Trend outlookGTrelnodbs 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 v 0 e%stments to facilitate the green transition of your business + 100 %
57 %
C- 10 li 0 m%ate-change induced investments into adapting operations + 100 %
51 %
B- 1 r 0 o 0 %ader application of Environmental, Social and Governance (ESG) (^) +s 1 t 0 an 0 %dards
51 %
I-n 10 c 0 %reased adoption of new and frontier technologies + 100 %
50 %
B- 1 r 0 o 0 %adening digital access + 100 %
40 %
C- 10 o 0 n%sumers becoming more vocal on environmental issues + 100 %
28 %
C- 10 o 0 n%sumers becoming more vocal on social issues + 100 %
20 %
S- 1 l 0 o 0 %wer global economic growth + 100 %
- 58 %
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 %
59 %
C- 10 li 0 m%ate-change mitigation technology (Alternative Energy, Greenhous+e 10 0 g%ases...
53 %
E- 1 n 00 c%ryption and cybersecurity + 100 %
53 %
I-n 10 te 0 %rnet of things and connected devices + 100 %
42 %
D- 10 ig 0 %ital platforms and apps + 100 %
38 %
C- 10 lo 0 %ud computing + 100 %
36 %
E- 1 d 00 u%cation and workforce development technologies + 100 %
28 %
A- 1 r 0 t 0 i%ficial intelligence (e.g. machine learning, neural networks) + 100 %
26 %
Role outlook
CFivhe-uyerarn s itnru (^) ctfiurvale lab yeouar-rfosrce churn (percent) 23 %
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
Data Analysts and Scientists^48 %^34 %
AI and Machine Learning Specialists^45 %^40 %
Project Managers^25 %^25 %
Business Development Professionals^23 %^24 %
Accountants and Auditors^9 %^19 %
General and Operations Managers^16 %^14 %
Assembly and Factory Workers^22 %^17 %
Accounting, Bookkeeping and Payroll
Clerks^26 %^29 %
Administrative and Executive Secretaries^28 %^35 %
Data Entry Clerks^36 %^42 %
Contextual indicators
INDICATORS
Labour force participation NA
Vulnerable employment 43 %
Share of youth not in employment, education, or
training (NEET) NA
Unemployment rate NA
Unemployment rate among workers with basic
eUdnue.mployment rate among workers with NA
advanced edu. NA
Secondary Education Attainment NA
Tertiary Education Attainment NA
E 1 =asCoemp oanfi (^) efis ncdaninnotg e (^) asskilyi fillendd s (^) kelilemd pemloployyeeeess, 7 i=nC loomcpanalie lsab cano euasr (^) ilym fiarnd kskeilletd employees 4. 78
F 1 =ilCl (^) ovmacanciespanies canno (^) tb filly v (^) achanirinciegs (^) bfoy hreirinigg nfo (^) relabgin labouorur, 7 =Companies can fil lvacancies by hiring foreign
labour^4.^32
C 1 =oGuovnerntrmye (^) nint dvoeess tnmot ienvnestt iinn mmdi-icdar-ecerar traieneinrg (^) ,t 7 rai=Gnovinegrnment invests ni mid-career training 5. 00
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 NA
Economy Profile 1 / 2
China
- 50 % 0 50 %
0 % 100 %Working Age Population (Millions)
1008. 8