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
B- 1 r 0 o 0 %ader application of Environmental, Social and Governance (ESG) (^) +s 1 t 0 an 0 %dards
67 %
I-n 10 v 0 e%stments to facilitate the green transition of your business + 100 %
63 %
C- 10 li 0 m%ate-change induced investments into adapting operations + 100 %
58 %
I-n 10 c 0 %reased adoption of new and frontier technologies + 100 %
38 %
C- 10 o 0 n%sumers becoming more vocal on environmental issues + 100 %
37 %
B- 1 r 0 o 0 %adening digital access + 100 %
27 %
S- 1 u 00 p%ply shortages and/or rising cost of inputs for your business + 100 %



  • 23 %
    S- 1 l 0 o 0 %wer global economic growth + 100 %

  • 29 %


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
E- 1 n 00 v%ironmental management technologies (e.g. pollution abatement, r+e 10 c 0 y%cling)
60 %
C- 10 li 0 m%ate-change mitigation technology (Alternative Energy, Greenhous+e 10 0 g%ases...
58 %
E- 1 d 00 u%cation and workforce development technologies + 100 %
44 %
B- 10 ig 0 %-data analytics + 100 %
38 %
A- 1 r 0 t 0 i%ficial intelligence (e.g. machine learning, neural networks) + 100 %
30 %
I-n 10 te 0 %rnet of things and connected devices + 100 %
27 %
D- 10 ig 0 %ital platforms and apps + 100 %
22 %
C- 10 lo 0 %ud computing + 100 %
16 %
Role outlook
CFivhe-uyerarn s itnru (^) ctfiurvale lab yeouar-rfosrce churn (percent) 22 %
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
Business Development Professionals^35 %^24 %
Architects and Surveyors^19 %^19 %
Civil Engineers^17 %^17 %
Assembly and Factory Workers^25 %^17 %
Construction Laborers^24 %^26 %
Technical Specialists^32 %^24 %
Managing Directors and Chief Executives^16 %^17 %
General and Operations Managers^18 %^14 %
Accountants and Auditors^13 %^19 %
Accounting, Bookkeeping and Payroll
Clerks^14 %^29 %
Data Entry Clerks^43 %^42 %
Administrative and Executive Secretaries^36 %^35 %
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
66 % 34 %
2027 Forecast
60 % 40 %
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
31 % -^100 % +^100 % 53 %
Talent development of existing workforce
2 % -^100 % +^100 % 86 %
Talent retention of existing workforce
13 % -^100 % +^100 % 56 %
Industry Profile 1 / 2
Infrastructure



  • 50 % 0 50 %


Global Employee (millions, ILO estimates)
183. 9
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