortage is users, not developers.
Should employers hire AI skills or train existing staff?
It depends on what you actually need. Genuine AI developers are scarce and expensive, and if you need one you will have to compete for them. But the growth is overwhelmingly in AI user roles, and those are much more realistically built from people who already understand your business. In England that training is fundable through the Growth and Skills Levy, which changes the arithmetic considerably against paying a market premium.
Is AI reducing the number of jobs?
PwC's data shows a more complicated picture than simple replacement. Roles most enhanced by AI, where it removes routine work so people can focus on judgement and decisions, have grown 39% since 2018, against 17% growth in roles where AI mainly simplifies tasks. Highly AI-exposed occupations still account for around 3.4 million UK postings. Over the longer run, though, postings have grown faster in occupations with lower AI exposure.
How is AI changing entry-level jobs?
PwC's analysis of 2.4 million US entry-level roles found that entry-level jobs most exposed to AI are now seven times more likely to require traditionally senior skills such as leadership and team building. Those roles have grown 35% since 2019, while other entry-level roles declined 10%. This analysis is US data, but the direction is relevant to UK employers thinking about how young people get their first rung.
How can UK employers fund AI skills training?
Through the Growth and Skills Levy. Levy-paying employers draw from their apprenticeship service account, and apprentices aged 16 to 24 are fully funded even when that account is exhausted. Non-levy employers get full funding for 16 to 24 year olds and co-invest for those aged 25 and over. Options range from short Level 5 AI leadership units to the AI & Automation Practitioner Level 4 apprenticeship, and none require a coding background.
Sources: all figures from PwC's 2026 AI Jobs Barometer, UK findings, published 15 June 2026, based on analysis of more than one billion job advertisements across 27 countries and territories. Entry-level findings are from PwC's analysis of 2.4 million US entry-level roles and are indicative rather than a UK measurement. Figures describe advertised roles and advertised pay. TESS Group provides levy-funded AI apprenticeships, so we have a commercial interest in the build option; the underlying data is PwC's and linked above so you can check it.