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
C- 10 li 0 m%ate-change induced investments into adapting operations + 100 %
56 %
I-n 10 c 0 %reased adoption of new and frontier technologies + 100 %
55 %
B- 1 r 0 o 0 %ader application of Environmental, Social and Governance (ESG) (^) +s 1 t 0 an 0 %dards
54 %
C- 10 o 0 n%sumers becoming more vocal on social issues + 100 %
50 %
B- 1 r 0 o 0 %adening digital access + 100 %
48 %
C- 10 o 0 n%sumers becoming more vocal on environmental issues + 100 %
44 %
S- 1 u 00 p%ply shortages and/or rising cost of inputs for your business + 100 %



  • 40 %
    S- 1 l 0 o 0 %wer global economic growth + 100 %

  • 43 %


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 %
82 %
A- 1 r 0 t 0 i%ficial intelligence (e.g. machine learning, neural networks) + 100 %
56 %
D- 10 ig 0 %ital platforms and apps + 100 %
55 %
C- 10 lo 0 %ud computing + 100 %
48 %
E- 1 - 00 c%ommerce and digital trade + 100 %
48 %
E- 1 n 00 c%ryption and cybersecurity + 100 %
44 %
E- 1 d 00 u%cation and workforce development technologies + 100 %
43 %
I-n 10 te 0 %rnet of things and connected devices + 100 %
38 %
Role outlook
CFivhe-uyerarn s itnru (^) ctfiurvale lab yeouar-rfosrce churn (percent) 26 %
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 ECCOHNURONMY GCLHOUBRANL
AI and Machine Learning Specialists^39 %^40 %
Project Managers^19 %^25 %
Strategic Advisors^40 %^30 %
Managing Directors and Chief Executives^7 %^17 %
General and Operations Managers^12 %^14 %
Assembly and Factory Workers^17 %^17 %
Administrative and Executive Secretaries^31 %^35 %
Accountants and Auditors^32 %^19 %
Data Entry Clerks^60 %^42 %
Accounting, Bookkeeping and Payroll
Clerks^52 %^29 %
Contextual indicators
INDICATORS
Labour force participation 54 %
Vulnerable employment 27 %
Share of youth not in employment, education, or
training (NEET)^25 %
Unemployment rate 10 %
Unemployment rate among workers with basic
eUdnue.mployment rate among workers with^10 %
advanced edu.^10 %
Secondary Education Attainment 42 %
Tertiary Education Attainment 21 %
E 1 =asCoemp oanfi (^) efis ncdaninnotg e (^) asskilyi fillendd s (^) kelilemd pemloployyeeeess, 7 i=nC loomcpanalie lsab cano euasr (^) ilym fiarnd kskeilletd employees 4. 65
F 1 =ilCl (^) ovmacanciespanies canno (^) tb filly v (^) achanirinciegs (^) bfoy hreirinigg nfo (^) relabgin labouorur, 7 =Companies can fil lvacancies by hiring foreign
labour^3.^00
C 1 =oGuovnerntrmye (^) nint dvoeess tnmot ienvnestt iinn mmdi-icdar-ecerar traieneinrg (^) ,t 7 rai=Gnovinegrnment invests ni mid-career training 2. 96
W 5 +=oNrok geurarsan' (^) tReeig ofh rtigsh (^) tsI ndduee txo the breakdown of the rule of law, 1 =Sporadic violations of rights 5
L 10 e=vTheel woofr (^) stNat possioibnle alsc (^) oCreo, lomwepr llieance vels of cwomipthlian Labce, 0 =oTuher bResigt photsssible score, higher levels of
compliance^4
Economy Profile 1 / 2
7 rNi\e



  • 50 % 0 50 %


0 % 100 %

Working Age Population (Millions)
. 8
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