WEF_Future_of_Jobs_2023

(SERGIO PINHEIROFdUjs8) #1
Trend outlook

GTrelnodbs amol (^) stt rmeonsdt likse (^) lay nto ddr (^) ivteh iendiurs itmry tpranascfotr (^) moatnio (^) njo anbd cthreier eaxptieocnted impact job creation, ordered by net
effect (share of organizations surveyed)
Job creator Job displacer Net effect Global net effect
I-n 10 c 0 %reased adoption of new and frontier technologies + 100 %
67 %
C- 10 o 0 n%sumers becoming more vocal on environmental issues + 100 %
63 %
B- 1 r 0 o 0 %adening digital access + 100 %
63 %
B- 1 r 0 o 0 %ader application of Environmental, Social and Governance (ESG) (^) +s 1 t 0 an 0 %dards
57 %
C- 10 o 0 n%sumers becoming more vocal on social issues + 100 %
45 %
C- 10 li 0 m%ate-change induced investments into adapting operations + 100 %
42 %
R- 1 i 0 s 0 %ing cost of living for consumers + 100 %



  • 5 %
    S- 1 u 00 p%ply shortages and/or rising cost of inputs for your business + 100 %

  • 21 %


TTeecchnholnogoielso mgoisets m (^) oastn lidke (^) lty htoe dirriv (^) eim indpusatcryt tr (^) anosnfo (^) rjomatbio cnr anead tthieoirn expected impact job creation, ordered
by net effect (share of organizations surveyed)
Job creator Job displacer Net effect Global net effect
B- 10 ig 0 %-data analytics + 100 %
78 %
E- 1 d 00 u%cation and workforce development technologies + 100 %
65 %
E- 1 n 00 c%ryption and cybersecurity + 100 %
63 %
D- 10 ig 0 %ital platforms and apps + 100 %
63 %
A- 1 r 0 t 0 i%ficial intelligence (e.g. machine learning, neural networks) + 100 %
59 %
A- 1 u 00 g%mented and virtual reality + 100 %
53 %
C- 10 lo 0 %ud computing + 100 %
50 %
I-n 10 te 0 %rnet of things and connected devices + 100 %
50 %
Role outlook
CFivhe-uyerarn s itnru (^) ctfiurvale lab yeouar-rfosrce churn (percent) 19 %
Global 23 %
KRoelesy mrooslte ssele fcoterd bbyu osrgianniezsatsio (^) nstr saurnvseyfeodr (asm eaithtieor ngrowing, stable or declining), ordered by net role
growth, and their net growth and structural churn (percent)
ROLES NET^ GROWTH INCDHUUSRTNRY GCLHOUBRANL
AI and Machine Learning Specialists^24 %^40 %
Mechanical Engineers^18 %^20 %
STehciph (^) nandicians Aircraft Controllers and 18 % 14 %
Industrial and Production Engineers^19 %^15 %
General and Operations Managers^30 %^14 %
Assembly and Factory Workers^11 %^17 %
ACclecrokusnting, Bookkeeping and Payroll 24 % 29 %
Business Services and Administration
Managers^28 %^22 %
Administrative and Executive Secretaries^15 %^35 %
Data Entry Clerks^41 %^42 %
MClaterekrsial-Recording and Stock-Keeping 51 % 32 %
Human-machine frontier
HTasukms paernfo-rmmeda bcyh hiunmean fsr oannd tmiacerhines today and in 2027 (share of total)
Human Machine Industry Frontier Global Frontier
ALL TASKS
Now
62 % 38 %
2027 Forecast
53 % 47 %
Workforce strategy outlook
TExapelectnedt cohuantgleo oin ktal (^) einnt (^) av (^20) ai (^2) lab (^7) ility, development and retention in the next five years (share of organizations
surveyed)
Improving Worsening Global average Global average
Talent availability when hiring
32 % -^100 % +^100 % 53 %
Talent development of existing workforce
0 % -^100 % +^100 % 90 %
Talent retention of existing workforce
15 % -^100 % +^100 % 55 %
Industry Profile 1 / 2
Automotive and Aerospace



  • 50 % 0 50 %


Global Employee (millions, ILO estimates)
22. 9
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