AI Jobs Barometer global findings deck
B · Useful, limited Slide companion to PwC's 2026 AI Jobs Barometer that repeats the flagship's job-ad and firm data, adding per-chart method notes and a few extra figures but no new analysis.
Summary based on the full text·Original: about 25 minutes to read
In short
This 45-slide deck presents the global findings of PwC's 2026 Global AI Jobs Barometer. It covers over one billion job ads from 27 markets and company accounts from ORBIS. Every chart comes with a short method box, which makes it easier to cite than the narrative report. The headline is the same: AI is splitting jobs into "professionalised" and "democratised" tracks, and companies in AI-exposed sectors show faster growth in productivity, headcount and wages.
Key numbers
- 68.9% vs 8.6%growth in AI specialist job postings vs all job postings, 2024 to 2025
- 10.7 vs 2.5AI specialist jobs vs other jobs today for every one of each in 2012
- 40%higher productivity growth at the most vs least AI-exposed companies (33.5% vs 24.0% since 2018)
- 7xhow much more likely the most AI-exposed entry-level jobs are to demand traditionally senior skills
As reported by the source.
English·PDF·opens pwc.com
What it reports
- AI specialist postings rose 68.9% from 2024 to 2025, while all postings rose 8.6%. For every AI specialist job in 2012 there are now 10.7, against 2.5 for other jobs.
- Share of AI specialist postings in 2025: tech, media and telecoms 11.4%, professional services 5.6%, financial services 5.4%, health 0.9% (up from 0.7% in 2024).
- The average AI wage premium is 61.9%. By sector it ranges from 118% in consumer markets to 16% in government. The deck notes that the premium does not control for education, experience or location.
- The most AI-exposed companies saw 40% higher productivity growth (33.5% vs 24.0%), faster headcount growth (52% vs 36%) and faster wage growth (24% vs 17%).
- Within the exposed group, the top 20% grew productivity 163%, and the deck says they raised wages 68%. Headcount growth at these firms was 44%, in line with the rest of the group.
- The most AI-exposed entry-level jobs are 7x more likely to require traditionally senior skills, such as strategic decision-making, stakeholder management and mentorship. Seniorised entry roles grew 35% since 2019, while non-seniorised ones fell 10%.
- Examples of democratised roles include software developers, accounting clerks and medical secretaries. Professionalised examples include air traffic controllers, environmental engineers and personnel and careers professionals.
How they got it
The data are the same as the full report: Lightcast postings, PwC's refreshed AI exposure indices, Teeselink and Carey (2026) expertise scores, Loaiza and Rigobon's EPOCH task scores and ORBIS firm accounts. Each slide states its calculation, for example indexing postings to 2012 or comparing advertised salaries between AI and non-AI roles within a sector.
Limits
- The deck adds no new analysis, and several of its own notes undercut the headlines: company exposure is assigned by sector, firms that exited are dropped, and the entry-level trend "is not to say AI is causing these impacts".
- The wage premium compares advertised pay with no controls for education, experience or location.
- The recommendations to business leaders, such as "invest in agentic AI", are PwC advice and do not follow from the data.
Why it matters for companies
Use this deck when you need a chart with its method attached, for a board pack or a workforce plan. The sector table on AI specialist hiring gives a quick benchmark for how much AI skill your industry is buying. The method notes are as useful as the charts: they show which claims are correlations at sector level, which matters before anyone uses "AI expands headcount" to justify a plan.
Summary based on the full text. Read the original for the full argument and data.Open PDF on pwc.com