Trend · rank 19 of 250

Technical & occupational skill shortages

Technological change and ageing workforces are creating persistent shortages in technical, trade and professional occupations, limiting national delivery capacity where vocational training and labour mobility respond slowly.

Human CapitalPeople, health & workwork skillsdemography

Second pass: Carried forward from the first pass, where it was Talent & labour shortages. Held by all three panel models.

Attention over three years

How much this trend is read about on Wikipedia and searched for on Google, week by week, set against the typical trend in the list so that what moves every trend at once is taken out. 100 is this trend's own three-year average. The score measures public attention, which is not the same as the strength of the force: a trend can deepen unnoticed, and a news event can lift attention for a fortnight.

Share of attention: 0.12%rank 174 of 250 · a year earlier 0.10%
Now: 87
Over a year: +6%Steady
Over three years: −36%
Peak: 1444 Feb 2024
Sources: Bothagreement 0.67
Coverage: 10languages · 17 nations

Trailing 4-week average. 100 is this trend’s three-year average.

By language

Wikipedia reading in each language edition where the trend’s pages are read enough to measure (10 of 28). Share is of all the readers counted.

Language	Share	Now	Over a year
English	70%	90	−1%
German	11%	100	+5%
Spanish	5%	159	+101%
Russian	4%	100	+17%
French	3%	95	+16%
Chinese	2%	112	+24%
Japanese	2%	103	+17%
Ukrainian	2%	105	−13%
Dutch	1%	83	+22%
Polish	1%	95	+28%

By country

Google search interest over the three years, as a share of each country’s searching. 100 is the nation where interest is highest. The search terms are English, which favours countries that search in English.

100

The 12 highest of 17 nations with a reading. All countries (CSV).

By region and G20 member

Attention to this trend inside each place, from Google searches made in its countries and Wikipedia reading in the languages mostly read there, averaged where both exist. Each line compares the trend with its own past in that place; the lines do not compare places.

Regions

Place	Read from	Now	90 days	1 year	3 years
North America	Google in 2 countries + Wikipedia in English	101	+22%	+7%	−6%
Europe	Google in 8 countries + Wikipedia in German, French, Polish, Dutch	88	+4%	−10%	−20%
Indo-Pacific	Google in 8 countries + Wikipedia in Japanese, Chinese	98	+17%	−2%	−13%
South Asia	Google in 1 country	152	−1%	+57%	+89%
Gulf and Middle East	Google in 1 country	41	−83%	−23%	−63%
Africa	Google in 1 country	90	+5%	+13%	−41%
Latin America and Caribbean	Google in 5 countries + Wikipedia in Spanish	127	+46%	+38%	+18%
Russia and Eurasia	Google in 1 country + Wikipedia in Russian, Ukrainian	101	+11%	−33%	+20%

G20 members

Place	Read from	Now	90 days	1 year	3 years
Argentina	Google	122	+49%	+23%	+47%
Australia	Google	86	+32%	−22%	−27%
Brazil	Google	74	−19%	−13%	−34%
Canada	Google	101	+47%	−9%	0%
France	Google + Wikipedia in French	83	−18%	+6%	−14%
Germany	Google + Wikipedia in German	95	+16%	−10%	−16%
India	Google	152	−1%	+57%	+89%
Indonesia	Google	109	+55%	+3%	−22%
Italy	Google	82	+24%	−24%	−29%
Japan	Google + Wikipedia in Japanese	100	+39%	+1%	−10%
South Korea	Google	75	+50%	−45%	−34%
Mexico	Google	100	+30%	−19%	−8%
Russia	Wikipedia in Russian	100	+8%	+17%	−20%
South Africa	Google	90	+5%	+13%	−41%
Türkiye	Google	41	−83%	−23%	−63%
United Kingdom	Google	55	−1%	−57%	−51%
United States	Google + Wikipedia in English	104	+21%	+11%	−5%

GINC Share of Attention: this trend's share of all the public attention the trends in the list draw, worldwide and in each region, week by week (a 4-week average). Each place is read from the Wikipedia languages mostly read there and Google searching in its countries; where a place's language is shared with others, as English is, Google stands alone.

Place	Share, last 13 weeks	Rank there	A year earlier	Read from
World	0.12%	174 of 250	0.10%	Wikipedia reading in all 28 languages, and Google searching worldwide
Asia Pacific	0.08%	202 of 250	0.06%	Wikipedia reading in the region's own languages, not English; Google searching in 15 countries, not China
Europe	0.16%	147 of 250	0.21%	German, French, Italian, Polish, Dutch and Swedish reading; Google searching in 10 countries, the UK among them
Africa	0.03%	193 of 250	0.07%	Google searching in 7 countries; Afrikaans and Swahili reading reaches too few trends to count
South America	0.32%	88 of 250	0.12%	Spanish and Portuguese reading, Spanish also read in Spain; Google searching in 5 countries
North America	0.09%	145 of 249	0.08%	Google searching in the United States, Canada and Mexico; English reading cannot be split by country
Oceania	0.06%	163 of 249	0.06%	Google searching in Australia and New Zealand; English reading cannot be split by country
United States	0.08%	152 of 249	0.07%	Google searching; English reading cannot be split by country
United Kingdom	0.02%	217 of 249	0.03%	Google searching; English reading cannot be split by country
India	0.01%	218 of 249	0.01%	Google searching; Hindi, Bengali and Tamil reading reaches too few trends to count, and English cannot be split by country
China	·	·	·	Wikipedia and Google are blocked in China; no open source counts reading there
Russia	0.08%	182 of 203	0.07%	Russian reading, which is also done across the former Soviet states; Google's figures for Russia cannot be bought
Japan	0.17%	148 of 250	0.13%	Japanese reading and Google searching
Germany	0.20%	120 of 250	0.26%	German reading and Google searching
France	0.09%	174 of 250	0.17%	French reading, also done in Africa and Canada, and Google searching
Italy	0.11%	159 of 250	0.14%	Italian reading and Google searching
South Korea	0.12%	154 of 250	0.09%	Korean reading and Google searching
Indonesia	0.12%	110 of 250	0.12%	Google searching; Indonesian reading reaches too few trends to count
Brazil	0.06%	192 of 250	0.07%	Portuguese reading and Google searching
Türkiye	0.00%	100 of 250	0.01%	Google searching; Turkish reading reaches too few trends to count

Relation to each scenario

A trend relates to a scenario when it changes how likely the scenario is, how hard it lands, or is itself sharply changed by it. Each score is the median of three scores given separately by the members of the model panel.

Relation	Scenario	Family
3 · Moderate	An AI deployment step causes abrupt labour displacement S08	Technology and infrastructure
3 · Moderate	A cryptographic breakthrough invalidates digital trust S09	Technology and infrastructure
3 · Moderate	A cross-regional market access compact redirects investment S12 ↗	Economic and trade
3 · Moderate	Cheap firm clean power becomes available at scale S15 ↗	Energy, climate and resources
3 · Moderate	AI-directed research produces a reproducible discovery step S17 ↗	Technology and infrastructure
2 · Low	Hybrid coercion ends in an infrastructure blackout S04	Geopolitical and security
2 · Low	A major disaster disables the national economic core S07	Energy, climate and resources
2 · Low	A novel respiratory pathogen exceeds health surge capacity S10	Health
2 · Low	A validated farming package raises water-efficient output S16 ↗	Energy, climate and resources
2 · Low	A public service platform reaches inclusive operation S18 ↗	Technology and infrastructure
2 · Low	Affordable preventive treatments reduce chronic illness S19 ↗	Health
2 · Low	A live outbreak proves rapid distributed pandemic defence S20 ↗	Health
1 · Very low	Critical trade divides into rival blocs S01	Economic and trade
0 · Not related	A global funding seizure reaches sovereign balance sheets S02	Economic and trade
0 · Not related	A regional war closes a globally important sea route S03	Geopolitical and security
0 · Not related	A disputed transfer of power breaks effective government S05	Geopolitical and security
0 · Not related	Two breadbasket failures trigger a food availability crisis S06	Energy, climate and resources
0 · Not related	A creditor agreement releases fiscal capacity S11 ↗	Economic and trade
0 · Not related	A great-power agreement lowers economic security barriers S13 ↗	Geopolitical and security
0 · Not related	A verified Middle East settlement restores access S14 ↗	Geopolitical and security

Similarity = 0.3 × shared tags (Jaccard) + 0.3 × likeness of scenario profiles (cosine) + 0.3 × likeness of names and descriptions (TF-IDF cosine) + 0.1 if in the same capability domain, cut into seven levels at 0.12, 0.22, 0.33, 0.45, 0.58, 0.72. Shown at Moderate and above.

Similarity	Trend	Theme	Rank
4 · High	Population ageing	People, health & work	96
4 · High	Youth population expansion	People, health & work	146
4 · High	Skilled & research talent migration	People, health & work	208
4 · High	Persistently low fertility	People, health & work	243
3 · Moderate	Civil service capability & pay	State capacity & governance	2
3 · Moderate	Entrenched opportunity inequality	People, health & work	9
3 · Moderate	AI & knowledge-work automation	People, health & work	53
3 · Moderate	Health system demand imbalance	People, health & work	56
3 · Moderate	Informal employment persistence	People, health & work	84
3 · Moderate	Care labour demand growth	People, health & work	86
3 · Moderate	Lifelong learning & digital reskilling	People, health & work	132
3 · Moderate	Foundational learning deficits	People, health & work	162
3 · Moderate	Youth employment exclusion	People, health & work	177
3 · Moderate	Graduate skill mismatch	People, health & work	178
3 · Moderate	Gender participation divergence	People, health & work	192
3 · Moderate	Migrant integration demands	People, health & work	205

Technical & occupational skill shortages

Sensitivity and network position