This chapter starts with an overview of key gender equality considerations relating to the green transition (e.g. the impacts of climate change and environmental degradation) and the digital transformation (e.g. the impacts of digital tools and technologies, automation and artificial intelligence). Topics covered include employment, health and well-being, and representation in leadership and innovation. The chapter closes with policy options that are integral to improving gender equality in the context of the green transition and the digital transformation.
Gender Equality in a Changing World
Taking Stock and Moving Forward
Abstract
Green transition
Occupational and industrial segregation means that job losses linked to the green transition are expected to be more pronounced for men than for women, while women are less likely to benefit from growing job opportunities in expanding sectors. The net gendered impact is unclear ex ante and requires close monitoring through gender-disaggregated data.
Women are more likely than men to make more sustainable consumption choices, which may reflect gender differences in concern for the environment, in preferences and in available (financial) resources. Such gender gaps are found to emerge early in life.
Environmental degradation, natural disasters and climate change can lead to increased morbidity and mortality for both women and men. Current estimates suggest that men are more likely to die from air pollution, while women are more likely to die from natural disasters.
Women are underrepresented in leadership relating to the green transition, including in government ministerial positions related to environment and in management positions in environmentally sensitive sectors.
Digital transformation
Occupational and industrial segregation mean the digital transformation will have gendered impacts, with women and men experiencing different degrees of change at work and in the labour market and having different capacities to deal with such change. There is little consensus yet on the net gendered effects.
Digital technologies in the workplace that facilitate flexible working arrangements and telework are expected to have gendered impacts, but the direction of impact is unclear ex ante. Flexible working arrangements and telework may entrench existing patterns of unpaid care and household responsibilities, but may also support greater take‑up among men.
Women are underrepresented in research and innovation at the digital frontier.
While opportunities and risks exist for women and girls in digital environments, an important risk relates to technology-facilitated gender-based violence. Although data are still limited, existing data show that women and girls are at greater risk than men and boys. In a recent survey in the EU, 27% of respondents agree that when a woman shares her opinion on social media, she should accept that it may elicit sexist, demeaning and/or abusive replies.
Promoting gender equality through policy combinations
Promoting gender equality in the green transition and the digital transformation requires policy options that span across government and across all stages of people’s lives. Key policy measures relate to tackling gender stereotypes and norms from an early age. Re‑training and re‑skilling are needed to address changing skill needs, including for women who exited the labour market for caregiving. Embedding gender considerations into infrastructure and emergency planning could further enhance women’s safety, particularly by reducing the risk of gender-based violence when using public transportation and during crises, including climate‑related disasters. Continually improving the availability and accessibility of gender-disaggregated data relating to the green transition and the digital transformation is equally necessary for evidence‑based policy making as conditions and contexts continue to evolve.
Both women and men will experience the effects of the green transition and the digital transformation in their work, health, and well-being, but the extent of positive and negative impacts is likely to vary by gender. Such differences stem from a range of factors, including unequal access to resources, gendered representation in leadership and research and development, physiological factors, discrimination, consumption and employment patterns and socio‑economic characteristics. Many of these factors relate back to gender norms and stereotypes.
This chapter proceeds as follows. Section 9.1 and Section 9.2 explore key indicators relating to the gendered nature of the green transition and the digital transformation, respectively, putting forward likely explanations for observed outcomes. Section 9.3 explores policy options and combinations to advance gender equality in the green transition and digital transformation.
Green transition
Climate change and environmental degradation are a major threat to economic growth and well-being. To mitigate its consequences requires collective action – including from consumers, producers and policy makers – to shift toward more sustainable and environmentally friendly behaviours (Causa, Nguyen and Soldani, 2024[1]). This shift is generally referred to as the green transition and it may have both positive and negative impacts for individuals, households, communities, economies and societies.
Digital transformation
OECD (2019[2]) defines digitisation as the conversion of analogue data and processes into a machine‑readable format. Digitalisation is the use of digital technologies and data as well as interconnection that results in new or changes to existing activities. Digital transformation refers to the economic and societal effects of digitisation and digitalisation.
This section explores gender gaps in key indicators relating to the green transition using a life course approach. The section starts with results on childhood and youth, deriving principally from Borgonovi et al. (2022[3]), before exploring results relating to adulthood, including on the labour market, health, leadership and innovation.
9.1.1. Childhood and youth: Gender gaps in environmental competence, preferences, awareness and behaviours emerge early
Gender differences in concern for the environment emerge early, with girls aged 15 years more likely than boys to report that they care about the environment throughout both EU and OECD countries (Borgonovi et al., 2022[3]). Girls are also slightly more likely to demonstrate foundational levels in environmental sustainability competence (see Online Annex Figure 9‑A1) (OECD, 2023[4]; Borgonovi et al., 2022[3]), which is defined as having basic science proficiency (i.e. Level 2 in the PISA science test), environmental awareness and concern, confidence in explaining environmental issues, and pro‑environmental behaviour. By comparison, there is a near-zero gender gap in advanced environmental sustainability competence, which is defined similarly to foundational sustainability competence, except that students must achieve at least Level 4 in the PISA science test (OECD, 2023[4]). This suggests that the closure of the gender gap when moving from foundational to advanced sustainability competence is driven by the fact that girls have lower levels of achievement in the PISA science test, especially at the top of the distribution (OECD, 2023[4]; Borgonovi et al., 2022[3]), in part due to gender stereotypes and norms (see Chapter 4).
Girls and boys also have differing levels of awareness of environmental problems depending on the nature of such problems (Borgonovi et al., 2022[3]). Boys report higher levels of awareness of environmental issues related to nuclear waste, greenhouse gases, genetically modified organisms and deforestation. By contrast, girls have greater awareness of environmental issues related to water shortages, air pollution and plant and animal extinction. This awareness aligns with academic performance: boys score higher in physical and earth science areas, while girls perform better in biology (Borgonovi et al., 2022[3]). It also maps into fields of study in tertiary education, with women better represented in biology than physics and engineering (McNally, 2020[5]).
In most EU and OECD countries, 15‑year‑old girls report engaging in individual forms of pro‑environmental behaviours (such as energy saving at home) more than similarly aged boys (Borgonovi et al., 2022[3]). At the same time, girls are less optimistic about potential improvements in the state of the environment over the next 20 years across all issues, with the largest gender gaps around air pollution and nuclear waste (Borgonovi et al., 2022[3]).
Gender gaps in environmental competence, preferences, awareness, and behaviours may evolve due to shifting social, economic, environmental and policy contexts. To track progress and inform action, governments must (continue to) regularly collect and monitor gender-disaggregated data.
9.1.2. Adulthood: Gender gaps on the green transition exist in the labour market, health, leadership and innovation
This section explores gender gaps in key indicators relating to the green transition in adulthood, including gender differences in potential job losses and health impacts and the underrepresentation of women in leadership and innovation.
Men are more likely than women to lose their jobs as a result of the green transition
To meet international climate targets, and in response to demand, many labour markets will undergo a significant transition to greener, more sustainable jobs. This is expected to shift jobs within existing industries and establish entirely new sectors (OECD, 2023[6]). These shifts are expected to have gendered impacts for two reasons.
Women are underrepresented in “green” jobs: Increased spending on the green transition will create more “green” jobs. Although defining these jobs is difficult (OECD, 2023[7]; 2024[8]), women are underrepresented across different definitions. In 2021, for example, women accounted for only 28% of green-task jobs (OECD, 2023[7]), defined as occupations where at least 10% of the tasks directly support sustainable development. According to another definition, on average between 2015 and 2019, only 12% of women were in green-driven occupations, compared to 29% of men, where green-driven occupations are defined as new jobs that emerge due to the green transition, jobs whose demanded skills and tasks will be changing because of the transition and jobs producing goods and services that are key inputs for lower-emission activities (OECD, 2024[8]).
Men are overrepresented in “polluting” industries and occupations: “Polluting” jobs are at the greatest risk of disappearing due to the green transition. Although different definitions of “polluting” jobs exist, all definitions point to a large overrepresentation of men. For instance, when “polluting” jobs are defined as those in the upper two deciles of the average greenhouse gases (GHG) intensity distribution in at least 10 out of 32 countries, men account for 81% of employment (OECD, 2024[8]). When defined as those jobs in industries in the top 95th percentile of emissions of at least 3 out of 8 contaminants, men account for 83% of jobs (OECD, 2023[7]).
Gender differences in the employment impacts of the green transition are largely driven by occupational and industrial segregation (i.e. women and men tend to work in different jobs) (see Chapter 5) (OECD, 2023[7]), with men over-represented in carbon-intensive extractive industries, like mining, oil and gas.
This occupational and industrial segregation is rooted in gender stereotypes and norms (see Chapter 4 and Chapter 5). Because low-paid men may be more likely to lose their jobs, the green transition may also slow down the closure of the gender wage gap, but the effect is likely to be minimal given the relative size of GHG-intensive employment (OECD, 2024[8]).
To ensure that both women and men benefit from the growing opportunities in the best-paying, expanding sectors, governments must work toward combatting gender segregation by field of study and occupation and industry and ensure that both women and men have access to re‑training and re‑skilling opportunities linked to the green transition (OECD, 2024[8]; Frey, Thomas and Alajääskö, 2024[9]; OECD, 2021[10]).
At a local level, the transition to green jobs and green sectors may directly impact men’s jobs since polluting industries and occupations are typically dominated by men (OECD, 2024[8]). The displacement of men’s employment may, however, indirectly impact women’s employment (OECD, 2022[11]). In the United Kingdom, for example, the closure of coal mines in the 1980s heavily impacted men at the outset. But, over time, women working in the manufacturing sector in regions near coal mines were crowded out as men took on jobs previously performed by women (Aragón, Rud and Toews, 2018[12]).
Women are more responsive than men to environmental concerns
Across countries, climate change is a salient issue, but women are more likely to be concerned than men (Wellcome, 2020[13]; OECD, 2023[4]; Asai, Borgonovi and Wildi, 2022[14]; Ballew et al., 2018[15]). In the 2024 OECD Risks that Matter (RTM) Survey, for example, 73% of women report being somewhat or very concerned about climate change in the next year or two, compared to 63% of men (Figure 9.1), with statistically significant gaps in 22 out of 27 participating OECD countries. Similar findings emerge in the OECD Survey on Environmental Policy and Individual Behaviour Change (EPIC) (OECD, 2023[16]; forthcoming[17]).
Women also have different policy preferences regarding government action around climate change, with 51% of women respondents to the 2024 RTM Survey believing the government is not doing enough to tackle climate change – bearing in mind the costs and benefits of policy action – compared to 43% of men (see Online Annex Figure 9‑A2).
Share (%) of women and men somewhat or very concerned about climate change in the next year or two, 2024
Note: EU‑17 and OECD‑27 averages are unweighted. ↗ indicates that the data is sorted according to this series in ascending order. * indicates that the difference between women and men is statistically significant at the 10% level. Respondents were asked “Thinking about the next year or two, how concerned are you about climate change?” Response options were “Not at all concerned,” “Not so concerned,” “Somewhat concerned,” “Very concerned,” and “Can’t choose.” “Concerned” in this figure includes “Somewhat concerned” and “Very concerned.” Data for this figure can be downloaded via Annex 9.A.
Source: OECD Secretariat calculations using OECD 2024 Risks that Matter Survey microdata (https://oe.cd/rtm).
Research additionally finds that women are more likely to (or be willing to) engage in environmentally sustainable behaviour than men. In a 2023 cross-national survey in EU‑27 countries, for example, women are more likely than men to report cutting down on consumption of disposable items, reducing waste and regularly separating recycling, buying and eating more organic food and buying and eating less meat (see Online Annex Figure 9‑A3) (European Commission, 2023[18]). Preliminary results from an OECD survey on consumer attitudes toward sustainable consumption also show that women (62%) are more likely than men (58%) to report that they would be willing to make sacrifices to protect the environment. Women (21%) were likewise more likely than men (16%) to report that their last purchase of a large household appliance, electronic device, furniture piece or apparel item in the past 12 months was second hand. Even when purchasing such products new, women were slightly more likely than men to consider the product’s environmental impact as at least “important” (52% vs. 50%) and less likely to consider this impact “not important at all” (18% vs. 22%) (OECD, forthcoming[19]).
Beyond consumer purchases, women also tend to use modes of transportation that result in lower emissions, such as public transport and walking, while men are more likely to drive a car (see Online Annex Figure 9‑A4) (European Union, 2020[20]). But safety remains a critical issue in public transport and spaces, with many women feeling unsafe using public transportation and walking home alone at night (see Chapter 8) (OECD, 2023[6]; 2019[21]; ITF, 2018[22]).
Higher concern about climate change and the environment, higher levels of environmental action and stronger preferences for government action among women relative to men stem from several factors. One such factor may be that sustainable consumption and pro‑environmental behaviour is associated with femininity (Brough et al., 2016[23]; Zhao et al., 2021[24]) Another factor may be that, as a result of their experiences with injustice, women are more likely than men to reject hierarchical values in favour of egalitarian values and are more likely to be “concerned about social justice, unity with nature, and social and environmental accountability, while men are more likely than women to ascribe importance to self-enhancement values” (e.g. power, achievement, hedonism, success, capability and ambition) (Bloodhart and Swim, 2020[25]). Gender differences in behaviour may also partly reflect differences in access to resources and lower levels of income among women, particularly around issues such as car ownership and second-hand purchasing.
Structural inequalities in socio-economic status and unpaid care and household responsibilities mean that women – especially single mothers, older women, and those in low-income households – are disproportionately energy poor and less able to invest in improving the energy efficiency of their homes. Applying a gender lens to climate policies, especially income‑regressive policies such as carbon pricing, in therefore key to avoid inadvertently burdening lower-income individuals and households, where women are overrepresented. Without targeted mitigation strategies – such as energy subsidies, investment in energy-efficient social housing, or direct rebates – the introduction of income‑regressive policies could exacerbate energy poverty among certain groups of vulnerable women.
Source: European Parliament (2023[26]; 2017[27]), Azimi et al. (2023[28]), Murauskaite‑Bull et al. (2024[29]), Linden, O’Donoghue and Sologon (2024[30]), EIGE (2023[31]) and Pradhan Shrestha et al. (2025[32]).
Gender gaps in harms related to the green transition
Poor environmental stewardship may affect both women’s and men’s health, but impacts are not identical across genders (Zavala et al., 2024[33]). Using available internationally-comparable data, this section provides an overview of gender gaps in mortality as a result of air pollution, natural disasters and heat waves.
Mortality alone is a very narrow scope for this section, but gender-disaggregated data on the health impacts of climate change, natural disasters and environmental degradation are scarce. Going forward, to better understand the gendered health impacts of climate change, natural disasters and environmental degradation beyond mortality, governments must invest in effective monitoring and in the production of gender-disaggregated data. Indeed, although there is a growing recognition of the intersection between gender and health more broadly (see Chapter 7) and in the context of the green transition, there is currently limited explicit acknowledgment of the relationship between gender, climate change and health in the national policies and action plans of OECD countries.
Air pollution is more likely to kill men than women
Air pollution – tiny particulate matter small enough to be inhaled into the deepest part of the lung – harms human health by causing or worsening existing respiratory, cardiovascular and other diseases, and in the worst of cases, air pollution may lower life expectancy by contributing to early mortality. From a gender perspective, women and men may face different risks of mortality and morbidity from air pollution (OECD, 2020[34]). In 2021, for example, air pollution was associated with slightly higher mortality rates among men than among women (see Online Annex Figure 9‑A5) (IHME, 2021[35]). These higher levels of mortality among men may derive from gender differences in exposure to air pollution due to occupational and industrial segregation (see Chapter 5), different daily movements between home, work and other locations, as well as gender differences in vulnerability to air pollution due to underlying health issues (see Chapter 7) (OECD, 2020[34]).
Within countries, low-income and marginalised populations are more likely to be exposed to air pollution, reflecting occupational, industrial and residential segregation. Lower-paying jobs, for example, are more likely to require outdoor physical labour, increasing exposure to air pollution, and low-income neighbourhoods are more likely to host industrial plants and busy highways and roads, important sources of pollution (Rentschler and Leonova, 2022[36]; Jbaily et al., 2022[37]). Although much research exists on the link between marginalisation and exposure to air pollution, it rarely focuses on intersectionalities, such as gender and race and gender and income (Michelson, 2022[38]).
Women are more likely than men to die from natural disasters
Often coming without warning, natural disasters have the potential to significantly disrupt lives and livelihoods. Although natural disasters do not discriminate, women have slightly higher mortality rates attributable to exposure to forces of nature – i.e. earthquakes, volcanic eruptions, avalanches, storms, lightning strikes and floods (IHME, 2021[35]). Greater mortality among women as a result of natural disasters may reflect pre‑existing socio‑economic gaps between women and men, with women tending to experience higher vulnerability in everyday life (Neumayer and Plümper, 2007[39]) and “gender gaps in access to information on disaster preparedness, access to public shelters and limits to mobility” (Erman et al., 2021[40]). But not all natural disasters are the same. For instance, evidence suggests that men account for 70% of flood-related deaths in Europe and the United States, potentially reflecting their greater likelihood of participation in rescue efforts (Erman et al., 2021[40]).
Besides mortality, natural disasters also impact a wide range of social, economic and health outcomes, and these impacts may vary between women and men. Several studies, mainly focused on lower-income or developing countries, show negative implications for women’s labour supply, mental health, and gender-based violence (Erman et al., 2021[40]). After a natural disaster, for example, research finds that women are at greater risk of experiencing post-traumatic stress disorder (PTSD) and anxiety. Women may also be more likely to face unemployment after a disaster, potentially reflecting increased unpaid household and care responsibilities (e.g. flood clean up, childcare due to school closures). Gender-based violence, too, has been found to increase post-disaster, including both stranger-perpetrated sexual violence and intimate partner violence (Erman et al., 2021[40]).
Women with disability, migrant women, women from racial and ethnic minorities and low-income women can face compounded disadvantages (see Chapters 4 through 8), which risk being exacerbated during crises. Yet, little research on gendered intersectional disadvantages in the context of natural disasters is available for EU and OECD countries, with most available evidence coming from developing countries. For example, women with disability are found to face elevated rates of death and greater risks of gender-based violence after natural disasters in Cambodia and Bangladesh (Gartrell et al., 2020[41]; Le Masson, 2022[42]). Greater risks of death reflect that women with disability face a “triple burden of poverty, gender and disability,” in addition to their role as carers, which limits their ability to access the political, economic and social resources required to prepare for disasters (Gartrell et al., 2020[41]). Greater risks of violence reflect that even outside of disaster contexts, women with disability who are victims/survivors may face additional barriers to accessing supports (see Chapter 8). During and immediately after disasters, disrupted support systems and weakened protections may leave women with disability even more exposed and vulnerable to exploitation and abuse.
The lack of evidence from EU and OECD countries presents an opportunity going forward. To ensure inclusive and accessible services, disaster preparedness must take intersectionality considerations into account, and outcomes before, during, and after natural disasters must be monitored using an intersectional lens (e.g. disability, race and ethnicity, Indigenous identity, income, education, age).
Gender differences in mortality from exposure to heat may depend crucially on age
All over the world, populations are increasingly exposed to hot days for longer periods of time. Gender differences in exposure to hot weather largely stem from differences in time spent outdoors (e.g. due to occupational segregation or differences in propensity to engage in outdoor leisure), access to indoor cooling methods, or differences in pre‑existing conditions.
Given the various potential factors behind gender differences in exposure to extreme temperature – many of which may differ across countries, time periods, and specific events – there is no consensus on whether men or women are at greater risk of heat-related illnesses or deaths (van Steen et al., 2018[43]; Gifford et al., 2019[44]). Estimates from the OECD Environment Statistics Database suggest that premature deaths due to high temperatures are slightly higher among men than among women, but differences are non-existent or quite small in most cases (see Online Annex Figure 9‑A6) (OECD, 2020[45]). By comparison, recent research based on the 2022 heat wave in Europe finds that, overall, women experienced more heat-related deaths than men. This gender gap, however, depended crucially on age, with men more likely to die than women when aged below 80 years and women more likely to die than men when aged 80 years and over (Ballester et al., 2023[46]).
Gender gaps may also be driven by gendered physiological differences and socio-cultural factors (Ballester et al., 2023[46]; Leach et al., 2024[47]), as well as gender disparities in health and healthcare access (e.g. unmet healthcare needs) (see Chapter 7) and economic security (e.g. higher risks of poverty) (see Chapter 5).
Gender gaps in leadership and innovation in the green transition
Politics: Women are underrepresented as climate change and environment decision-makers
By designing policy to shape incentives, governments play a critical role in leading the transition away from fossil fuels. But women are underrepresented as legislators and as ministers in nearly all EU and OECD countries (see Chapter 6), including in environment-related portfolios. In EU‑27 countries, for example, women accounted for only 34% of members of the government or political executive in national ministries dealing with environment and climate change in 2024 (Figure 9.2). This is similar to the share dealing with basic, economic and infrastructure functions, but significantly less than the share dealing with socio-cultural functions (EIGE, 2024[48]).
Share (%) of members of the government or political executive in national ministries dealing with environment and climate change who are women, 2024
Note: EU‑27 and OECD‑25 averages are unweighted. Data refer to national ministries or departments of national governments with competences in environment, climate change, energy and transport. Note that the names of the ministries may vary between countries. Members of government or political executive in national ministries refers to the sum of senior and junior government ministers with competences in environment, climate change, energy and transport. Senior ministers are ministers who have a seat in the cabinet or council of ministers, junior ministers do not. See EIGE (2023[49]) for a list of ministries included and for more details on data sources, data collection and methods. Data for this figure can be downloaded via Annex 9.A.
Source: EIGE “National ministries dealing with environment and climate change: ministers by seniority,” (https://eige.europa.eu/gender-statistics/dgs).
In the context of the green transition, research shows that greater representation of women in decision-making positions is related to a heighted focused on environment-related topics (D’souza, 2018[50]), more ambitious climate goals and more effective climate actions (Strumskyte, Ramos Magaña and Bendig, 2022[51]; Mavisakalyan and Tarverdi, 2019[52]), stronger support for environmental legislation (Ramstetter and Habersack, 2019[53]), improvements in environmental quality (DiRienzo and Das, 2019[54]; Salahodjaev and Jarilkapova, 2020[55]), greater focus on gender-specific environmental impacts (OECD, 2021[56]), and an increased likelihood of ratifying international environmental treaties (Norgaard and York, 2005[57]).
This may reflect that, in OECD countries, women are more likely to be concerned about climate change (Figure 9.1) and to report that the government is not doing enough to tackle climate change (see Online Annex Figure 9‑A2).
Business: Women are less likely than men to be managers in environmentally sensitive industries
In the green transition, businesses also have a key role to play in adopting sustainable practices, ensuring that climate targets are met in a just and inclusive way, and supporting employees through the transition.
As in the world of business at large, women are underrepresented at all levels of leadership in energy-related or environmentally sensitive sectors (European Union, 2019[58]; McKinsey, 2021[59]). Bringing more women into management and leadership positions in business could have important implications for climate action. Research has shown, for example, that a critical mass of women on boards and in senior management can lead to improved corporate social performance, better climate governance, and increased dissemination of information to stakeholders and decision-makers on environmental matters (Hafsi and Turgut, 2012[60]; Arayssi, Dah and Jizi, 2016[61]; Di Miceli and Donaggio, 2018[62]; Hossain et al., 2017[63]; Post, Rahman and Rubow, 2011[64]; Sasakawa Peace Foundation and BloombergNEF, 2020[65]; Velte, 2016[66]; Yarram and Adapa, 2021[67]), as well as more renewable energy consumption (Atif et al., 2021[68]) and environmental and climate change innovation (Moreno-Ureba, Bravo-Urquiza and Reguera-Alvarado, 2022[69]; García-Sánchez et al., 2023[70]).
Innovation and research: Women are less likely to be researching and innovating in the area of climate change and the environment
Science‑related jobs, especially in research and development, are crucial in leading the transition away from fossil fuels. But women continue to be underrepresented in most science‑related fields (see Chapters 4 and 5), including those related to the climate and the environment. In the field of climate research, for example, the Intergovernmental Panel on Climate Change (IPCC) is seen as an “authoritative and influential source of reports” (Gay-Antaki and Liverman, 2018[71]), yet women represented only 33% of authors in the Sixth Assessment Report in 2021‑23. Gender gaps are similar among authors of other publications in environmental science (see Online Annex Figure 9‑A7) (De Kleijn et al., 2020[72]).
Women-founded climate tech companies also received only 58 funding deals in 2023 worldwide, compared to 826 for companies founded by men (Garden, 2024[73]). Other research paints a similar picture (Furness, 2022[74]; Sqalli et al., 2021[75]). And, across OECD countries with available data, only 8% of patents relating to environment management, 10% of patents relating to climate change mitigation, 10% of patents relating to climate change adaptation technologies, and 15% of patents relating to a sustainable ocean economy had at least one female inventor in 2022 (see Online Annex Figure 9‑A8) (OECD, 2023[76]).
This section explores gender gaps in key indicators relating to the digital transformation using a life course approach, looking specifically at the labour market, gender-based violence, leadership and innovation.
9.2.1. Childhood and youth: Girls may be more negatively impacted by the digitalisation than boys
Digitalisation penetrates all aspects of life – including school, work, socialisation and leisure. While digitalisation can create new opportunities for healthy, productive and fulfilling lives, it can also exacerbate existing risks and create new ones (OECD, 2024[77]).
New risks largely reflect that digital environments and online communication are markedly different from face‑to-face interaction. Online interactions are, for example, often anonymous, which allows individuals to express themselves more freely, often bypassing social filters. Digital environments also lead to disembodiment (i.e. absence of physical presence), which can diminish empathy. Disinhibition is another common feature of online settings, with individuals more likely to engage in candid or extreme behaviour (OECD, 2024[77]). These features combined can create situations where harmful behaviours thrive, such as cyberbullying. Digital environments and online communication are also often designed to exploit psychological triggers that make it difficult to disengage, especially for young people, contributing to the rise of problematic internet and social media use (Pérez-Torres, 2024[78]).
Cyberbullying and problematic internet and social media use are linked to mental health issues, including anxiety, depression, and low self-esteem (OECD, 2024[77]), and research suggests that these negative behaviours in digital environments may disproportionally affect girls. Girls are, for example, more likely to report problematic social media use (see Online Annex Figure 9‑A9) and since 2017, the overall rate of young people reporting problematic social media use increased by 49% across 37 countries and regions, with the share of girls increasing more than twice as much as boys (OECD, 2022[79]; OECD, 2024[77]). In addition, in OECD countries with available data, 17% of girls aged 11‑, 13‑ and 15‑years old report having been a victim of cyberbullying at least once in the previous couple of months. This compares to 14% of boys (see Online Annex Figure 9‑A10).
Generative AI tools have also been found to create “overtly sexualised digital avatars or images of women while portraying men as more professional and career oriented” (Caira, Russo and Aranda, 2023[80]). Generative AI can also perpetuate other types of biases in visual representation of certain careers and occupations. In one study in Australia, for example, generative AI “included a disproportionately high proportion of white male medical students which is not representative of the diversity of medical students in Australia” (Currie et al., 2024[81]). This could reinforce or further entrench gender equality issues, including harmful gender stereotypes and norms, and requires close monitoring and potentially policy action (OECD, 2024[82]).
At the same time, digital technologies are also associated with a range of positive experiences and outcomes around access to education and mental health resources, social connections, creativity, self-expression and civic engagement. This means that all actors – parents, governments, teachers, communities – must help young people maximise the benefits of digital transformation while minimising the risks.
9.2.2. Adulthood: Digitalisation presents both opportunities and risks for gender equality
Through the lens of the digital transformation, this section considers gender differences in potential job losses, teleworking, technology-facilitated gender-based violence (TF-GBV) and the underrepresentation of women in innovation and research relating to digitalisation.
Employed women and men are differently impacted by the digital transformation
Recent improvements in digital technologies – especially artificial intelligence (AI) – have expanded the traditional view of automation (i.e. robots taking over repetitive, manual tasks, often in manufacturing) to encompass automation of more complex, cognitive tasks that were previously considered beyond technological reach (e.g. problem-solving, language comprehension and decision-making) (OECD, 2023[83]).
These developments have the potential to reshape labour markets, change management practices, and completely alter the type and extent of interactions between machines, computers, managers and colleagues. Impacts could be positive, including, for example, improved work-life balance, increased workplace safety, a reduction in undesirable tasks, and increased demand for human-only skills (e.g. communication, customer service, leadership, creativity, originality, complex social interaction and dealing with uncertainty) (Brodnitz, 2024[84]; Raman and Flynn, 2024[85]; UNESCO/OECD/IDB, 2022[86]). At the same time, impacts could be negative, including reduced demand for certain skills and/or jobs and increased levels and/or durations of unemployment.
As in the case of the green transition, occupational and industrial segregation by gender (see Chapter 5) means that women and men may face different degrees of positive and negative impacts from the digital transformation. Women and men may also have different capacities to respond to or deal with the digital transformation (e.g. learn new skills or tools).
Women and men, for example, may have different opportunities to access and use remote working or teleworking arrangements – and employers and colleagues may perceive the use of such arrangements by women and men differently (see below) (OECD, 2023[6]). Women and men may also experience differences in changes to management practices (e.g. performance reviews, surveillance) and workplace health and safety (e.g. automation of dangerous tasks).
AI advances (particularly in generative AI) have recently attracted a lot of attention. Although empirical analyses do not suggest that overall employment levels have fallen due to AI (e.g. OECD (2023[83]), Lane (2024[87])), certain groups may be more likely to experience job losses and the future impact of AI could be different as the technology matures and diffuses and as new advances emerge. For this reason, researchers continue to estimate the (potential) impact of AI on different occupations and socio‑economic groups (e.g. OECD (2024[88]; 2024[89]), Lane (2024[87]), Cazzaniga et al. (2024[90]), Gmyrek, Berg and Bescond (2023[91]), Lassébie and Quintini (2022[92]), McKinsey Global Institute (2023[93]), Dabla-Norris and Khalid (2019[94]), Webb (2019[95]) and Cortes, Jaimovich and Siu (2018[96]), Nedelkoska and Quintini (2018[97]), Brussevich).
When looking at the gender angle, research comes to different conclusions due to the use of different methodologies and assumptions – including on the speed and nature of technological advances, the diffusion of these technologies throughout industries and sectors, and potential protective barriers (e.g. task mix, education level, employment protection, employer versus employee power, etc.), among others. Some studies suggest that men could be at higher risk of automation due to all technologies (not just AI) (e.g. Lassébie and Quintini (2022[92]), Webb (2019[95])) and some studies suggest that women could be at higher risk (e.g. Gmyrek, Berg and Bescond (2023[91])). Other studies suggest that women and men face roughly similar levels of occupational exposure to AI, but that effects differ by occupation. Clerical workers (where women are overrepresented) and science and engineering professionals and chief executives (where women are underrepresented) face particularly high exposure to AI (OECD, 2024[89]).
Despite the lack of consensus on gender differences in potential future impacts of the digital transformation, there is agreement that the digital transformation will be disruptive to those occupations exposed to it, that workers need to be prepared to adapt to change, and that impacts will be unequal across population subgroups. Not all workers are equally prepared to adapt to change, with evidence pointing to gender gaps in digital skills (e.g. programming) that could contribute to gender differences in the labour market impacts of the digital transformation (OECD, 2024[98]). This requires a close monitoring of developments in the labour market with a gender-sensitive lens and appropriate investment in public policies to assist both women and men who lose their jobs with retraining, re‑skilling and re‑entering the labour market.
Results from the 2024 OECD Risks that Matter Survey show that women and men are aware of the potential for both positive and negative impacts – but men are more likely to believe that technology will help them in some way over the next five years, such as by improving their work-life balance or reducing the repetitiveness of their work (Figure 9.3). Men are also more concerned about potential negative impacts than women, including being replaced by a robot, AI or a person providing a similar service on an Internet platform. They are also more concerned about losing employment due to a lack of or incompatible technical skills.
Share (%) of employed women and men who predict or anticipate certain employment outcomes as a result of automation and technological change, average of 27 OECD RTM countries, 2024
Note: All estimates are unweighted averages across RTM‑27 countries. Respondents were asked “How likely do you think it is that the following will happen to your job (or job opportunities) over the next five years? (a) My job will be replaced by a robot, (b) My job will be taken over by an artificial intelligence (AI) tool like ChatGPT, (c) My job will be replaced by a person providing a similar service on an internet platform, (d) I will lose my job because I am not good enough with new technology or because I will be replaced by someone with better technological skills, (e) Technology will help my job and working hours become more compatible with my private life, (f) Technology will help my job become less dangerous or physically demanding, (g) Technology will help my job become less boring, repetitive, stressful or mentally demanding.” Response items (a) through (g) were randomly rotated. Response options were: “Very unlikely,” “Unlikely,” “Likely,” “Very likely” and “Can’t choose.” Estimates refer to the combined share of “Likely” and “Very likely.” This question was only asked to those who reported that they were in paid work or temporarily away from paid work. Data for this figure can be downloaded via Annex 9.A.
Source: OECD Secretariat calculations using OECD 2024 Risks that Matter Survey microdata (https://oe.cd/rtm).
Platform work – like self-employment – may support a better balance between work and care responsibilities, and like other self-employed workers, platform workers also “have limited access to social protection, are not covered by employment protection or minimum wages, and are typically not allowed to engage in collective bargaining” (OECD, 2024[99]). At the same time, unlike self-employed workers, platform workers have limited or no business capital, may be dependent on only a few clients (e.g. Uber), and do not always enjoy entrepreneurial freedoms, such as choosing their own prices (OECD, 2024[99]). Platform workers may also have poor or no career development options (European Union, 2020[100]; Eurofound, 2018[101]; Cirillo, Guarascio and Parolin, 2023[102]; OECD, 2024[99]). Just as women are, in general, less likely to be self-employed (see Chapter 5), evidence from the 2022 OECD Risks that Matter Survey suggests that women are also slightly less likely to engage in platform work than men (see Online Annex Figure 9‑A11). Similar findings come out of the European Institute for Gender Equality (EIGE)’s 2020 Survey of Platform Workers, run in 10 EU countries, where women represented between 33% (Finland) and 48% (Poland) of platform workers (EIGE, 2022[103]).
In the last two decades, the creator economy has gained prominence, giving both women and men new opportunities to generate income, express creativity and build audiences. While the digital economy is often celebrated for its relatively low barriers to entry, which may help women enter the labour market, gender disparities remain an issue. A recent study focusing on Italy’s YouTube ecosystem, spanning over 18 000 channels launched between 2006 and 2023, sheds light on these ongoing challenges and the evolving role of gender in this space (Gioia and Morabito, 2025[104]). The study finds, for example, that men entered the YouTube space significantly earlier than women, that there are gendered content niches (e.g. women content creators specialise in beauty and food, while men dominate areas such as technology and knowledge), that women tend to receive lower audience engagement compared to men, and that women tend to have shorter tenures on the platform.
The increasing use of AI in the labour market – including but not limited to job search, job advertisement, human resources management and performance management – presents both challenges and opportunities. AI could, for example, further entrench existing gender gaps, as it must be trained on existing data sets, which have implicit or explicit biases and assumptions regarding gender and other characteristics, such as race and ethnicity (Borgonovi, Hervé and Seitz, 2023[105]; Lazaro, 2022[106]). These biases can become embedded into programmes and software through unrepresentative datasets or through model weights in AI algorithms, leading to risks such as incorrect, differential and discriminatory treatment of labour market groups, including those who are underrepresented or vulnerable (EIGE, 2021[107]; UNESCO/OECD/IDB, 2022[86]; Borgonovi, Hervé and Seitz, 2023[105]). At the same time, with intentional effort, AI could be used to reduce gender bias and improve fairness, increasing job quality and inclusiveness (OECD, 2023[83]). Ensuring that AI systems are designed to appropriately address harmful embedded bias and discrimination this requires careful planning and review and the consideration and/or inclusion of women and other underrepresented groups at the early stages of and throughout the AI system lifecycle (UNESCO/OECD/IDB, 2022[86]; EIGE, 2021[107]; OECD, 2023[83]).
Teleworking may improve work-life balance, but could further entrench gender norms around unpaid care responsibilities
The digital transformation has facilitated teleworking, remote working and working from home, which can improve job satisfaction and work-life balance by reducing commute times, increasing autonomy and allowing for greater flexibility in working hours (Cazes et al., 2022[108]). Depending on the patterns of use of teleworking, remote working and working from home, there may be positive or negative impacts on gender equality (Touzet, 2023[109]).
On the one hand, teleworking, remote working and working from home may improve gender equality in the labour market by enabling both women and men to better reconcile work and life. Consider, for example, a randomised controlled trial in Italy where women and men workers could choose the location and timing of their work. Results showed that both women and men spent more time doing housework and care activities, suggesting that flexible working arrangements could help reduce or eliminate gender gaps in unpaid care and housework responsibilities (Touzet, 2023[109]; Angelici and Profeta, 2020[110]). On the other hand, teleworking, remote working and working from home may reinforce gender norms around unpaid care and household responsibilities (OECD, 2023[6]). This may be especially true if and when women dominate the use of such flexible working arrangements due to pre‑existing responsibilities, which can create and reinforce expectations and assumptions that women can and should use flexible working arrangements to combine work and family. Teleworking, remote working and working from home may also lead to increased work intensity and (unpaid) overtime hours (Chung, 2022[111]), as well as social and professional isolation (Charalampous et al., 2018[112]; Tavares, 2017[113]).
Research has further pointed to a gendered stigma around workplace flexibility – where employees (particularly women) who use flexible worker arrangements (including teleworking, remote working and working from home, but also shifted hours, compressed weeks and job sharing) for caregiving purposes are perceived as less productive and less committed (Chung and Seo, 2024[114]; Chung, 2018[115]; Chung, 2018[115]; Chung, 2024[116]). This stigma may contribute to widening gender disparities in career progression and wages (Arntz, Sarra and Berlingieri, 2019[117]; Mas and Pallais, 2017[118]; Chung and van der Lippe, 2018[119]; Leslie et al., 2012[120]; Tomei, 2021[121]). This is despite the fact that this stigma appears to be based on perceptions, rather than actual productivity outcomes, since evidence suggests that flexible working arrangements and telework are not necessarily productivity-reducing and may, in fact, be productivity-enhancing (Brecheisen, 2023[122]; Bartik et al., 2023[123]).
These mixed results reflect that teleworking, remote working and working from home themselves may not lead to improvements or reductions in gender equality on their own. Instead, what matters is the interaction of teleworking, remote working and working from home with public and workplace policies (e.g. right to request rules that enable everyone, not just parents to telework), as well as gendered norms and stereotypes around unpaid care and household responsibilities.
Digital technologies facilitate “constant connectedness” to employment, which may increase employers’ expectations of employee availability outside of regular work hours (OECD, 2019[124]). This may lead to peer pressure and a race to the bottom among employees determined to show their work availability and outputs. Given that women are often responsible for more unpaid household tasks than men (see Chapter 5), women may be less able to meet such expectations of constant connectedness. Indeed, in 2019, 42% of employed men self-reported being contacted at least occasionally by their employer during their leisure time within the last two months, but only 35% of women reported the same (see Online Annex Figure 9‑A12) (Eurostat, 2022[125]). Such gender differences in connectedness outside of working hours could differentially impact earnings growth and promotion opportunities (see Chapters 5 and 6). Evidence suggests that women tend to select jobs or firms (even within a given occupation or industry) that offer greater flexibility, but that may come with lower wages, reflecting “compensating differentials” (or a trade‑off) in the labour market around pay and flexible working arrangements (Goldin, 2014[126]; Sobeck, 2024[127]).
Recognising the importance of the right to disconnect, the European Parliament called on the European Commission to “come up with a law granting employees the right to disconnect from work during non-work hours without consequences and setting minimum standards for remote work” (European Parliament, 2021[128]).
Compared to centuries ago, automation has already massively reduced time spent on unpaid work – think washing machines, dishwashers and microwaves. Digital technologies are also increasingly being used by many in undertaking unpaid care activities. In a 2022 EIGE survey, for example, 50% of respondents stated they use digital tools and resources at least several times a month in their role as a carer for people who depend on help with daily living activities (e.g. e‑health tools, web platforms, apps with reminders about medications), and 22% said they use them daily. 53% also reported using digital tools and resources in their childcare activities (e.g. online learning, childcare management apps and tools, leisure time tools) at least several times a month, and 24% reported using them daily. For housework tasks, 43% reported using digital tools and resources (e.g. vacuum robot, smart homes, robotic lawn mowers, ordering grocery delivery) at least several times a month, with 17% reporting using them daily.
Looking ahead, AI could continue to reduce the burden of unpaid care work. According to 65 AI experts from the United Kingdom and Japan, for example, among a specified list of 17 house and care work tasks, “39% of the time spent on a domestic task will be automatable within ten years” (Lehdonvirta et al., 2023[129]). Tasks relating to childcare and eldercare were deemed less automatable, while those related to housework (e.g. cooking, cleaning and shopping) more automatable. Among the experts consulted, women and men differed in their expectations about the automatability of domestic work, potentially reflecting gender differences in their lived experiences with technology as well as with house and care work. Another study that adapted the automation likelihood of paid work to domestic work tasks (e.g. cooking, dish washing, laundry, pet care) found that automation could save 50‑60% of the total time spent on unpaid domestic work (Hertog et al., 2023[130]).
These results suggest that there are and could continue to be tremendous gains from using AI to reduce the burden of unpaid work. Policy could steer this process by spurring investments in research and development of new tools and technologies that reduce unpaid care and household responsibilities and by supporting better access to existing tools and technologies (e.g. robotic vacuums).
At the same time, many virtual personal assistants (e.g. Alexa and Siri) and advanced humanoid robots (e.g. Sophia, Ameca, Jia Jia, and Nadine) are animated with female voices, reflecting traditional gender stereotypes and norms of women as nurturers in supporting roles (OECD.AI Policy Observatory, 2023[131]). AI could therefore potentially reinforce pre‑existing gender gaps.
Technology-facilitated gender-based violence is a significant risk for women public figures
While opportunities and risks exists for women and girls in digital environments, an important risk relates to technology-facilitated gender based violence (TF-GBV) (OECD, 2024[82]), a form of violence where perpetrators use digital technologies – such as social media, messaging apps, online forums, gaming platforms and other digital communications tools – to intimidate, bully, stalk, harass, threaten or otherwise cause harm (Canadian Women's Foundation, 2024[132]; OECD, 2024[82]). Such violence may exist on its own or it may be used as an additional tool to further aggravate or amplify other forms of violence (Government of Australia, 2024[133]).
Although data on TF-GBV are still limited, the data that do exist show that women and girls – especially women public figures – may be at greater risk than men and boys (Dunn, 2021[134]). On average across EU and OECD countries, girls are more likely than boys to report being victims of cyberbullying at least once in the past couple of months (see Online Annex Figure 9‑A10) (OECD, 2024[82]; 2022[79]; 2024[135]). A survey by the Economist Intelligence Unit additionally finds that 85% of women report witnessing online violence against other women (including from outside their networks), 65% report knowing other women who had been targeted online from their personal or professional networks, and 38% report personal experiences with online violence (EIU, 2021[136]). The most common types of online threats to women are misinformation and disinformation (Box 9.11), cyber harassment and hate speech. Other studies focusing on women public figures have further identified TF-GBV and have linked it to poorer retention of women in politics (OECD, 2024[82]). TF-GBV is also a growing concern within immersive technologies and environments, including virtual reality (OECD, 2024[82]).
According to a recent EU survey, the high prevalence of online violence against women is relatively normalised, with 27% of respondents agreeing that when a woman shares her opinion on social media, she should accept that it may elicit sexist, demeaning and/or abusive replies (see Online Annex Figure 9‑A13) (Eurobarometer, 2024[137]).
Misinformation and disinformation are gaining increasing attention internationally, especially in the context of democracy, citizen participation, and trust in government (Aïmeur, Amri and Brassard, 2023[138]; Pérez-Escolar, Lilleker and Tapia-Frade, 2023[139]; Muhammed T and Mathew, 2022[140]; OECD, 2022[141]; OECD, 2022[142]; OECD, 2022[143]; Lesher, Pawelec and Desai, 2022[144]), and research is increasingly exploring the interaction of these issues with gender.
Gendered targeting: Famous women, especially women in politics, are targeted by a disproportionate amount of “gendered disinformation campaigns [featuring] fake stories and threats, as well as humiliating and sexually charged images” (Di Meco and Wilfore, 2021[145]). These campaigns aim to undermine women by framing them as “inherently untrustworthy, unintelligent, or too emotional or too libidinous to hold office or participate in democratic politics” (Di Meco and Wilfore, 2021[145]). Examples abound (UK Government Stabilisation Unit, 2020[146]).
Gender differences in use of and trust across sources: Women and men may react differently to the same information. For example, women are found to trust expert sources more and are less questioning of celebrity and citizen sources, while men perceive news with political sources and no sources as more credible (Martí-Danés et al., 2023[147]). The same may be true for the type of platforms through which information is obtained. According to the OECD Truth Quest survey, for example, women are more likely to get information from social media – which is the least trusted media source overall (OECD, 2024[148]). While there are only small gender differences in trust of information from social media on average, differences are notable in some countries (OECD, 2024[148]).
Gendered narratives: Some disinformation campaigns use narratives around gender to divide public opinion, weaken social cohesion and sow fear. In many instances, these narratives are intersected with narratives on race, ethnicity, migrant status, beliefs and religion. For example, disinformation campaigns may manufacture information and data on controversial gender topics such as sexual violence perpetrated by migrants (UK Government Stabilisation Unit, 2020[146]).
Gender differences in confidence in identification of false and/or misleading information: The OECD’s Truth Quest Survey finds that men are more confident in their abilities to identify false and/or misleading information than women (OECD, 2024[149]). However, the survey also finds that confidence is not related to actual ability, with no sizeable gender differences in actual ability to identify false and misleading information across content types (e.g. disinformation, misinformation, contextual deception, propaganda and satire) and themes (e.g. environment, health, international affairs).
Note: According to the OECD taxonomy of false and misleading content online, disinformation is defined as verifiably false or misleading information that is knowingly and intentionally created and shared for economic gain or to deliberately deceive, manipulate or inflict harm on a person, social group, organisation or country. According to this same taxonomy, misinformation is defined as false or misleading information that is shared unknowingly and is not intended to deliberately deceive, manipulate or inflict harm on a person, social group, organisation or country (Lesher, Pawelec and Desai, 2022[144]).
Gender gaps in research and innovation in the digital transformation
Despite strong growth in AI and ICT-related jobs and skills (UNESCO/OECD/IDB, 2022[86]; Green and Lamby, 2023[150]; OECD, 2023[6]; Manca, 2023[151]; OECD, 2024[152]; OECD, 2024[148]), women are less likely to participate as developers in the digital transformation, in ICT task-intensive jobs, and in developing and maintaining ICT and AI systems (Green and Lamby, 2023[150]; OECD, 2024[148]). This is true no matter what indicator is used for measuring women’s participation. For example:
ICT specialists: In 2023, only 11‑24% of all ICT specialists in OECD countries were women (OECD, 2024[148]).
ICT-related patents: Most ICT patent inventors are men, with only 4% of ICT-related patent families attributed to women (only) and 20% attributed to at least one woman in 2018‑21 (OECD, 2024[148]).
ICT-related businesses: Over the last two decades, an average of 6% of start-ups in digital-related activities in OECD countries funded by venture capital were founded by only women and 15% were founded by at least one woman (OECD, 2024[148]).
AI skills: Men are more likely than women to report AI-related skills on LinkedIn (Caira, Russo and Aranda, 2023[80]; World Economic Forum, 2025[153]).
AI research: In 2022, about 45% of AI publications had at least one female author. For men, the same share is 89%. Turning to exclusive authorship, only 11% of AI papers were written only by women, compared to 55% written only by men (Caira, Russo and Aranda, 2023[80]). This underrepresentation exists also in fiction: out of 116 AI researchers in 142 influential films between 1920 and 2020, only nine were women (Cave et al., 2023[154]).
AI faculty: On average, among top US-based university AI programmes, only 22% of faculty were women, ranging from a low of 8% at the University of Pennsylvania to a high of 43% at Harvard (Sey and Hafkin, 2019[155]).
AI developers: In a 2022 Stack Overflow survey of over 70 000 developers, 92% of all respondents and 93% of professional developers identified as a man (Stack Overflow, 2022[156]).
Studies also find that encouraging women to enter STEM fields is only one part of the solution – retention is another. According to research in Canada, for example, even when women do pursue postsecondary education in STEM fields, they are less likely to work and persist in STEM occupations (Frank, 2019[157]).
Beyond the indicators presented in this chapter and in the Online Annex, relevant data sources include:
OECD Dashboard on Gender Gaps: Presents key indicators on gender inequalities in education, employment, governance and private and public leadership.
OECD Programme for International Student Assessment (PISA): Features data on students’ behaviours, experiences, expectations, and skills, with special content on environmental actions, knowledge of climate change and the use of digital technologies.
OECD Child Well-Being Data Portal: Includes data on the experiences of children online, including problematic social media use and cyberbullying, among other indicators.
OECD Skills Outlook: Offers insights into ongoing and forthcoming issues related to skills, including issues relating to the green transition and the digital transformation.
OECD Environment Statistics: Provides statistics on air quality and health by gender and age, as well as data on patent development by gender.
OECD ICT Access and Usage by Households and Individuals Database: Contains indicators on access to and use of the Internet.
OECD Going Digital Toolkit: Presents key indicators by gender on use of the Internet, digital skills and abilities, and perceptions of digital technologies, among others.
OECD.AI Policy Observatory: Features gender data on AI publications, AI skills, the prevalence of AI talent, and the demographics of AI professionals.
OECD Risks That Matter Survey: Includes questions on perceptions of the risks of climate change and automation and preferences for related government policy.
European Institute for Gender Equality (EIGE)’s Gender Statistics Database: Contains information on gender equality, including women in decision-making positions linked to climate change and the environment.
Eurostat Digital Economy and Society Database: Includes a variety of statistics on digitalisation from the perspective of individuals, households and businesses.
University of Oxford Digital Gender Gaps Web App: Presents gender-disaggregated data on digital gender gaps and adoption levels for countries globally, including internet use and mobile phone ownership at the national and subnational level.
Using Table 9.1, this section applies the priority considerations of the conceptual framework included in Chapter 3 to advance gender equality by exploring two examples of policy goals (priority consideration 1) relating to gender equality in the green transition (Outcome A) and the digital transformation (Outcome B). These goals need to be accompanied by a results framework (priority considerations 1 and 4), whose indicators can be drawn from those presented in Section 9.1 and additional sources.
Table 9.1 is designed to assist policy makers in identifying cross-portfolio policy and programme combinations (priority consideration 3) and planning for their evaluation (priority consideration 2). While the list of policy options is extensive, it does not pretend to be exhaustive. At the same time, not all policy options apply in all settings or contexts. Overall, Table 9.1 aims to encourage the consideration of different policy options as part of a cross-sectoral and multi-stakeholder approach that works towards the achievement of gender equality outcomes. The green transition and the digital transformation may impact various aspects of women and men’s lives (education, employment, health, violence, etc.), meaning that policy options need to involve a range of ministries and reflect a life course approach.
Consider education, for example. In the earliest stages of life, learning materials that challenge gender stereotypes and norms around mathematics and science can ensure that girls and boys and women and men can equally see themselves pursuing careers in the green and digital economies. In later stages of life, re‑training and re‑skilling can enable equal access to opportunities in those fields. Similarly, in the context of the digital transformation, gender bias in AI may need to be specifically addressed through legislation to ensure more equal treatment of women and men across employment, health, social protection, justice and more. In the case of the green transition, embedding gender considerations into transportation and infrastructure planning and development may help to foster safety through, for example, better lighting and emergency call boxes in public transport hubs.
Table 9.1 also highlights the important feedback loops between policy goals, with both the green transition and the digital transformation linking back to gender gaps in educational attainment and skills (see Chapter 4), paid and unpaid work (see Chapter 5), leadership and representation (see Chapter 6), health (see Chapter 7) and gender-based violence (see Chapter 8).
The effectiveness of the policies and programmes outlined in Table 9.1 varies across countries and across time. Continuous monitoring and evaluation that incorporates a gender perspective is therefore essential for governments to understand the gendered effects of policies and programmes (see Chapters 2 and 3); ensure that policies and programmes are achieving their intended outcomes; identify strengths and areas for improvement; improve decision-making, resource allocation and accountability; and inform future strategies (priority consideration 6). While international evidence offers valuable insights on similar interventions, the effectiveness of each policy and programme will depend on their specific design and context – including interactions with other interventions, socio‑economic and cultural factors, available resources, and institutional settings.
For instance, a study evaluating scalable programmes aimed at facilitating labour market transitions for women in technology found that targeted interventions, such as mentoring and job-training programmes, can enhance women’s success rates in obtaining tech jobs (Athey and Palikot, 2022[158]). At the same time, a systematic literature review of initiatives to recruit and retain women in computing education, categorised into policy, pedagogy, support, and engagement, highlighted that most of them lack rigorous evaluation (Berry et al., 2022[159]). Similarly, policy analyses suggest that designing public spaces and transportation systems that are safe and accessible for women encourages their active participation in green economies (OECD, 2024[82]), but thorough academic evaluations are scarce.
The limited availability of evaluations of interventions to address gender gaps in the green transition and digital transformation poses challenges for designing successful policy responses. In fast-changing fields such as those related to the green transition and the digital transformation, embedding an evaluation perspective in public interventions is essential to generate timely lessons, ensure a better understanding of the effects of policies and programmes from a gender angle, and adapt public action as contexts and needs evolve.
9.3.1. Key policy actions across EU and OECD countries
Note: “Env.” stands for Environment and “Agri.” stands for Agriculture.
Source: OECD Secretariat based on desk research and the 2024 OECD Questionnaire on Policy Combinations for Gender Equality and OECD (2022[160]), OECD (2024[161]; 2024[89]; 2024[77]), Koshiyama et al. (2022[162]), Lerouge and Trujillo Pons (2022[163]), Jochecová (2023[164]), Eurofound (2023[165]) and European Union (2015[166]).
9.3.2. Country case studies of key policy combinations in EU and OECD countries
According to the OECD Secretariat’s 2024 Questionnaire on Policy Combinations for Gender Equality, many EU and OECD countries have implemented policy combinations to advance gender equality in the green transition and digital transformation. Case studies are provided below.
Promoting gender equality in the green transition
Costa Rica’s National Action Plan on Gender Equality in Climate Action (2023‑25) is a collaborative initiative by the National Institute for Women (INAMU), the United Nations Development Programme (UNDP), the Ministry of Environment and Energy (MINAE), and the Ministry of Women’s Affairs. It seeks to close gender gaps in climate action by enhancing women’s roles as change agents, increasing their resilience, and involving them in local climate decision-making. The plan focuses on five strategic areas with approximately 40 actions, including promoting equality and sustainability, including integrating gender and environmental perspectives in strategic plans, creating a national network for gender equality in climate action, and increasing women’s representation in decision-making bodies for climate action; empowering women’s economic autonomy by expanding services supporting women’s economic activities related to climate change and promoting women in non-traditional roles such as reforestation and blue and green jobs; building capacities and fostering innovation through capacity-building for institutional staff and women in key sectors related to climate change; managing climate‑related risks; and generating data on women’s diverse situations related to the environment. The plan establishes a shared governance model between INAMU and MINAE, co‑ordinating the implementation of priority actions involving public institutions, the private sector, and local governments.
The Task Force for the “Climate Crisis and Gender” in Greece was established by the Ministry of Social Cohesion and Family to address the gender-specific impacts of the climate crisis. Recognising that women face unique challenges in the wake of natural disasters, the Task Force aims to document these issues and promote gender-balanced representation in decision-making. By collaborating with NGOs, universities, and research institutions, it seeks to create a scientific report that will guide the development of effective policies to eliminate gender inequalities related to the climate crisis.
Japan’s Fifth Basic Plan for Gender Equality (2020‑25) addresses gender inequality by promoting women’s economic independence, work-life balance, women’s participation in decision-making, and safety and security. It also integrates gender perspectives into disaster prevention, reconstruction, and environmental issues. Recognising the impact of natural disasters, and informed by past experiences like the Great East Japan Earthquake, the strategy advocates for gender-sensitive disaster management practices and environmental policies – including within Japan’s national disaster prevention and reconstruction framework. Key initiatives include targeted training to disaster management personnel to raise awareness of the different impacts disasters have on women and men. The strategy also supports local governments in adopting gender-sensitive disaster management measures, promoting the use of the “Guidelines for disaster prevention and reconstruction from the perspective of gender equality.” Japan aligns its efforts with global frameworks such as the Sendai Framework for Disaster Risk Reduction (2015‑30) and the UN’s CSW resolution 58/2. In environmental policy, the strategy highlights the importance of women’s participation in shaping industrial and energy policies, particularly those addressing climate change. To drive these initiatives, Japan has set targets, such as achieving 30% women’s representation on Local Disaster Management Councils by 2025 and increasing the proportion of women firefighters and volunteer fire department members.
Ensuring gender equality throughout the digital transformation
Greece enhances women’s representation in the digital transformation with foundational education and professional development. In early education, digital technologies are used daily and are functionally integrated in all thematic fields. Moreover, the Ministry of Education, Religious Affairs and Sports has implemented pilot ICT projects in pre‑schools to foster digital literacy among girls. It has also developed Innovation Centres in 13 regional directorates to connect schools with research institutions, universities, and businesses, with the aim to modernise vocational education and promote STEM careers, particularly for girls. Greece also applies gender-based approaches to ensure that educational content and career guidance are tailored to attract more women into advanced technology and digital innovation. At the same time, the Gender Innovation Lab for Women (GIL4W), launched with the support of the Ministries of Development, Social Cohesion and Family, and Interior, brings together over 25 academic, research, and commercial entities to create a collaborative ecosystem that promotes women’s active participation in research, innovation, and digital business. By focusing on best practices and strategies from Europe and globally, GIL4W seeks to increase women’s roles as developers and inventors in the digital economy in Greece.
Hungary promotes gender equality in digitalisation by addressing gender gaps at multiple levels – including in education, professional development, and representation. In early education, the National Core Curriculum, managed by the Ministry of Interior, introduced Digital Culture as a subject, replacing traditional ICT courses. This curriculum focuses on algorithmic thinking, programming and digital citizenship, ensuring that all students develop essential digital skills from an early age. At the same time, the “Your Future!” programme, managed by the Ministry of National Economy, increased the number of applicants to IT courses and involved over 60 000 students through digital experience centres, making digital skills accessible to those from less developed regions. This initiative also actively worked to break down gender stereotypes in the IT profession. The National Digitalisation Strategy 2022‑30, led by the Prime Minister’s Office, focuses on increasing the proportion of women in ICT by supporting their retention and success in tertiary ICT education. This includes specific measures to reduce dropout rates among women students. The DIMOP PLUS programme, also under the Prime Minister’s Office, complements these efforts by supporting gender representation in digital transformation projects to increase the number of highly skilled women ICT professionals. The Hungarian Association of IT Companies and the Women in Technology Hungary Association also launched “40+ women role models in the digital economy” to showcase women who have made significant contributions to the digital economy, serving as role models for younger women and encouraging them to pursue careers in technology.
Several ministries in Norway, including Culture and Equality; Children and Families; Trade, Industry and Fisheries, share responsibility for “Time for games – the government’s gaming strategy 2024‑26.” The strategy points to the strengths and the potential of the gaming culture as a leisure activity, an expression of art and culture, for e‑sport and as a tool for learning. It also highlights significant challenges related to hate speech, insults and harassment in gaming culture. The strategy’s initiatives in this area will help strengthen knowledge and expertise, activity and content, and the infrastructure for safe and inclusive physical and digital meeting places. It will work toward the achievement of a diverse and impactful selection of high-quality computer games; equality and diversity in Norwegian games and the Norwegian gaming industry; professionalism and growth in the Norwegian gaming industry; and an inclusive, safe and accessible gaming culture.
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Note: Supporting data for all Chapter 9 figures in the main text and the Online Annex are available in the StatLink below.