《WEF&領英：2025智能時代性別平等研究報告：AI驅動型經濟轉型的機遇與挑戰（英文版）（20頁）.pdf》由會員分享，可在線閱讀，更多相關《WEF&領英：2025智能時代性別平等研究報告：AI驅動型經濟轉型的機遇與挑戰（英文版）（20頁）.pdf（20頁珍藏版）》請在三個皮匠報告上搜索。

1、Gender Parity in the Intelligent AgeW H I T E P A P E RM A R C H 2 0 2 5In collaboration with LinkedInContentsCover image:Unsplash 2025 World Economic Forum.All rights reserved.No part of this publication may be reproduced or transmitted in any form or by any means,including photocopying and recordi

2、ng,or by any information storage and retrieval system.Disclaimer This document is published by the World Economic Forum as a contribution to a project,insight area or interaction.The findings,interpretations and conclusions expressed herein are a result of a collaborative process facilitated and end

3、orsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum,nor the entirety of its Members,Partners or other stakeholders.PrefaceExecutive Summary1 Introduction2 Gender Parity to fuel the Intelligent Age 2.1 AI innovation:the power of expan

4、ding talent pools2.2 Balancing the impact of AI deployment2.3 The starting point for talent:how to close the augmentation gap2.4 Fair hiring,performance evaluation and promotion3 Levelling the field:automating parity ContributorsEndnotes3456691316171819Gender Parity in the Intelligent Age2PrefaceThe

5、 advent of new technologies is often accompanied by flurries of optimism,scepticism and,in some cases,resistance.The rapid emergence of Generative Artificial Intelligence(GenAI)is no different.As history has shown,rather than the technology itself,the decision-making that designs,develops,directs an

6、d deploys it can tilt outcomes towards gender parity and in the process,towards shared prosperity.For industry leaders,the GenAI revolution is a competition for talent,and those who harness a broader,more diverse workforce will gain a decisive edge.Increasing womens participation in AI-related roles

7、 is not just a matter of fairness it is a strategic imperative.Firms that double their GenAI talent pools by integrating women more effectively will see higher rates of innovation,better problem-solving,and a competitive advantage in the marketplace.For policy-makers,GenAI presents both an opportuni

8、ty and a challenge.By proactively embedding gender parity into AI development and deployment,economies can achieve higher levels of social representation and economic integration.Economies that foster inclusive GenAI strategies early in the technological adoption period will not only reduce workforc

9、e inequalities but also drive faster,more sustainable growth.To address this urgent challenge,the World Economic Forum launched the Gender and AI Dialogue Series the first knowledge drive of the Global Gender Parity Sprint,with the intention of surfacing novel,short-burst insights on critical gender

10、 parity issues at the intersection of current global transformations.In parallel,LinkedIn and its Economic Graph Research Institute have built and maintained a research agenda exploring and understanding how AI technologies are impacting labour-market outcomes.Leaders from industry,policy and multil

11、ateral spheres continue to collaborate on identifying how GenAI can be leveraged as an accelerant,rather than a divider,for gender parity.Their insights form the foundation of this briefing paper,co-developed by the World Economic Forum and LinkedIn,as part of a longstanding data collaboration for t

12、he Global Gender Gap Report.This paper highlights key opportunities and challenges,offering industry and economic leaders clear strategies to ensure AI-driven transformation benefits reach the broadest social base possible.Gender Parity in the Intelligent AgeMARCH 2025Silja Baller World Economic For

13、umMatthew BairdLinkedIn Economic Graph Research InstituteGender Parity in the Intelligent Age3Artificial Intelligence(AI)technologies are being primed to help address a range of pressing economic challenges,from job creation,to boosting productivity,and even increasing GDP growth.Economies that harn

14、ess the broadest talent pool in this transition will be best placed to achieve a resilient,innovative,and comprehensive transition into the intelligent age.This white paper,developed with LinkedIn,examines how gender gaps are shifting in the“Intelligent Age”.It explores scenarios in innovation,workf

15、orce,and skilling where AI augmentation can support gender parity and inclusive growth.The first section finds that economies advancing in AI with limited talent diversity risk economic drag and AI-driven inequality.Healthy innovation ecosystems require a mix of talent at every stage,but talent pipe

16、lines see a stream of female talent drop-off at various points of the career cycle.The existing pool of innovators is further constrained by highly uneven innovation ecosystems,leading to the clustering of women innovators in only a handful of economies.As AI accelerates,economies capturing diverse

17、talent will gain a competitive edge.The paper then explores how GenAI is reshaping jobs and career paths differently for men and women.LinkedIn data suggests women are more likely to hold roles disrupted by GenAI and less likely to experience augmentation.Despite these differences,the AI talent land

18、scape is evolving,with more women acquiring AI-related skills in response.Womens participation in tech has grown to nearly one-third,yet retention remains a challenge.Men are overrepresented at every career stage,especially in the STEM C-suite.However,LinkedIn research suggests the dynamism of AI tr

19、ansformation offers an opportunity to break with longstanding gender disparities.LinkedIn data shows female AI talent on the platform has expanded significantly between 2018 and 2025,and the gender gap in AI talent has narrowed in 74 of 75 economies.More promisingly,underreporting could hint at a la

20、rger female AI talent pool.Finally,the paper reflects on how augmentation can impact talent development strategies.Balanced workforce pipelines depend on equitable hiring,evaluation,and promotion practices.With 99%of Fortune 500 companies using automation in hiring,AI must address existing gender bi

21、ases to ensure women benefit fully from AI-driven career opportunities.As AI reshapes economies,proactive leadership is essential to drive gender parity.Companies embedding gender considerations into AI strategies can unlock broader talent and innovation.Policies ensuring equitable AI development ca

22、n enhance workforce participation,leadership representation,and economic resilience.AI also has the potential to elevate roles vital to societal well-being,fostering inclusive growth.Executive summaryGender Parity in the Intelligent Age4IntroductionArtificial Intelligence(AI)technologies are being p

23、rimed to help address a range of pressing economic challenges:improving productivity,creating new jobs and industries,and,ultimately,increasing GDP growth.Economies that harness the broadest talent pool will be the frontrunners in the AI race and achieve the highest levels of innovation,economic exp

24、ansion and workforce resilience.For industry leaders,gender parity in AI presents a rare opportunity:integrating women into AI leadership,development,and application will double the available talent and unlock fresh perspectives in innovation.Companies that achieve gender balance in AI-intensive fie

25、lds will see improved product design,enhanced decision-making and better financial performance.For policy-makers,AI offers a lever for broader workforce participation,but only if policy frameworks prioritize inclusive upskilling and fair workforce integration.Governments and institutions must take p

26、roactive measures to ensure women are not only included in AI development but are also positioned for leadership roles within the evolving digital economy.A technology transformation in which women have an equal share of industry leadership,innovation,consumer benefits and economic rewards from tech

27、nological progress will be more powerful in achieving economic growth.To ensure that the full potential of tech transformation is not lost due to a lack of foresight,this briefing paper provides a pulse check on how gender parity can serve as a critical element to shape an AI transformation that bri

28、ngs the largest,fastest benefits to the broadest sectors of society.The Industries in the Intelligent Age report series,launched by the World Economic Forums AI Governance Alliance,offers a comprehensive collection of insights on the adoption and scaling of AI.Other Forum reports,such as the Future

29、of Jobs Report,delve into the specific implications AI is having on workforce transformation.This briefing paper provides an overview of how gender gaps are shifting in the so-called“Intelligent Age”,highlighting emerging opportunities and challenges while emphasizing the importance of gender parity

30、 in maximizing the benefits of AI augmentation.Economies drawing on the broadest talent pool will flourish in the AI race,generating growth faster and for the most people.1Gender Parity in the Intelligent Age5Gender Parity to fuel the Intelligent Age 2AI innovation:the power of expanding talent pool

31、s 2.1As the adoption of AI evolves,so does the scope of implications to businesses and economies.Economies moving towards the AI frontier with less than half the necessary talent,creativity and input are likely to face significant economic drag which will be compounded by the downstream costs result

32、ing from the social and economic AI disenfranchisement.To conceptualize the existing and persistent gender gaps at the core of a tech-driven economy,this section presents insights from an ongoing data collaboration with LinkedIn in the context of the Global Gender Gap Report series which are expande

33、d in this white paper.These insights paint an evolving picture of how gender gaps in talent are transitioning into the Intelligent Age,shedding light on new opportunities and challenges that come with the adoption of talent strategies to win the AI talent race.Innovation ecosystems that engage the f

34、ull spectrum of creative talent,from a gender parity perspective,have the potential to reduce bias,improve accessibility and expand economic opportunities for innovators and the constituents their advancements benefit.AI applications are a promising mechanism for helping to mitigate bias in hiring,p

35、ay structures,and workplace dynamics all of which will foster a more inclusive job market.Such a vision is contingent on having a healthy and heterogenous pipeline of innovators present at every stage of the technology lifecycle from ideation to development and delivery.However,in a number of econom

36、ies,we see pipelines bursting with female talent at the early stages reduced to a drip of seasoned and crowned innovators at the later stages.The environmental factors that contribute to the degradation of womens opportunities in innovation reflect,in part,the uneven conditions under which innovatio

37、n currently takes place.Only few regions have a majority share of their economies participating in the development of new AI processes,applications and technologies.Of all the economies featured in the 2024 edition of the Global Gender Gap Index,66 have applied for AI patents and 59 have received th

38、em.The Emerging Technology Observatory(ETO)(Figure 1)shows that Northern America and Europe are two distinct hubs of AI innovation in terms of the share of economies in the region participating.By that measure,the Eastern Asia and the Pacific;Middle East and Northern Africa,and Latin America and the

39、 Caribben regions demonstrate moderate participation in AI innovation,while Central Asia,Southern Asia and Sub-Saharan Africa have the lowest proportion of economies engaged in AI innovation The ETO data set also reveals that,while a lower share of economies in Eastern Asia and the Pacific are parti

40、cipating in AI innovation,they are obtaining a larger share of patents(Figure 2).As a regional block,Eastern Asia and the Pacific has granted nearly four times as many patents as Northern America and 40 times as many as Europe.Approximately 77%of granted AI patents worldwide come from the EAP region

41、,compared to only 20%from Northern America.Most of the regions activity is driven by China,a finding that reflects two significant developments for AI gender parity:(1)Chinese nationals are estimated to represent approximately over one-quarter of global AI talent,and(2)An overwhelming majority of th

42、em are absorbed by the national AI industry.1Businesses and economies chasing tech-enabled growth will be best served by casting a wide and robust talent net one that keeps female talent from“dropping off”.Gender Parity in the Intelligent Age60102030405060708090100PercentageNorthern AmericaEuropeEas

43、tern Asia and the PacificMiddle East and Northern AfricaSub-Saharan AfricaCentral AsiaSouthern AsiaLatin America and the Caribbean14%29%41%47%61%80%100%6%SourceWorld Economic Forum calculations based on the Emerging Technology Observatory Country AI Activity Metrics dataset.NoteEconomies included in

44、 the 2024 Global Gender Gap Index with AI patent submisions in the last 10 yearsShare of economies innovating on AI,by regionFIGURE 1Northern America20.3Europe2.1Eastern Asia and the Pacific77.1 Sub-Saharan Africa0.1Southern Asia0.2Latin America and the Caribbean0.3Eastern Asia and the PacificCentra

45、l AsiaMiddle East and Northern AfricaEuropeSub-Saharan AfricaSouthern AsiaNorthern AmericaLatin America and the CaribbeanSourceWorld Economic Forum calculations based on the Emerging Technology Observatory Country AI Activity Metrics data set.NoteShare of granted AI patents in a given region among a

46、ll granted AI patents.Economies included in the 2024 Global Gender Gap Index with AI patent granted in the last 10 years.Distribution of AI patents granted,by regionFIGURE 2Gender Parity in the Intelligent Age7While international data comparability for Science,Technology,Engineering and Mathematics(

47、STEM)STEM graduates poses a challenge in measuring and comparing Chinas AI talent pool to other those of other economies,it does not fully dim the relevance of these findings.In recent years,China has been estimated to be among the largest producers of STEM graduates,with an average self-reported ra

48、te of female graduates at 40%.2 Neighbouring economies in the region,whose numbers trail behind Chinas in comparison,are in turn taking measures to boost their STEM talent.In Japan,for example,the number of universities adopting female STEM quotas rose to 40 in 2024.3While the disaggregated profile

49、of AI innovators is limited,it is helpful to observe the overall presence of women in innovation.European Patent Office(EPO)data suggests that the share of women innovators has been gradually increasing over time,with distinct footprints in the United States,Japan,China and South Korea the latter ho

50、lding the highest proportion of women innovators,exceeding 25%,10 percentage points higher than in the European Union(EU)and the United States.4Resourcing of AI innovation shows other asymmetries in the global innovation ecosystem.Over the past 10 years,while disclosed investments in AI companies ha

51、ve increased,resources have clustered significantly in Northern America(Figure 3).During that same period,there were two noticeable surges in investment.The first occurred from 2019-2021,and was followed by a drop in 2022,and the second,a rebound beginning in 2023,is expected to reach 2021 figures b

52、y 2024.With resources across the global innovation ecosystem being unevenly distributed across regions,it is worth considering that other factors beyond investment can play a role in expanding talent pools to include a higher share of women in AI and to advancing AI innovations.Sub-Saharan AfricaEas

53、tern Asia and the PacificCentral AsiaMiddle East and Northern AfricaEuropeSouthern AsiaNorthern AmericaLatin America and the Caribbean010,00020,00030,00040,00050,00060,00070,00080,00090,000100,000110,000120,000130,000140,00020142015201620172018201920202021202220232024SourceWorld Economic Forum calcu

54、lations based on the Emerging Technology Observatory Country AI Activity Metrics dataset.Aggregate investment in AI companies,2014-2024,by regionFIGURE 3Amount of investment in million USDGender Parity in the Intelligent Age8Balancing the impact of AI deployment2.2As successive editions of the Globa

55、l Gender Gap Index have shown,gender parity in the workforce is a driver for growth and resilience.However,to date we are seeing AI deployment drive greater disparity.This section lays out emerging patterns in terms of workforce impact and underlying bottlenecks.It further presents levers to ensure

56、more women are benefitting from AI-driven augmentation;these include skilling,fair hiring,performance evaluation and promotion.The deployment of GenAI technologies has shifted the goal post for the future of work.As machine learning models have moved beyond research labs and into everyday interactio

57、ns notably,with the launch of ChatGPT in 2022 a surge of custom applications and innovations was enabled with real-life implications on work.The types of tasks,roles and industry demands that men and women respond to are changing,and with it the future of workforce representation,leadership opportun

58、ities and career progression.The impact of GenAI technologies on jobs is increasingly conceptualized in terms of three processes augmentation,disruption and insulation which have since been adopted as categories describing the future of work(Table 1).Of the three processes described in the table abo

59、ve,augmentation carries an expectation for workers to engage proactively with the tech-driven workforce transformation and to be well-rewarded for it,compared to the other two categories.When considering the gender composition by GenAI segment,the data shows that augmentation would create scenarios

60、where the shares of women or men working with AI would vary depending on their occupation(Figure 4).LinkedIn research suggests that women tend to work in occupations with less potential to be augmented by GenAI compared to men.Data from their United States membership suggests that more women than me

61、n will be in jobs disrupted by GenAI(57%vs 43%),whereas less women than men will see their work augmented(46%vs 54%)by GenAI.Only four percentage points separate the share of women whose roles would be insulated(48%),compared to men(52%).AugmentationThese jobs core skills include a large share of bo

62、th GenAI-replicable and GenAI-complementary skills.GenAI may positively affect a relatively large portion of the skills in these jobs,leaving more time for higher value-added complementary skills.DisruptionThese jobs core skills include a large share of GenAI-replicable and a relatively low share of

63、 generative complementary skills.The skills are likely to become obsolete with broader adoption of GenAI.InsulationThese jobs have a relatively small proportion of GenAI-replicable skills among their core skills,which are likely to remain unchanged in the near term.SourceAdapted from Karin Kimbrough

64、s and Mar Carpanellis 2023 paper“Preparing the Workforce for Generative AI Insights and Implications”published by LinkedIn Economic Graph Research Institute,2023.GenAI processes:impact on jobs and skills usedTABLE 1Gender Parity in the Intelligent Age9LinkedIn data from 2025 suggests that most women

65、 without AI engineering skills are working in roles that are being disrupted(38.4%),while among men without AI engineering skills,this constitutes the smallest group(31.1%).Relatively fewer women are insulated from the effects of AI and just over 28%are in roles that are being augmented(Figures 5a a

66、nd 5b).In comparison,workers with AI engineering skills are less likely to be in roles impacted by disruption or which are fully isolated.Among men with AI engineering skills,the vast majority(65.4%)are in augmented roles,compared to women with engineering skills where the proportion is 57.2%.About

67、one quarter of women who have engineering skills are currently in disrupted roles yet should have a relatively easier path transitioning to augmented roles compared to the 38.4%of women without AI engineering skills in disrupted roles.Given this skill and AI impact mix,a relatively higher number of

68、women will need to transition from disrupted roles and relatively fewer currently have the skills to do so.Businesses and economies chasing GenAI-related growth will be best served by casting a wide,and robust talent net one that nurtures female talent and develops its potential,from entry-level and

69、 all the way into leadership.The workforce however is unlikely to upskill and reach for emerging GenAI-related opportunities without a compelling vision for the future of work.As GenAI is increasingly integrated into workplaces,workers attitudes reveal that gender gaps shape workers appetites to eng

70、age with this shift at scale.PwC data featured in the Global Gender Gap Report 2024 highlighted that only 54%of women,compared to 61%of men,expected significant changes in the skills required for their jobs over the next five years.Women also reported a less clear understanding of how these shifts w

71、ill affect their roles(62%of women versus 68%of men),signalling a potential gap in preparedness for the AI-driven economy or the fact that women are disproportionately filling roles which have little exposure to AI.This finding echoes other insights from studies that suggest women are somewhat less

72、likely to use AI than men.5However,the rapid pace of the shift means attitudes are also changing fast.Insights from LinkedIns Workforce Confidence Index reveal that,between 2023 and 2024,mens and womens attitudes towards GenAI evolved rapidly(Figure 6).A higher share of both men and women reported t

73、hat the role of GenAI had increased in their workplaces in 2024,compared to 2023.While men were more likely than women to report that GenAI skills would help their career progression and reported a higher use of GenAI than women,the proportion of both men and women recognizing the importance of AI s

74、kills and reporting AI use at work have increased between 2023 and 2024.Where beliefs diverged over time were in the perceived importance of soft skills and whether they doubted that GenAI would 0102030405060Augmented by GenAIDisrupted by GenAIInsulated from GenAIMenWomenSourceLinkedIn Economic Grap

75、h Research Institute,2023.Gender composition by GenAI processFIGURE 4Share of LinkedIn members in the US(%)Gender Parity in the Intelligent Age10affect their work.For these two questions,an increasing share of women showed assurance that GenAI would impact their job,while also growing the importance

76、 of soft skills.While a limited display of initiative from the workforce to engage with GenAI is to be expected,it will not fuel the seamless integration of new technologies.Many aspects of work will be impacted by GenAI over the coming years,and it is contingent on leaders to lay the path forward.W

77、hile GenAI may not be a part of every professional future,for workers wanting to participate in the AI economy,tools and transitions need to be identified in a timely matter.Creating a broad understanding of what this change entails will enable workers to find their footing more quickly.010203040Sha

78、re(%)Share(%)020406080(b)Workers with AI Engineering Skills(a)Workers without AI Engineering SkillsAugmented by GenAIDisrupted by GenAIInsulated from GenAIAugmented by GenAIDisrupted by GenAIInsulated from GenAIAI impact on workers,men vs women,based on skill profile,2025FIGURE 5SourceLinkedIn Econo

79、mic Graph Research Institute,2025.MenWomenGender Parity in the Intelligent Age112023020406080202420232024202320242023202420232024Share of respondents agreed witha given statement(%)020406080Share of respondents agreed witha given statement(%)MenWomenSourceLinkedIn Economic Graph Research Institute N

80、oteUnweighted averages from 12 economies covered in the Workforce Confidence Index.Gender gaps in Linkedins Workforce Confidence Index,2023-2024FIGURE 6Gaining AI skills will help me progressin my careerThe role of AI in my workplace hasincreased in the past yearWith the growing popularity of AI,sof

81、t skillsare more important than everI am currently using AI for my job I doubt AI will have much impact on my jobGender Parity in the Intelligent Age12The starting point for talent:how to close the augmentation gap2.3While womens presence in tech fields has grown in the past few decades,rising from

82、26.1%in 2016 to 28.2%in 2024,they still represent less than one-third of the STEM workforce(Figure 7).As highlighted in the 18th edition of the Global Gender Gap Report,women are underrepresented in STEM roles across industries,particularly in Information and Communication Technologies(ICT)ICT and p

83、rofessional services,where men are twice as likely as women to hold STEM roles.02016201720182019202020212022202320243010204050Share of women(%)Share of women in non-STEM workforce(%)Share of women in STEM workforce(%)Womens workforce representation in STEM vs non-STEM workforce,2016-2024FIGURE 7Sour

84、ceLinkedIn Economic Graph Research Institute25201345303540Share(%)Years since graduation20212020201920182017Share of women STEM graduates by years since graduationFIGURE 8SourceLinkedIn Economic Graph Research Institute for the Global Gender Gap Report 2023NoteYear 0 refers to the year when women gr

85、aduated from the STEM education.Gender Parity in the Intelligent Age13To address this initial gap,strategies seeking to transition more female STEM graduates into STEM roles and industries have been a staple of tech-focused economies.A trend documented in the 2023 edition of the Global Gender Gap Re

86、port showed that a larger cohort of female STEM graduates entered STEM employment every year.However,their retention is not as promising.As Figure 8 indicates,the first year in the workforce carries a significant“drop off”for women in STEM employment:women graduating in 2017 accounted for 35.5%of ST

87、EM graduates,but only 29.6%of STEM job entrants in 2018.The“school-to-work”transition is but one of the many stages in the professional life of STEM workers where gender gaps are a glaring obstacle to talent strategies.The rise to industry leadership is another.Presented as the“drop to the top”,this

88、 metric shows how women transition into STEM leadership roles in lower proportions than men(Figure 9).In 2024,women held 24.4%of STEM managerial positions in STEM but only 12.2%of STEM C-suite level roles.This contrasts with womens representation in non-STEM roles,which in 2024 declined from 39.6%at

89、 the managerial level to 24.3%in executive leadership.From the start,and throughout the entire career cycle,the STEM industrys ability to attract and retain female talent is feeble:men are overrepresented at every stage of the professional ladder.The gender disparity in STEM has persisted for decade

90、s,with incremental change taking a long time to reflect on opportunities.While AI remains part of the broader STEM ecosystem textured by many of its structural obstacles it is not yet fully rigid in its gender dynamics.AI is a much younger and more dynamic field,creating a window for intervention th

91、at can foster greater gender equity before biases become fully institutionalized.One example of this is the rapid uptake of AI skilling.With technology adoption expected to play a growing role in economic transformation,AI and big data skills are increasingly attracting employer attention.In 2022,fe

92、wer than one-third of employers surveyed in the Future of Jobs Survey believed these skills were essential for their organizations.By 2024,this share had risen to 45%.6 What the survey also revealed is that over three-quarters of business executives view AI reskilling and upskilling as the primary s

93、trategy for adapting to its growing impact,making it the most widely adopted approach across industries.This aligns with findings from the Forums 2024 Executive Opinion Survey,which suggested that business leaders see accelerating education and talent development as key objectives for driving innova

94、tion and shaping industry policy.Rising to meet this demand is a growing cohort of AI talent workers with AI engineering and literacy skills across industries and occupations.7 For both,we observe rapid adoption of AI skills and a persistent gender disparity that is,nonetheless,narrowing.Data on AI

95、engineering(Figures 10a and 10b)indicates that the share of LinkedIn members who list AI engineering skills in 75 economies has rapidly expanded from 2018-2025.The median change across economies over the last year was 0ManagerEntrySeniorDirectorVPCXO204060Share of women(%)non-STEMSTEMDrop to the top

96、 in STEM vs non-STEMFIGURE 9SourceLinkedIn Economic Graph Research InstituteNote“Drop to the top”refers to the widening of the gender gap as workers progress into leadership roles.Gender Parity in the Intelligent Age14an increase of 51.5%.However,across the same period men have a higher share than w

97、omen of members listing AI engineering skills:from 0.1%of women and 0.3%of men in 2018,to 1.1%of women and 2.0%of men in 2025.This is true in 95.7%of country/months in the data,and 91.9%of economies currently.However,that gap is narrowing(Figure 10b).In 2018 globally,23.5%of AI engineering skill-lis

98、ters were women.This has increased over time,such that in 2025 29.4%of AI engineering skill-listers are women.Over the past five years,this gender gap has narrowed in 74 of the 75 economies examined.2018201920202021202220232024202500.511.522.5201820192020202120222023202420250102030Share(%)Share of w

99、omen(%)MenWomen(b)Share of AI engineering skills listers who are women(a)Share of LinkedIn members with AI engineering skills listed,by genderGender gaps in AI talent,2018-2025FIGURE 10SourceLinkedIn Economic Graph Research InstituteNoteAverage taken across all members in 75 economies in which there

100、 is sufficient data quality.Gender Parity in the Intelligent Age15Although women represent less than one-third of AI talent on the platform,there is reason to believe that not all the observed skills gap between men and women reflect true disparities in skills held,but that some part of it reflects

101、differences in how men and women list skills on the LinkedIn platform.This may be true for a few reasons.First,over half of men and women who have an AI literacy skill(63.4%of men and 53.8%of women)also have at least one AI engineering skill listed,compared to only 2.9%and 1.6%of men and women with

102、no AI literacy skill listed.Put another way,men with AI literacy skills listed are over 20 times as likely as men with no AI literacy skills to have AI engineering skills.For women,that increases to 33.6 times more likely.Almost 90%of men who have an AI literacy skill list have at least one disrupti

103、ve tech or AI engineering skill,as do 79.2%of women.Thus,these early adopters of AI literacy skills are likely highly technical and in these disruptive tech skill areas.However,that is truer for men than it is for women.8Second,AI engineering skills may reflect differences in propensities to list sk

104、ills on LinkedIn,as the share of female AI engineering talent increases by 9 percentage points,from 29.8%to 37.7%,when accounting for implicit skills deduced from their profiles but not listed directly by themselves.A gender bias in self-reporting,however,should not foster complacency with gender ga

105、ps in AI skilling and re-skilling.Research from Randstad suggests that employers seem to be prioritizing AI upskilling training among male employees across all economies surveyed in the study,apart from Belgium and India.9 Moreover,with skilling being centred as the uncontested strategy for navigati

106、ng workforce transformation,as noted earlier in this paper,there is a risk of overlooking other areas where AI can add value and close gender gaps,including pay,career advancement,and occupational and industrial gender segregation.Skilling women for AI roles will not eliminate the persistent dispari

107、ties in both leadership representation and career progression.AI has the potential to help revalue work by automating labour-intensive tasks in clerical and administrative roles,areas that are traditionally feminized and underpaid.By integrating AI into these functions,pathways can be created to re-

108、evaluate work in areas such as communication,decision-making and relational tasks lower-value roles that are also predominantly performed by women.Furthermore,AI integration in areas as mundane as the synchronization of administrative workflows and routine functions can provide organizations with th

109、e opportunity to implement broader shifts in business models,organizational structures and AI-driven decision-making.Fair hiring,performance evaluation and promotion2.4Transparent and fair processes for hiring,performance evaluation and promotion will be a critical element in building more balanced

110、workforce and leadership pipelines for women to reap the full benefits from AI augmentation.Today,99%of Fortune 500 companies use some form of automation in their hiring processes.10 As these processes become widespread,it will be critical to document the extent to which AI agents can overcome and o

111、verturn gender gaps in existing training data.Gender gaps reflected in training data are concerning to the extent that they inform AI-driven recruitment systems that favour the competencies,performance markers and trajectories of male candidates.The true challenge for AI in the workforce is not just

112、 mitigating bias but actively expanding the talent pool by identifying and including individuals who are often overlooked.Hiring and performance evaluations are among the most powerful levers for advancing womens careers.Before AI,organizations relied on gender-blind hiring policies and standardized

113、 interviews to promote diversity,yet systemic bias persisted beyond recruitment.11 Performance evaluations also frequently reflect subjective gendered assessments of potential.12 AI could transform this process by implementing better-tuned assessments,creating new pathways for underrepresented talen

114、t to be recognized and advanced in the workforce.Fair,AI-driven recruitment and evaluation processes can be a game-changer for gender parity,enabling women to be assessed more accurately and ensuring equitable access to leadership opportunities.In turn,employers can expand their workforces potential

115、,make better talent decisions and provide personalized development opportunities.Gender Parity in the Intelligent Age16Levelling the field:automating parity 3As technology becomes central to business transformation and economic productivity,there are immediate areas where leaders can take action to

116、capitalize on the full spectrum of AI talent,AI leadership,AI industry potential and AI innovation available today.AI-driven economic growth will be strongest where gender parity is embedded in its design a virtuous circle where:Industry and policy goals are aligned to address gender disparities ske

117、wing the tech transition from design to development to adoption.Parity in skilling and reskilling brings equal access to opportunities and rewards in the future of work,in both AI and non-AI roles.Industry practices and mindsets remove biases in workforce representation and leadership that limit pro

118、ductivity and innovation.Increased female participation in the tech transition leads to improved innovation outcomes,with applications better tailored to changing populations and with more efficient uptakes.Parity in resourcing nurtures the innovation ecosystem.Increased representation in the data t

119、ranslates to better learning models with more discerning outcomes.For industry leaders,the case is clear:companies that fail to integrate gender parity into AI strategy will miss out on half of the available talent,reducing their capacity for innovation and long-term competitiveness.For policy-maker

120、s,AI can be adopted as a driver of workforce transformation,economic dynamism and social integration,ensuring that AI-driven economies are not only moving forward,but doing so by growing the proverbial pie.AI is more than a tool it is a vehicle for economic and social transformation.Decisive,discern

121、ing leaders who recognize this and act now will shape the future of AI-driven growth,ensuring that its benefits extend to all.Technological disruptions call for re-design:tech can boost growth and close gender gaps in participation,leadership,ownership and innovation.Gender Parity in the Intelligent

122、 Age17ContributorsWorld Economic ForumSilja Baller Mission Head,Diversity,Equity,and Inclusion Yanjun Guo Insights Specialist,Diversity,Equity,and InclusionKim Piaget Insights Lead,Diversity,Equity,and InclusionLinkedInMatthew Baird Senior Staff Economist,LinkedIn Economic Graph Research InstituteSi

123、lvia Lara Senior Data Scientist,LinkedIn Economic Graph Research InstituteKristin Keveloh Senior Lead Manager Public Policy,LinkedInSarah Steinberg Head of Global Public Policy Partnerships,LinkedInProductionPietro Guinea Montalvo Designer,Accurat StudioBeatrice Lattuada Designer,Accurat StudioAless

124、andra Facchin Designer,Accurat StudioEditingMike Fisher We are grateful to our colleagues who provided invaluable insights and support over the course of this project.At the World Economic Forum:Attilio Di Battista,Maria Basso and Eoin Cathasaigh.Special thanks to participants of the Global Gender P

125、arity Sprint Dialogue Series on Gender and AI who provided insightful reflections and relevant questions for this discussion.Gender Parity in the Intelligent Age18Endnotes1.Yang,Zeyi,“Four things you need to know about Chinas AI talent pool”,MIT Technology Review,27 March 24,https:/ Chinese Academy

126、of Education Sciences reported that 40.6%of graduates in science and technology were female in 2018-2019.3.Takahama,Yukihito,Hajime Ueno and Yukiko Kitamura,“Survey:40%of universities to have quota for female students”,The Asahi Shimbun,14 June 2024,https:/ Patent Office,“Statistics and indicators,W

127、omen inventors”,2023,https:/www.epo.org/en/about-us/statistics/patent-index-2023/statistics-and-indicators/applicants/women-inventors.5.LinkedIn Economic Graph,Future of Work Report:November 2023,2023,LinkedIn Future of Work Report https:/ Economic Forum.Future of Jobs Report 2023 and 2025.7.Example

128、s of AI engineering skills include machine learning,artificial intelligence and large language models.Examples of AI literacy skills include ChatGPT,prompt engineering and Microsoft Copilot.8.Linkedin9.Randstad,AI skills gap widens:71%of AI talent are men,while only 22%of baby boomers receive traini

129、ng-reveals randstad data.,12 November 2024,https:/ Is Replacing Humans In The Interview Process-What You Need To Know To Crush Your Next Video Interview”,Forbes,30 September 2023,https:/ K.,David R.Hekman and Elsa Chan,“If Theres Only One Woman in Your Candidate Pool,Theres Statistically No Chance S

130、hell Be Hired”,Harvard Business Review,2016,https:/ are less likely than men to be promoted.Heres one reason why”,Ideas to Matter blog,12 April 2022,MIT Sloan School of Management,https:/mitsloan.mit.edu/ideas-made-to-matter/women-are-less-likely-men-to-be-promoted-heres-one-reason-why.Gender Parity

131、 in the Intelligent Age19World Economic Forum9193 route de la CapiteCH-1223 Cologny/GenevaSwitzerland Tel.:+41(0)22 869 1212Fax:+41(0)22 786 2744contactweforum.orgwww.weforum.orgThe World Economic Forum,committed to improving the state of the world,is the International Organization for Public-Private Cooperation.The Forum engages the foremost political,business and other leaders of society to shape global,regional and industry agendas.