Living dashboard
Talent & Augmented Skills Observatory
Work is not disappearing as fast as the skills it demands are changing. By 2030 two in five core skills will have shifted and nearly six in ten workers will need training; those who pair their craft with AI command a measurable wage premium. The question is no longer whether you will be replaced, but whether you will have real access to relearn.
Work is not disappearing as fast as the skills it demands are changing. By 2030 two in five core skills will have shifted and nearly six in ten workers will need training; those who pair their craft with AI command a measurable wage premium. The question is no longer whether you will be replaced, but whether you will have real access to relearn.
- No editorial index
- Curated monthly
- Weekly source watcher
- Experimental
Evidence vs hype
Three planes so you don't confuse the skills that are said to change with the ones the market is already paying for.
Projected skill change
- What it measures
- What share of skills will transform according to models and projections (39% by 2030; ~70% per LinkedIn).
- Examples
- WEF Future of Jobs; LinkedIn Economic Graph estimates.
- Why it matters
- It sets the ceiling of change: the maximum relearning the decade could demand.
- If misread
- Reading the projection as a calendar. It is an aggregate expectation, not an obsolescence schedule.
Employer-declared demand
- What it measures
- What firms say they need and plan: reskilling, hiring AI-skilled profiles, perceived barriers.
- Examples
- WEF employer survey (63% cite the skill gap; 85% will prioritise upskilling).
- Why it matters
- It is the leading signal: where demand is moving before it shows up in wages.
- If misread
- Declared intent is neither committed budget nor realised hiring.
Observed market outcome
- What it measures
- What is already measured: paid wage premium, real skill-change velocity, employment and productivity growth.
- Examples
- PwC Global AI Jobs Barometer (56% premium; productivity 7%→27%).
- Why it matters
- It is the counterweight to hype: what is actually happening in pay and jobs, not what is announced.
- If misread
- It is an early-phase snapshot; the aggregate can hide losses in specific tasks.
Verified claims
Verified evidence
Claims traceable to their primary source, with how to read them and their limits.
Tier 1 = multilateral bodies (WEF). Tier 2 = labour-market analytics (PwC, McKinsey, LinkedIn).
Tier 1Official projection
39 %
of core skills changing by 2030
39% of workers' core skills will change or become outdated between 2025 and 2030.
- Verified
- High confidence
- Skill velocity
- Geography: Global
- Timeframe: 2025-2030
- How to read it
- High as it is, this figure is down from the 44% projected in the 2023 edition, a sign of some stabilisation.
- What it does NOT prove
- It is an employer estimate about the future, not a measurement of skills already lost.
- Source
- World Economic Forum, Future of Jobs Report 2025
Tier 1Official projection
59 %
of workers needing training by 2030
59% of workers will need training by 2030: 29% could be upskilled in their current roles, 19% reskilled and redeployed, and 11% would not receive the reskilling they need.
- Verified
- High confidence
- Reskilling need
- Geography: Global
- Timeframe: 2030
- How to read it
- The challenge is not only training more people, but closing the 11% that today falls outside any training at all.
- What it does NOT prove
- The 29/19/11 breakdown is an aggregate projection; it does not guarantee how it will split across countries or sectors.
- Source
- World Economic Forum, Future of Jobs Report 2025
Tier 1Employer survey
63 %
of employers cite the skill gap as the top barrier
63% of employers identify the skills gap as the biggest barrier to transforming their business in 2025-2030.
- Verified
- High confidence
- Skill gap
- Geography: Global
- Timeframe: 2025-2030
- How to read it
- Companies see the lack of talent, not the lack of technology, as their main brake.
- What it does NOT prove
- It is the self-reported perception of surveyed employers, not an objective measurement of the gap.
- Source
- World Economic Forum, Future of Jobs Report 2025
Tier 1Employer survey
85 %
of employers will prioritise upskilling
85% of employers plan to prioritise upskilling their workforce, and 50% expect to move staff from declining to growing roles.
- Verified
- High confidence
- Reskilling need
- Geography: Global
- Timeframe: 2025-2030
- How to read it
- The intent to invest in training is nearly universal; the challenge is turning intent into real, accessible programmes.
- What it does NOT prove
- It measures stated plans, not committed budget or training outcomes.
- Source
- World Economic Forum, Future of Jobs Report 2025
Tier 2Labour-market analysis
56 %
AI-skills wage premium
Workers with AI skills earn a 56% wage premium, up from 25% the previous year.
- Verified
- High confidence
- AI-skills premium
- Geography: Global
- Timeframe: 2025
- How to read it
- Knowing how to use AI is no longer a bonus: it translates into salary, and the premium more than doubled in a year.
- What it does NOT prove
- It draws on job postings across a set of countries; it reflects advertised, not necessarily paid, wages and may skew towards highly qualified profiles.
- Source
- PwC, 2025 Global AI Jobs Barometer
Tier 2Labour-market analysis
66 %
faster skill change in AI-exposed jobs
The skills employers ask for change 66% faster in the occupations most exposed to AI.
- Verified
- High confidence
- Skill velocity
- Geography: Global
- Timeframe: 2025
- How to read it
- Where AI arrives, the shelf life of each skill shortens: the pressure to relearn is greatest exactly where the technology is most intense.
- What it does NOT prove
- It measures turnover in the skills named in job postings, not the real depth of change on the job.
- Source
- PwC, 2025 Global AI Jobs Barometer
Tier 2Labour-market analysis
27 %
productivity growth in AI-exposed industries
Employment is still growing in virtually every AI-exposed occupation, including the most automatable ones, and productivity in the most exposed industries nearly quadrupled (from 7% to 27%).
- Verified
- Medium confidence
- Work augmentation
- Geography: Global
- Timeframe: 2018-2024
- How to read it
- In this phase, AI is augmenting human work more than replacing it: the dominant lever is productivity, not layoffs.
- What it does NOT prove
- It is a snapshot of an early phase; it does not project what happens if automation deepens, and aggregate job growth can mask losses in specific tasks.
- Source
- PwC, 2025 Global AI Jobs Barometer
AI figures come from job-posting analysis, not censuses; they reflect stated demand, not necessarily filled jobs.