普华永道：2026年全球AI就业晴雨表-AI时代就业的两种未来图景（2026年-英文版）

2026

Global

AI

Jobs

BarometerTwo

futures

for

jobsin

an

AI

eraPwC’s

2026

Global

AI

Jobs

Barometer2PwCIntroduction301

A

two-track

jobs

market

is

emerging402

A

two-track

jobs

market

is

emerging

at

the

entry

leveltoo1103

The

AI

skills

earthquake

is

accelerating1404

‘Superstar’

companies

are

capturing

the

greatest

gains

from

AI1805

Wage

premiums

for

AI

skills

continue

to

rise2206

Hiring

of

AI

specialists

is

rising

sharply,

indicating

growing

AIinvestment24Conclusion:

Next

Steps26Table

of

contentsPwC’s

2026

Global

AI

Jobs

Barometer3PwCAI

is

creating

a

two

track

labour

market.That

is

a

key

findingfrom

our

analysis

of

over

one

billion

online

job

advertisementsacross

six

continents.Rather

than

simply

replacing

jobs,

AI

is

reshaping

theminfundamentally

differentways.

At

one

end

of

the

spectrum,

AI

is

professionalisingwork,

automating

away

routine

tasks

and

elevating

the

importance

of

human

expertise,

judgementand

creativity.

At

the

other

end,

it

is

democratisingwork,

reducing

the

skillbarriers

for

complex

tasks

and

shifting

roles

toward

less

specialised

activities.This

divergence

is

creating

two

tracks

in

the

labour

market

with

markedly

different

outcomes.

The

22%

of

jobs

that

are

being

professionalised

are

growingtwice

as

fast

as

democratised

jobs

(52%

of

jobs)

and

seeing

42%higherwagegrowth

since2021.The

study

reveals

a

potentially

counter

intuitive

finding

-

greaterAI

exposure

islinkedtoheadcountgrowth,

notdecrease.

Why?While

AI

can

deliver

significantvalue

through

productivity

improvements,

its

greatest

potential

comes

throughredesigning

how

companies

operate.

Reinvention

is

the

key

to

unlocking

themaximum

benefits

from

AI,

andour

data

suggests

the

companies

that

areachieving

the

largest

productivity

gains

are

taking

that

route.

Headcount

growthat

the

most

exposed

organisations

is

double

growth

at

the

least

exposed,

withwages

also

growing

significantly

faster.

Consistent

with

other

PwC

research,

wefind

a

‘superstar’

effect

-

while

the

companies

most

exposed

to

AI

are

seeingproductivity

growth

relative

to

a

2018

baselineof

34%,

if

you

zoom

in

on

thetop20%

of

companies

in

this

group,

that

number

rises

to

163%.As

work

changes

rapidly,

skill

needs

change

rapidly

too

-

with

employersincreasinglyfocused

on

attributes

that

are

distinctively

human.

Skillsrequired

for

the

most

AI

exposed

jobs

are

changing

twice

as

fast

as

in

the

least

exposedroles,

while

new

tasks

that

rely

on

skills

like

empathy,

judgement,

and

creativityare

added

2.5x

faster.A

two

track

labour

market

is

emerging

atevery

level.

Analysis

of

US

data

findsthat

entrylevel

jobs

highlyexposed

to

AI

are

evolving

to

require

traditionally

seniorcapabilities

(such

as

motivational

leadership,

strategic

decision

making

and

teambuilding)

which

now

account

for

52%

of

new

skillsrequired

for

these

jobs.

For

entrylevel

jobs

least

exposed

to

AI,

theequivalentnumber

is

just

7%.

Entry

level

jobs

that

have

been‘seniorised’in

this

waycontinue

togrowinnumber(up

35%),

whilegloballythe

number

of

entry

level

jobs

in

roles

highly

exposed

to

AI

has

flatlined.There

is

a

clear

lesson

from

thisyear’s

AI

Jobs

Barometerfor

both

businessleaders

and

workers:

winning

is

not

just

about

using

technology,

it

is

about

humanskills.The

more

AI

is

deployed,

the

more

distinctly

humanexpertiseisvalued.

Fororganisations,

the

focus

should

be

onredesigningwork

not

just

automating

tasks,while

for

individuals

it

will

be

important

to

make

sure

they

hone

their

leadership,judgement,

creative

and

teamwork

skills

so

they

can

do

what

AI

cannot.PwC’s

2026

Global

AI

Jobs

Barometer4PwCA

two-track

jobs

marketis

emergingA

puzzle:

why

does

AIautomationappear

to

benefitsome

occupations?Last

year’s

AI

JobsBarometeruncovered

a

puzzle.

Despite

widespread

concernsthat

AI

automation

may

displace

workers,

we

found

that

job

numbers

and

wagesarerising

in

jobs

highly

automatable

by

AI.AI

automation

makes

some

roles

more

expertWebelieve

that

whatmattersis

howautomationreshapes

the

role

–

specifically,whether

AI

automation

grows

or

diminishes

the

need

for

human

expertise(defined

as

specialised

knowledge

or

capabilities).1

In

this

year’s

Barometer,we

test

this

idea.011

Expertise,

Autor

&Thompson,2025PwC’s

2026

Global

AI

Jobs

Barometer5PwC123Three

types

of

jobsAll

jobs

globally

fall

into

one

of

three

categoriesLow

AI

exposure

jobs:

Jobs

that

include

few

tasks

in

which

AIhas

capabilities,

so

AI

is

likely

to

have

limited

impact

on

the

role.Examples:

Chefs,

construction

workers,

mechanics.Professionalised

jobs:

Jobs

reshaped

by

AI

to

demand

moreexpertise.

Examples:

Radiologists,

employment

recruiters,

air

trafficcontrollers.Democratised

jobs:

Jobs

reshaped

by

AI

to

demand

less

expertise.Examples:

Software

developers,

loan

officers,

finance

managers.See

Methodology

appendix

for

more

information.First,

let’s

look

at

how

AI

can

increase

the

need

for

expertise.

By

taking

onthe

relatively

basic

tasks

in

a

job,

AI

leaves

the

more

complex

and

experttasks

topeople.For

example,

AI

helps

lawyers

with

basic

tasks

like

documentsummarisation,

leaving

people

tougher

tasks

like

building

a

case

in

court.

Orconsider

employment

recruiters;

AI

can

now

automatically

screenCVs,

leavingrecruiters

more

demanding

tasks

like

negotiating

contracts.

We

call

jobs

mademore

expert

by

AI

‘professionalised.’On

the

other

hand,

AI

can

take

away

the

relatively

more

expert

tasks

in

a

role,leaving

the

less

demanding

tasks

for

people.

Consider

inventory

clerks.

AI

nowperforms

complex

tasks

like

managing

inventory,

leaving

people

less

experttasks

like

moving

stock

in

warehouses.

We

call

these

jobs

‘democratised.’AI

is

having

two

different

impacts

on

jobs

depending

on

whether

it

isautomating

more

or

less

expert2

tasks52%ofjobs

are

beingDEMOCRATISED(shifted

toward

less

expert

tasks)Example:

Inventory

Clerk22%ofjobsare

beingPROFESSIONALISED(shiftedtoward

more

expert

tasks)Example:RecruiterMore

expert

tasks

like

negotiate

contractsAI

automatedLess

expert

tasks

like

screen

CVsMore

expert

tasks

like

manage

inventoryAI

automatedLess

expert

tasks

like

move

stockRemainRemain2

Expert

=

requiringspecialised

knowledgeor

capabilityPwC’s

2026

Global

AI

Jobs

Barometer6PwC20AI

raisesexpertise

10

required0-10-20-30-40-50-60Low

AI

exposure

jobs26%

of

advertised

jobsDemocratised

jobs52%

of

advertised

jobsProfessionalised

jobs22%

of

advertised

jobs00.51Of

380

ISCO-08

job

categories,

74

are

Professionalised,

125

are

democratised,

and

181

have

low

exposure

to

AI.

40SOC-2018

occupations

are

excluded

from

the

analysis

because

of

limited

data

quality

from

Teeselink

et

al.

for

ranking

expertise.The

ProfessionalisedvsDemocratised

frameworkmovesuspastabackward-looking

view

of

AI’s

impact

–

cataloguing

old

tasks

that

have

been

automated

-

to

a

forward-looking

view

ofhow

AI

reshapes

roles

for

thefuture.

Our

hope

isthat

Professionalised

vs

Democratised

offers

a

clearer

lens

for

understanding

thefuture

of

jobs

in

an

AI

era

–

and

as

we

will

see

below,

it

may.Software

developersSystems

Finance

administrators

managers

MedicalsecretariesCommercialsales

representativesEmployment

agents

and

contractorsand

servicersBuilding

Electronics

mechanicsconstruction

labourersWindow

cleanersPharmacistsEnvironmentalengineersHuman

resource

managersArchivists

and

curatorsCredit

and

loans

officers0.25Lower

AI

exposure0.75Higher

AI

exposureAIreducesexpertiserequiredOurdata

shows

that

AI

significantly

reduces

the

human

expertise

neededfor

some

democratised

jobs.

For

medical

secretaries

and

IT

systemsadministrators,

for

example,

AI

automates

a

large

share

of

the

expert

tasksformerly

performed

by

people.

(Please

see

the

Methodology

appendix

for

a

fullexplanation

of

how

expertise

change

is

calculated,

drawing

on

the

workof

Teeselink

and

Carey

(2026).AI’s

impact

on

professionalised

and

democratised

jobs

will

be

widely

felt.

Abouthalf

of

advertised

jobs

globally

are

democratised,

while

arounda

quarter

areprofessionalised

and

the

remaining

quarter

have

low

exposure

to

AI.AI’s

impact

on

expertise

is

especially

strong

for

democratised

jobsPwC’s

2026

Global

AI

Jobs

Barometer7PwC3

US

Current

Population

Survey

–

FT

analysis,

‘What

the

AI

Jobpocalypse

narrative

misses,’

2025Professionalised

jobs

are

pullingahead

innumbers,

complexity,

and

pay

–

whiledemocratised

jobs

fall

behindTo

understand

the

possible

future

trajectories

ofprofessionalised

anddemocratised

jobs,

consider

what

happened

when

spreadsheets

came

intowidespread

use

in

the

1980s.Spreadsheets

could

perform

many

of

the

more

challenging

parts

of

the

roles

ofbookkeepers

and

accounting

clerks,

effectivelydemocratising

theserolesandsending

numbers

of

these

jobs

intoa

gradual

but

steady

decline.

Financialanalysts,

on

the

other

hand,

now

had

a

powerful

new

tool

that

enabled

them

toperform

analysis

withunprecedented

complexity

and

fluidity,

effectivelyprofessionalising

theirjobs.

Numbers

of

financial

analysts

began

a

steep

ascentthat

has

continued

into

the

2020s

as

new

fields

of

financial

analysis

werepioneered

–

many

with

rising

wages

(USdata).3Our

analysis

shows

that

professionalisedjobs

across

the

world

are

indeedbecoming

more

complex,

demanding

new

skills

at

twice

the

rate

ofdemocratised

jobs.1.81.61.41.21.00.02018

2019

2020

2021

2022

2023

2024

2025Source:

PwC

analysis,

Lightcast

data,

Teeselink

and

Carey

(2026)Notes:

Due

todatarobustness,

weonly

include

the

six

countries

for

which

Lightcastdatais

available

from

2012onwards.Number

ofskillsdemanded,

relative

to2018Professionalisedrolesare

demanding

additional

skills

at

twice

therate

of

democratised

roles,

and

the

gap

has

widened

since

2022Number

of

skills

demanded

relative

to

2018,democratised

vsprofessionalisedoccupations,globalDemocratised

Professionalised2.0Professionalised:68%

growthDemocratised:33%

growthPwC’s

2026

Global

AI

Jobs

Barometer8PwC42%The

rising

demands

onProfessionalised

workersare

reflected

in

42%fastersalarygrowthvsdemocratised

jobsThe

rising

demands

on

professionalised

workers

are

reflected

in

42%

fastersalary

growth

vs

democratised

jobs,

and

the

gap

has

grown

since

2022

when

AIuse

soared.1.41.3Growth

in

advertisedsalary

(relative

to2021)42%

fastersalary

growth

for

ProfessionalisedjobsProfessionalised

roles

have

seen

42%

faster

growth

in

average

salariesrelative

to

democratised

roles,with

a

growing

gap

from

2022Growth

in

average

advertised

salary,

democratised

and

professionalised

jobs,

relative

to

2021,

global

Democratised

Professionalised1.21.11.02021

2022

2023

2024

2025Teeselink’s

expertise

data

was

providedto

us

at

SOC-2018

level.

SOC

classification

inLightcast

jobs

data

isnotavailable

outsideof

the

US.

Thus,

in

order

to

produce

global

figures

andmetrics

for

our

expertise

analysisusing

Lightcast

data,

we

map

Teeselink’s

expertise

scores

from

SOC-2018

to

ISCO-08

for

this

purpose

only.professionalisedsalaries

have

grown

37%

since

2021

and

democratised

by

26%

-

a

42%

gap.Source:

PwC

analysis,

Lightcast

data,

Teeselink

and

Carey

(2026)Notes:

Due

todatarobustness,weonly

include

the

six

countries

for

whichLightcastdata

is

available

from

2012onwards.Turningtojob

numbers,

we

find

–

encouragingly

–

that

both

democratised

andprofessionalisedjobs

are

continuing

togrow.However,

professionalised

jobsare

growingmarkedlymore

quickly

than

democratised

ones.

This

suggests

agradual

rebalancingof

the

jobs

market

away

from

democratised

jobs.Professionalisedjobs

are

growing

twice

as

quickly

as

democratised

jobsNumber

of

job

postings

relative

to

2018,

2018

-

2025,

democratised

and

professionalised

jobs,

globalDemocratised

Professionalised1.71.61.51.41.21.11.00.90.82018

2019

2020

2021

2022

2023

2024

2025Source:

PwC

analysis,

Lightcast

data,

Teeselink

and

Carey

(2026)Notes:

Due

todatarobustness,

weonly

include

the

six

countries

for

which

Lightcastdatais

available

from

2012onwards.1.3Number

of

job

postings,relative

to

2018Professionalised:39%

growthDemocratised:17%

growthPwC’s

2026

Global

AI

Jobs

Barometer9PwCOur

data

suggests

that

some

jobs

expected

to

be

displaced

or

devalued

by

AIautomation

–

such

as

air

traffic

controllers

and

marketingmanagers,bothofwhich

are

professionalised

–

mayinfact

see

growing

demand,

wages,

and

skillrequirements.

It

may

be

time

for

the

debate

on

work

and

AI

to

move

on

from

fearof

AIautomation

to

more

nuanced

questions

about

how

AIreshapes

the

valueworkers

can

deliver.Other

forces

shaping

AI’s

impact

on

jobsThe

broad

global

trend

is

for

professionalised

jobs

to

have

higher

growth

in

jobnumbers

and

wages

–

while

democratised

jobs

see

the

opposite

–

but

there

willbe

exceptions.Consider

nursing

aides,a

professionalised

job.

AI

professionalises

thisroleby

taking

on

some

more

basic

tasks

like

tracking

vital

signs

and

schedulingmedication,

enabling

nursing

aides

to

spend

more

time

on

more

expert

tasks

likebuildingrelationshipswith

patients

or

responding

to

unexpected

situationswithempathy

and

discretion.PwC’s

2026

Global

AI

Jobs

Barometer10PwCWe

might

expect

nursing

aides

to

follow

the

path

of

1980’s

financial

analystsnewly

equipped

with

spreadsheets

–

that

is,

to

be

even

more

in

demand

astechnology

helps

them

step

up

to

perform

more

expert

tasks.

But

AI’s

impact

onnursing

may

beconstrained

by

forces

such

as

regulation,

challenges

in

workflowintegration,

or

a

limited

supply

of

job

candidates

willing

to

enter

a

demandingprofession.Or

consider

child

care

services

managers,

a

democratised

role.

AI

can

assist

with

some

of

the

more

expert

parts

of

this

role

from

budget

management

tocomplying

with

government

regulation.

But

far

from

stagnating,

job

postings

forchild

care

services

managers

have

more

than

doubled

since

2019

given

the

vastlatent

demand

forchildcare

-

combined

withdemocratisationof

the

role

whichenables

many

more

people

to

perform

it.4Four

questions

to

help

foresee

the

future

of

any

jobOur

analysissuggests

four

questions

for

business

leaders

and

workers

toconsider

as

they

seek

to

understand

the

future

of

a

particular

job

role:Expertise:

How

is

AI

changing

the

level

of

human

expertise

required?Supply

and

Demand:

How

might

demand

for

this

job

–

and

the

supply

ofworkers

to

fill

it

-

change

as

AI

reshapes

the

role?AI’slimitations:

Where

is

human

involvement

needed

tooverseeor

assist

AI,forexample

tocheck

the

qualityofAI’s

output

or

manage

atypical

cases?Environmental

forces:How

do

external

forces(frombusiness

processbottlenecks

to

regulation)

constrainor

affect

the

use

of

AI?Considering

these

four

questions

–

starting

with

expertise

change

–

can

help

touncover

how

AI

is

redefining

the

partnership

between

people

and

technologyina

given

job,

and

what

the

future

may

hold

for

that

role.4

David

Autor

argues

in

Expertise

(2026)

that

as

technologyreduces

the

expertise

required

for

a

job,

the

pool

ofqualifiedcandidatesexpands

which

can

in

turn

enable

the

occupation

to

grow

(while

wages

may

stagnate).

Think

of

taxi

drivers,

for

example;

as

satellite

navigation

reducedtheneedfor

specialisedroad

knowledge,

many

morepeoplecan

fill

this

job

–leadingnumbersof

taxidriversto

soarwhile

wagesstagnate.This

is

what

appearsto

be

happeningwith

childcareservice

managers;

job

listingshavemore

than

doubled

since2019(growing111%)whilewages

havegrownonly

8%.1234PwC’s

2026

Global

AI

Jobs

Barometer11PwCA

two-track

jobs

marketis

emerging

at

the

entrylevel

tooThe

well-known

decline

in

AI-exposed

entry

leveljob

numbers

hides

a

deeper

storyA

recent

Stanford

University

analysis

found

a

16%

decline

inentry

level

jobs

inAI-exposed

fields.

Much

deeper

declines

in

entry

level

roles

have

been

noted

insomeindustries

heavilyexposed

to

AIsuch

asfinance

and

tech.5The

trend

is

likely

to

continue

and

perhaps

intensify.

PwC’s

latest

Global

CEO

Survey

finds

that

49%

of

CEOs

expect

AI

adoption

to

decrease

junior

hiring

inthe

next

threeyears

(vs

12%

for

seniorhiring).025

Canaries

in

the

Coal

Mine?

Six

Facts

about

the

recentEmployment

Effects

of

Artificial

Intelligence,Brynjolfsson

et

al,

2025;The

Crisis

of

Entry

level

Labor

in

the

Age

of

AI,

Jacob

Jacquet,

2025PwC’s

2026

Global

AI

Jobs

Barometer12PwCBelow,

we

offer

one

way

toknow

which

entry

level

jobs

are

most

and

least

likelytodecline

in

number

-

a

vital

pieceof

information

for

junior

workers

seeking

tobuild

successful

careers

(and

for

the

companies

that

employ

them).The

answer

liesin

how

AI

is

reshaping

the

need

for

humanexpertise.Entry

leveljobs

most

exposed

to

AI

(such

as

juniordataanalyst)

are

rapidly

evolvingtodemand

more

skills

traditionallyrequired

of

seniorworkers.6In

fact,

the

most

AI-exposed

entry

level

jobs

are

now

seven

times

more

likely

torequire

traditionally

senior

skills

than

the

leastAI-exposed

ones.

These

seniorskillsdemand

EQ,

judgment,

and

leadership

ability

at

a

level

not

historicallyrequired

in

many

junior

roles.Did

your

first

job

require

these

skills?Examples

of

skills

traditionally

required

in

more

senior

roles

that

arenow

required

in

many

AI-exposed

entry

level

rolesMotivational

leadershipTeam

buildingPeople

managementStakeholder

managementProcess

managementMentorshipData-driven

decision

making6

Askill

is

defined

as

traditionally

senior

if

it

had

>50

mentions

in

experienced

(non-entry-level),

high

AIexposure

job

postings

in

2019

and

≤5

mentionsin

entry-level,high

AI

exposure

postings

in

201949%PwC’s

latestGlobal

CEOSurvey

finds

that

49%

ofCEOs

expect

AI

adoptionto

decrease

junior

hiringin

thenextthreeyearsAcross

advanced

economies,

job

postings

are

growing

more

slowly

forentry

level

workers

more

exposed

to

AINumber

of

entry-level

job

postings

relative

to

2012,

by

AI

exposure

quartile,

global9.0

ChatGPT

8.07.06.05.04.03.02.01.00.02012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025Source:

PwC

analysis,

Lightcast

dataNotes:The

“Years

of

Experience”

variable

from

Lightcastis

used

as

aproxy

for

early-career

jobs.

A

posting

is

defined

as

an

early-career

job

if

itsyearsof

experience

listed

is

between

0-2

years.

Due

todataavailability,we

only

include

thefollowingcountries

in

our

analysis:

Canada,

Singapore,

UK

and

US

(1)

Careful

interpretation

of

this

chart

is

necessary

–

this

is

not

to

say

AI

is

causing

these

impacts.

Other

shocks

/

structural

characteristics

of

occupations

in

the

Top

25%

may

also

contribute

to

the

observed

trend.

(2)

Results

are

mainly

driven

by

US

datawhich

accounts

for

c.73%

of

total

job

postings

in

the

sample

of

countries

with

data

available

from

2012.Number

of

job

postings,relative

to

2012releasedEarly

careerBottom25%Lowest

AI

exposureThird

25%Second

25%Top25%HighestAIexposureOnly

quartile

where

early-career

vacancieshave

flatlinedPwC’s

2026

Global

AI

Jobs

Barometer13PwCIn

other

words,

not

all

AI-exposed

entry

levelrolesare

shrinking.

The

AI-exposedentry

level

is

in

effect

being

Seniorised,

with

increasing

opportunities

for

workerswhose

jobs

are

reshaped

by

AI

to

be

even

more

complex

and

demanding.Companies

(and

educators)

must

rethink

how

they

train,

mentor,

and

scaffoldearly

career

pathways

to

help

junior

workers

build

and

demonstrate

senior

skillsmuch

earlier.35%Entry

level

roles

that

nowrequire

more

than

10

new,traditionally

senior

skillsare

thrivingwithagrowthrate

of35%Zoom

in

on

the

most

AI-exposed

set

of

entry

level

jobs,

and

a

striking

divergenceis

apparent.Entrylevel

roles

that

now

require

more

than

10

new,

traditionallysenior

skills

are

thriving

with

a

growth

rate

of35%,

whileotherentry

level

rolesdecline

in

number.AI-exposed

entry

level

roles

have

very

different

job

growth

outcomesdepending

on

whether

they

are

being

upskilled

to

demand

moretraditionally

seniorabilitiesChange

in

entry-level

job

postingsbetween

2019

and2025,

seniorisedvs

non-seniorised

roles,

top

AIexposure

quartile,

US30%25%20%15%10%5%0%-5%-10%35%40%-15%Source:

PwC

analysis,

Lightcast

dataNotes:(1)

An

entry-level

job

posting

is

classified

as

“seniorised”

if

it

contains≥10mentionsof

a

skill

that

is

bothnewand

traditionally

senior.Askill

isdefinedas

new

fora

given

occupation

if

it

has>10mentions

in

entry-levelpostings

in2025but

≤5mentions

in

entry-level

postings

for

thesame

occupation

in

2019.

Askill

is

defined

as

traditionally

senior

if,

within

the

sameAIexposurequartile,

ithad>50mentions

in

experienced

(non-entry-level)

jobpostingsin2019

and≤5mentions

in

entry-levelpostings

in

2019.166Non-SeniorisedSeniorised35%-10%Change

in

entry

level

jobpostings

between

2019

-

2025

%PwC’s

2026

Global

AI

Jobs

Barometer14PwCThe

AI

skills

earthquakeis

acceleratingAI

is

rapidly

changing

the

skills

workers

needto

succeedProfessionalised

roles

in

particular

are

becoming

more

complexanddemanding,

but

that

does

not

mean

workers

in

democratised

rolescan

standstill

when

it

comes

to

skill

development.Skills

needed

for

the

most

AI-exposed

jobs(including

both