Call for evidence outcome

Building a Future Tech Sector That Works for Everyone: call for evidence findings

Updated 6 July 2026

Ministerial foreword

The UK’s tech sector is one of our greatest strengths. Since becoming Technology Secretary, I have been struck by the optimism, ambition and innovation that defines our science and tech ecosystem.

Last year, our science and tech companies raised more venture capital than France, Switzerland and Germany combined. We saw the creation of 16 new unicorns; and AI startups secured $7.9 billion in funding (just under £6 billion), an 80% increase on the year before^{[footnote 1]}.

We are home to world-leading digital and tech firms shaping the future of our economy.

But this success is not shared equally - and it falls short of its potential because the sector is not yet representative of the full talent of this great country.

The evidence is clear. Women are less likely to enter the sector, less likely to stay, and less likely to progress into leadership. Not because of a lack of talent, but because of barriers that hold them back.

This starts in school. Girls outperform boys in GCSE Computer Science^{[footnote 2]} yet only 1 in 5 of the A-level exam entrants are girls^{[footnote 3]}.

This persists and compounds as women move into the workplace: with less women entering and even fewer progressing into leadership roles in tech. At the current rate, it will take 283 years to reach parity in representation between men and women across the tech sector^{[footnote 4]}, while the UK loses an estimated £2-3.5 billion each year as women leave tech roles^{[footnote 5]}.

Tech offers some of the most exciting, high-quality opportunities in the economy and I am clear that women should be able to seize these opportunities, going as far as they want in the fields in which they can succeed. This is a matter of principle, makes economic sense, and it is critical to ensure the tech of tomorrow works for all.

It is no coincidence that AI tools used in recruitment have already been shown to favour male candidates^{[footnote 6]}. That’s what happens when the people building the tech do not reflect the people it is meant to serve.

We now have a unique opportunity to shape a sector that works for everyone. In December, I launched the Women in Tech Taskforce. This is a group of 14 experts and industry leaders developing practical solutions for government and industry, side by side.

As well as bringing more women into tech, we must ensure they are treated fairly and supported to succeed. And we want to start with the facts, and the real experiences of the people in the sector. This call for evidence is foundational to that work, helping us ensure that any interventions proposed by the Taskforce are grounded in the realities of women across the sector and can keep pace with the rate of technological change shaping the sector.

The findings set out in this report underscore both the scale of the challenge and the urgency of the action needed to drive gender parity in the sector.

They point to the need not only to widen access to opportunities to enter and work in tech, but also to create an environment in which women can thrive and lead in shaping the technologies of the future.

They show that emerging technologies are already reshaping the skills, roles and pathways at pace. While this creates significant opportunity, it is also changing who enters, progresses and succeeds in the sector - risking the reinforcement of existing inequalities if left unaddressed.

Respondents have told us they are already experiencing this unevenly, and that they are facing barriers to training, access to networks and progression. They have also highlighted challenges in returning to the sector after maternity leave and other caring responsibilities.

Too many people also told us, directly and in their own words, about experiences of misconduct, harassment, and discrimination. These were not easy things to share, and I want to be clear that they have been heard. They are unacceptable, and they must change.

To everyone who responded to this call for evidence, thank you.

You have spoken and we have heard you. You shared the challenges you face and a belief that things can be better. That belief is not misplaced. Your voices will shape what we do next.

Sincerely,

The Rt Hon Liz Kendall

Secretary of State for The Department for Science, Innovation and Technology

Introduction

This report presents a summary of the findings of the call for evidence on ‘Building A Future Tech Sector That Works For Everyone’ launched in March 2026 by the Department of Science, Innovation and Technology (DSIT).

In December 2025, DSIT Secretary of State, Liz Kendall, launched the Women in Tech Taskforce (the “Taskforce”) to address the systemic barriers that prevent women from entering, progressing, and leading in the tech sector.

The Taskforce is working to address the systemic barriers that prevent women from entering, progressing, and leading in the tech sector. This work is increasingly urgent as the wider context of the sector is changing rapidly - new and emerging technologies are reshaping the economy, transforming how, where, and on what we work.

Ensuring that everyone can participate in this evolving landscape is essential for delivering better, more inclusive tech and services, as well as unlocking the full potential of the UK economy. When more people can contribute to technological change, businesses gain access to a broader talent pool, improved productivity, and greater innovation–driving economic benefits across the UK.

However, structural barriers continue to limit who can enter, stay, and succeed in the tech industry. These challenges have created an uneven playing field and a sector that does not yet reflect the diversity of the UK:

• Only 9% of tech employees are reported to be from lower socio-economic backgrounds, compared with 29% in finance and 23% in law, 29%^{[footnote 7]} of tech employees, and only 21% of senior tech role holders, are women or non-binary^{[footnote 8]}

• While 25% of employees are from ethnic minorities (vs 19% nationally), representation drops to just 14% in senior roles^{[footnote 9]}

• 6% of tech employees are disabled relative to 23% of the UK working population, with 63% facing qualification barriers^{[footnote 10]}

• Older professionals (50+) make up 31% of the working-age population but only 20% of the tech workforce ^{[footnote 11]}

As era-defining technologies such as AI, quantum, and engineering biology are still being built, the decisions made now about who participates in shaping them will influence the future of the tech sector, and society, for years to come.

Without deliberate action, existing inequalities risk being replicated or further entrenched in these emerging fields, and this is already happening. AI tools used in recruitment have been found to favour male names nearly 5 times more than females^{[footnote 12]}, and research uncovered AI models built to predict liver disease were twice as likely to miss the disease in women^{[footnote 13]}.

Throughout this report, the analysis recognises that some individuals experience multiple, overlapping barriers associated with characteristics such as gender, ethnicity, disability and socioeconomic background. Where relevant, these experiences are reflected in the findings.

This call for evidence sought insights into the interventions needed to help build a tech sector that works for everyone – within the wider context of rapid sectoral changes driven by emerging technologies, to inform the work of the Taskforce.

The call for evidence sought insights into:

• practical examples of interventions (schemes, programmes, or organisation approaches) that have supported greater participation, progression, or leadership of women and other underrepresented groups in tech
• how and why these worked in practice, including their design, scope, and delivery
• how emerging technologies are reshaping the tech workforce, including changes to skills, roles, and career pathways, and creating new barriers or opportunities for women and other underrepresented groups

The responses to this call for evidence will be used to inform the Taskforce’s work and ensure policy recommendations are grounded in evidence and real insights from those in the sector. This report is structured as follows:

• an executive summary setting out the key findings and themes
• an overview of the methodology and respondent data
• a section-by-section summary of responses to each question

Executive summary

In March 2026, DSIT launched a call for evidence on what needs to change in the tech sector as it evolves to better support the entry, progression, and leadership of women. The call for evidence closed on 23 April and received 570 responses from members of the public, including:

• individuals working within the tech sector
• charities and non-profits
• big corporates
• senior leaders in tech
• students and trainees
• founders
• academics and researchers

The survey consisted of 9 open response questions and 19 closed questions. Respondents could provide the name of the organisation they represented, where relevant, but this information is for internal use only and will not be published. All other responses are anonymous.

Key insights

• The vast majority of respondents (95%) were women

• Respondents came from organisations of all sizes, with nearly half (47%) working in organisations of fewer than 10 employees, likely reflecting the high proportion of startups and early-stage companies in the tech sector
• Almost all respondents (95%) said emerging technologies are changing the skills required in their organisation or sector, with nearly two thirds (62%) saying this is happening to a great extent
• Nearly three quarters (73%) said these changes are already affecting who applies for and succeeds in tech roles

Across all the responses, we found clear themes raised by respondents:

1. Cultural and everyday practices disadvantage women and other underrepresented groups in tech, and change is long overdue
2. Emerging technologies are reshaping who can enter, progress and lead in tech, and without deliberate action, they risk entrenching existing structural barriers
3. Not everyone is benefitting from the skills pathways and training they need to reach their potential

Cultural and everyday practices disadvantage women and other underrepresented groups in tech, and change is long overdue.

Nearly three quarters of respondents (74%) agreed that improving team and organisational culture would support women’s entry, progression, and leadership in tech. This was the most commonly occurring theme across all questions.

Barriers begin at entry and persist throughout careers

Respondents noted that recruitment practices shaped by biased algorithms, limited feedback and network-driven hiring can reinforce exclusion before individuals reach the door. Once in the workforce, a number of respondents highlighted that they had encountered male-dominated cultures, as well as those that are at times hostile, including instances of microaggressions, discrimination and a lack of psychological safety. Respondents also highlighted that progression is further constrained by bias in promotion, pay and performance, and by unequal access to networks, sponsorship, and development opportunities.

Workplace structures penalise those who take career breaks

Respondents reported that the tech sector’s culture of continuous availability and rapid evolution of skills needed disproportionately penalises those who have taken career breaks, the majority of whom are women. Respondents also highlighted that inflexible structures and insufficient support at key life stages, such as caring responsibilities, parental leave, returning to work, compound this effect. 77.9% of respondents said interventions to support return-to-work transitions would improve retention.

Disadvantage is cumulative and intersectional

These challenges do not operate in isolation. Responses highlighted that individuals facing multiple disadvantages – related to ethnicity, disability, or socioeconomic background reported experiencing compounded barriers. Respondents also highlighted that rapid technological change risks widening existing inequalities further, as access to skills development and emerging opportunities remains uneven.

There is a growing pipeline that current systems are failing to retain

Despite this, respondents noted that AI is expanding the range of skills valued in the sector. Not just technical expertise, but capabilities like creativity, judgement, and ethical reasoning. This is drawing in talent from non-traditional routes – career switchers, returners, and self-taught individuals who many not have followed a conventional path into tech. The pipeline is growing, but respondents felt that systems and cultures are still designed around a narrow conception of how someone enters and progresses in the sector, and are not yet equipped to recognise or retain the broader range of people now arriving.

Addressing these challenges requires sustained, systemic change

Respondents highlighted that addressing these challenges means embedding inclusive practices across the full career lifecycle: creating workplaces where people feel able to speak up, tackling bias in recruitment and progression, supporting flexible and non-linear careers, and tailoring support to recognise those facing multiple forms of disadvantage experience barriers differently.

Emerging technologies are reshaping who can enter, progress and succeed in tech - but without deliberate action, they risk entrenching existing structural barriers

Emerging technologies are fundamentally changing the skills, roles and pathways required to succeed in tech, with implications for who can access and progress in the workforce with 84% of respondents saying that emerging technologies are leading to new or significantly changed roles in their organisation or sector.

The demand for AI skills is increasing, and entry level roles are declining

Respondents said that rapid advances in AI and automation are increasing demand for AI literacy, technical skills, and continuous upskilling, raising entry thresholds. At the same time, entry-level roles are declining or evolving, making it harder to gain the foundational experience needed to progress. The growing use of AI in recruitment is also introducing risks, including bias, reduced transparency, and challenges in demonstrating skills authentically.

Inequalities are being reinforced - not reduced

Respondents felt these shifts disproportionately impact women and underrepresented groups, who already face structural barriers to training, networks, and progression. Where career pathways are less defined and rely more on self-advocacy, visibility, and informal access to opportunity, those with greater social capital continue to benefit. This can widen the confidence gap, leaving many individuals with the necessary skills and potential - but without the support, sponsorship, or confidence to progress.

Progression into emerging roles is uneven

As new roles and hybrid skillsets emerge, access to these opportunities is not evenly distributed. This risks widening skills gaps and limiting progression into higher value and leadership roles.

There is a growing but under-supported talent pipeline

Some responses acknowledged that demand for cross-disciplinary and human skills- such as creativity, judgement and communication is increasing, alongside a more diverse pipeline of talent, including career switchers, returners, and non-traditional entrants. However, current systems and workplace structures are not yet designed to fully support or retain this talent.

Emerging technologies are at a critical juncture for inclusion

Responses highlighted that emerging technologies are acting as a force multiplier - with the potential to either expand access and diversity or deepen existing inequalities. Realising the opportunity will require more inclusive design across the system, including equitable access to skills, fair recruitment practices, and career pathways that support diverse and non-linear routes into and through the sector.

Not everyone is benefitting from the skills pathways and training they need to reach their potential

Access to training, upskilling and clear entry pathways is central to whether women and underrepresented groups can enter, progress and lead in tech. 74% of respondents agreed that increasing training and upskilling opportunities would support this.

Pipeline challenges start early and persist

Responses highlighted that barriers begin in the early pipeline, with limited exposure, low awareness of tech careers and entrenched stereotypes restricting participation. 80% of respondents identified school-stage interventions as most effective. Traditional, linear pathways also fail to support alternative routes into the sector.

Access to training remains unequal

Respondents felt that access to relevant, high-quality training is uneven, limiting entry and progression. Where provision exists, they felt it was often not sufficiently accessible, affordable, or aligned to need, contributing to persistent participation gaps.

Targeted interventions are key to unlocking access and progression

From their experiences, respondents said that practical programmes, such as bootcamps, apprenticeships, internships and returnships, can be highly effective in building skills, confidence, and progression, particularly when supported by financial assistance, such as help with travel costs.

Continuous upskilling is essential for retention and progression

Ongoing access to training across the career lifecycle is critical to enable progression. Without it, women and underrepresented groups are more likely to stagnate or leave the sector.

Flexible pathways remain underdeveloped

Some respondents said that non-traditional routes, including mid-career entry and returner pathways, are increasingly important but not consistently supported across the sector.

Training and reskilling are a system-wide lever for change

Overall, respondents agreed that training, upskilling, and pipeline development are key levers for improving diversity, but only where they are inclusive, flexible, and aligned to real career pathways. Delivering impact will require a joined-up, lifecycle approach - from early engagement through to progression into leadership.

Data collection

This call for evidence was comprised of:

• A digital (‘core’) survey on GOV.UK, open from 11 March to 23 April 2026
• A PDF version of the questions that some respondents used to respond via email from 11 March to 23 April 2026.

It was open to all to ensure a wide spectrum of perspectives are represented.

The core survey consisted of 10 open questions and 19 multiple choice questions.

The PDF version contained all questions in the core survey. Responses from the PDF survey have been combined with those of the core survey, to be analysed and presented together, as a single set of results.

All responses to this consultation have been considered as part of the analysis. A thematic analysis was conducted on all responses to identify key themes. For the purposes of this analytical summary, the team used a Government Artificial Intelligence (AI)-assisted tool, Consult, developed by the Incubator for Artificial Intelligence (i.AI) in DSIT, to support the identification and assignment of themes.

Consult identifies key themes from the responses to each question and maps each response against those themes, with policy experts reviewing the outputs at every stage. Themes generated by Consult were then subject to human-review and finalised by policy experts working on this call for evidence, who added, edited, and removed themes based on their subject matter expertise. These finalised themes were then used as the framework for mapping all responses in the dataset.

Methodological considerations

The findings in the report should be interpreted in the context of the methodology used. Participation in the call for evidence was voluntary, meaning respondents self-selected into the survey. The findings therefore reflect the views and experiences of those who chose to respond and are not intended to be statistically representative of the UK tech sector as a whole.

Responses are based on respondents’ self-reported experiences and perspectives submitted through the call for evidence and have not been independently verified. All demographic data is based on self-identification.

The identification and interpretation of themes involve analytical judgement. While all themes and their assignment to responses were reviewed and refined by policy officials, alternative interpretations of some qualitative responses may be possible.

Further information on response numbers, question routing and data completeness is provided in the ‘Notes on Data’ section.

Table 1: Call for evidence questions

Question	Options
1. Are you responding to this call for evidence as an individual or on behalf of an organisation?	- I am responding as an individual - I am responding on behalf of an organisation - I am responding both as an individual and on behalf of an organisation
2. Which of the following best describes your current role?	- Technical role (e.g. software engineer, data scientist, developer, architect) - Technical leadership role (e.g. lead engineer, principal, CTO) - Non technical role within the tech sector (e.g. product, policy, HR, operations) - Senior leadership or executive role - Research, academic, or education role - Student or trainee - Founder or co founder - Prefer not to say - Other (please specify)
3. Which best describes your current career stage?	- Student or pre-entry - Early career (e.g. junior roles, first few years) - Mid-career - Senior or leadership level - Later-stage career (e.g. 50+, reskilling, portfolio career) - Prefer not to say
4. How long have you worked in the tech sector, if at all?	- I have not worked in the tech sector - Less than 2 years - 2–5 years - 6–10 years - More than 10 years - Prefer not to say
5. Which of the following best describes your gender?	- Woman - Man - Nonbinary - Another gender identity (please specify)
6. Do you identify with any of the following groups?	Disabled or long-term health condition: - Yes - No - Prefer not to say From an ethnic minority background: - Yes - No - Prefer not to say From a socio economically disadvantaged background: - Yes - No - Prefer not to say Caring responsibilities (e.g. children, adults): - Yes - No - Prefer not to say
7. Which of the following best describes your organisation?	- Private sector business - Start up or scale up - Large enterprise - Public sector organisation - Charity or third sector organisation - Academic or research institution - Industry body or professional association - Investor or funder - Other (please specify)
8. Which of the following best describes your organisation’s primary focus?	- Software / digital services - Data, AI, or machine learning - Cyber security - Hardware, engineering, or manufacturing - Emerging technologies (e.g. AI, quantum, engineering biology) - Platform or infrastructure services - Education or training - Policy, regulation, or research - Other (please specify)
9. Approximately how many people does your organisation employ in the UK?	- Fewer than 10 - 10–49 - 50–249 - 250–999 - 1,000 or more - Don’t know / Prefer not to say
10. Which parts of the UK does your organisation’s experience primarily relate to?	- UK-wide - England - Scotland - Wales - Northern Ireland - Specific local or regional areas (please specify)
11. What is the name of your organisation?	Open
12. To what extent, if at all, are emerging technologies changing the skills required in your organisation or sector?	- To a great extent - To some extent - Hardly at all - Not at all - Don’t know
13. Please describe the specific changes you are seeing in the skills required in your organisation or sector as a result of emerging technologies.	Open
14. To what extent, if at all, are emerging technologies leading to new or significantly changed roles in your organisation or sector?	- To a great extent - To some extent - Hardly at all - Not at all - Don’t know
15. Please describe any new or significantly changed roles emerging in your organisation or sector due to emerging technologies.	Open
16. To what extent, if at all, are emerging technologies reshaping traditional career pathways in your organisation or sector?	- To a great extent - To some extent - Hardly at all - Not at all - Don’t know
17. Please describe the changes you are observing in career pathways in your organisation or sector.	Open
18. In your experience, to what extent are changes to skills, roles or career pathways due to emerging technologies affecting who applies for, or succeeds in, tech roles within your organisation or sector?	- To a great extent - To some extent - Hardly at all - Not at all - Don’t know - I have not seen changes to the skills, roles, or career pathways in my organisation or sector due to emerging technologies
19. Please describe the changes you are noticing in who applies for, or succeeds in, different tech roles? What do you think may be driving these changes?	Open
20. To what extent, if at all, have each of the following helped women and people from under-represented groups to enter, stay in, and progress in the tech sector?	Training or upskilling opportunities: - To a great extent - To some extent - Hardly at all - Not at all - Don’t know Team or organisational culture: - To a great extent - To some extent - Hardly at all - Not at all - Don’t know Access to leadership roles or decision-making spaces: - To a great extent - To some extent - Hardly at all - Not at all - Don’t know Funding or resources: - To a great extent - To some extent - Hardly at all - Not at all - Don’t know Policies or regulations (inside or outside organisations): - To a great extent - To some extent - Hardly at all - Not at all - Don’t know
21. At which stages in education or work do you think support is most important for helping under-represented groups?	- At school (e.g. subject choices, early exposure to tech) - Further education or training - Entering the tech sector for the first time - Early-career development - Moving into management for the first time - Progressing into senior leadership roles - Returning to work after time out - Experiencing major life or health transitions - Later-stage careers - Don’t know / None of these - Other (please specify)
22. Please tell us why you think these stages matter, and what contributes to barriers at these points.	Open
23. Which initiatives and interventions have helped under-represented groups develop and progress in their tech careers?	Open
24. Which initiatives and interventions have helped under-represented groups influence decisions or shape emerging technology areas?	Open
25. Which, if any, initiatives or interventions that have previously been used now feel less effective, and what alternatives would you suggest?	Open
26. Is there anything else that you would like to share to inform the work of the Women in Tech Taskforce?	Open

Responses to each question

Notes on data

The call for evidence received 570 submitted responses. This figure includes all respondents who answered at least one survey question and submitted their response. Partial responses (where respondents started but did not submit the survey) have been excluded from the analysis.

As many questions were optional or only shown based on previous responses, the number of respondents varies by question. For example, the first question was mandatory and therefore received 570 responses, whereas subsequent optional and conditional questions have lower response counts depending on whether respondents chose or were eligible to answer them.

Themes are not mutually exclusive and individual responses may be assigned to multiple themes. Percentages therefore indicate the proportion of responses associated with each theme and may total more than 100%.

Percentages presented in the thematic analysis tables have been rounded to the nearest whole number for ease of interpretation.

1.Are you responding to this call for evidence as an individual or on behalf of an organisation?

A total of 570 respondents answered this question.

Response	Percentage
I am responding as an individual	77.72%
I am responding on behalf of an organisation	6.67%
I am responding both as an individual and on behalf of an organisation	15.61%

2. Which of the following best describes your current role?

A total of 532 respondents answered this question.

Response	Percentage
Technical role (e.g. software engineer, data scientist, developer, architect)	20.86
Technical leadership role (e.g. lead engineer, principal, CTO)	12.41
Non-technical role within the tech sector (e.g. product, policy, HR, operations)	21.24
Senior leadership or executive role	15.98
Research, academic, or education role	8.83
Student or trainee	2.82
Founder or co-founder	8.27
Prefer not to say	1.50
Other (please specify)	8.08

3. Which best describes your current career stage?

A total of 532 respondents answered this question.

Response	Percent
Student or pre-entry	2.26%
Early career (e.g. junior roles, first few years)	8.83%
Mid-career	30.83%
Senior or leadership level	44.74%
Later-stage career (e.g. 50+, reskilling, portfolio career)	13.16%
Prefer not to say	0.19%

4. How long have you worked in the tech sector, if at all?

A total of 532 respondents answered this question.

Response	Percent
I have not worked in the tech sector	4.89%
Less than 2 years	7.71%
2–5 years	16.73%
6–10 years	16.73%
More than 10 years	53.57%
Prefer not to say	0.38%

5. Which of the following best describes your gender?

A total of 532 respondents answered this question.

Response	Percent
Woman	95.30%
Man	4.32%
Non-binary	0.00%
Another gender identity (please specify)	0.38%

6. Do you identify with any of the following groups?

A total of 532 respondents answered this question.

Response	Yes	No	Prefer not to say
Disabled or long-term health condition	19.55%	78.01%	2.44%
From an ethnic minority background	29.51%	69.55%	0.94%
From a socio-economically disadvantaged background	30.64%	65.60%	3.76%
Caring responsibilities (e.g. children, adults)	46.43%	51.32%	2.26%

7. Which of the following best describes your organisation?

A total of 129 respondents answered this question.

Response	Percent
Private sector business	27.13%
Start-up or scale-up	27.91%
Large enterprise	1.55%
Public sector organisation	6.98%
Charity or third sector organisation	13.95%
Academic or research institution	9.30%
Industry body or professional association	3.10%
Investor or funder	1.55%
Other (please specify)	8.53%

8. Which of the following best describes your organisation’s primary focus?

A total of 129 respondents answered this question.

Response	Percent
Software / digital services	34.88%
Data, AI, or machine learning	33.33%
Cyber security	13.95%
Hardware, engineering or manufacturing	8.53%
Emerging technologies (e.g. AI, quantum, engineering biology)	23.26%
Platform or infrastructure services	17.05%
Education or training	44.19%
Policy, regulation or research	16.28%
Other (please specify)	17.05%

9. Approximately how many people does your organisation employ in the UK?

A total of 129 respondents answered this question.

Response	Percent
Fewer than 10	47.29%
10–49	11.63%
50–249	10.08% 250–999
10.85% 1,000 or more	13.18%
Don’t know / Prefer not to say	6.98%

10. Which parts of the UK does your organisation’s experience primarily relate to?

A total of 570 respondents answered this question.

Response	Percent
UK-wide	72.87%
England	24.81%
Scotland	6.98%
Wales	3.10%
Northern Ireland	1.55%
Specific local or regional areas (please specify)	3.88%

11. What is the name of your organisation?

Responses to this question are not published.

12. To what extent, if at all, are emerging technologies changing the skills required in your organisation or sector?

A total of 567 respondents answered this question.

Response	Percent
To a great extent	61.90%
To some extent	32.63%
Hardly at all	3.53%
Not at all	0.35%
Don’t know	1.59%

13. Please describe the specific changes you are seeing in the skills required in your organisation or sector as a result of emerging technologies.

A total of 484 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
AI Driven Changes to Technical Skills and Ways of Working	Emerging technologies are reshaping both the technical skills required and how work is carried out. There is growing demand for AI literacy, data skills, and technical fluency, alongside an increasing need to work effectively with automation and AI enabled tools.	314	77%
Necessity of Continuous Learning and Adaptability	Rapid technological change requires ongoing reskilling, continuous learning, and adaptability, with individuals, employers and education providers needing to continuously develop new skills and approaches to remain relevant.	155	38%
Human Judgement, Critical Thinking, Leadership and Soft Skills	As AI and automation take on more routine tasks, greater value is being placed on human judgement, critical thinking, creativity, communication, empathy and the ability to interpret and challenge AI-generated outputs. Equally, leadership, strategic thinking, and change management skills are increasingly important for effectively implementing and managing technological transformation within organisations.	122	30%
Responsible, Ethical and Secure Use of Emerging Technologies	The adoption of emerging technologies is increasing the need for skills in AI governance, cybersecurity, risk management, ethics, digital safety and the responsible use of technology. Employees increasingly need to understand both the opportunities and limitations of AI enabled systems.	92	22%
Cross Disciplinary and Transferable Skills	Roles increasingly require people who can work across technical, business, policy, legal, ethical and operational domains, translating between specialist and non-specialist audiences and supporting effective technology adoption.	69	17%
Inclusive Access to Skills and Opportunities	The benefits of emerging technologies are not being experienced equally, highlighting the need for inclusive skills development, accessible training opportunities and targeted support for underrepresented groups, career changers and those facing barriers to participation.	69	17%
Job Displacement and Workforce Restructuring from AI and Automation	AI and automation are causing job displacement, restructuring, and increased market pressure, particularly affecting junior and repetitive roles and raising concerns about job security and career progression.	45	11%
Transformation of Education and Early Talent Development	The rise of emerging technologies is changing education and early talent development, necessitating new approaches to teaching, assessment, and curricula to equip students and educators with relevant digital and AI skills.	30	7%
Recruitment and Assessment Challenges from AI-Generated Content	Recruiters and assessors face new challenges in distinguishing genuine experience from AI-generated content and must adapt hiring practices to the realities of emerging technologies.	11	3%
No Reason Given	The response does not provide a substantive answer to the question.	7	2%
Other	A small number of responses raised workplace culture, wellbeing, and workload concerns, alongside sector-specific issues.	6	2%

14. To what extent, if at all, are emerging technologies leading to new or significantly changed roles in your organisation or sector?

A total of 566 respondents answered this question.

Response	Percent
To a great extent	39.75%
To some extent	44.17%
Hardly at all	11.66%
Not at all	1.24%
Don’t know	3.18%

15. Please describe any new or significantly changed roles emerging in your organisation or sector due to emerging technologies.

A total of 483 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Creation of AI, Data-Focused Roles and Upskilling.	Organisations are establishing new positions and teams dedicated to artificial intelligence and data, such as AI engineers, Chief AI Officers, AI product managers, prompt engineers, and data analysts, highlighting the growing importance of AI and data in business strategy and operations. For existing roles, the workforce must engage in ongoing learning and skill development to keep pace with changing technologies and evolving job requirements.	180	53%
Changing Skills for Traditional Roles	Traditional job roles are increasingly merging with AI responsibilities, leading to the creation of hybrid positions that demand broader skill sets and the ability to manage AI tools, including data scientist, software engineer roles, and copywriting.	144	43%
Changes in Employment Landscape - Job Displacement, Role Consolidation, and Recruitment Challenges Caused by AI	AI and automation are causing job losses, redundancies and fewer entry-level opportunities, particularly in administration. On the other end, organisations face difficulties in recruiting and training for new technology positions, including high-salary expectations.	86	25%
Emergence of AI Governance, Ethics, Safety, and Use Roles	New specialist positions are being created in AI governance, ethics, auditing, compliance, and responsible AI to address the ethical, regulatory, and safety challenges associated with AI adoption.	66	20%
Shifting Organisational Structures and Leadership	Leadership roles and organisational structures are evolving, with flatter hierarchies, new AI-focused leadership positions, and a stronger emphasis on agile, flexible, and innovative working methods. Senior staff are increasingly leading digital transformation and change management efforts.	49	15%
Increase in Digital Security Roles	There is a growing need for specialists to manage cybersecurity technological risks, enhance digital safety, and ensure system resilience.	36	11%
Other	Responses primarily related to sector-specific examples, education and training impacts, entrepreneurial and partnership-focused roles, and broader reflections on technological change.	21	6%
No Reason Given	The response does not provide a substantive answer to the question.	5	2%

16. To what extent, if at all, are emerging technologies reshaping traditional career pathways in your organisation or sector?

A total of 563 respondents answered this question.

Response	Percent
To a great extent	39.43%
To some extent	36.59%
Hardly at all	14.74%
Not at all	1.42%
Don’t know	7.82%

17. Please describe the changes you are observing in career pathways in your organisation or sector.

A total of 480 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Skills Development and Lifelong Learning	Rapid technological change is increasing demand for AI and technical skills, requiring continuous upskilling, reskilling and adaptation throughout careers.	142	48%
New and Changing Roles in an AI Enabled Workforce	Emerging technologies are creating new occupations and reshaping existing roles, changing the tasks, responsibilities and expertise required across the workforce.	126	42%
Entry Routes and Early Career Progression	Junior, graduate, apprenticeship and entry level routes are changing. There are higher expectations for new entrants and increasing challenges in gaining the foundational experience needed to progress in the early stages of a career.	107	36%
Changing Career Pathways	Career progression is becoming less linear and more flexible, with greater movement across disciplines, functions and sectors. Progression is increasingly shaped by skills, adaptability and varied experience rather than traditional hierarchical career ladders.	99	33%
Job Insecurity, Redundancy and Workforce Pressure	Technological change and automation are increasing uncertainty around job security, contributing to redundancies, workforce restructuring and changing employment patterns. These shifts are also creating pressure on employees to adapt quickly to evolving roles, skills requirements and ways of working.	61	20%
Exacerbated Diversity and Inclusion Challenges	The impact of technological change on women, minorities, and non-traditional entrants, including barriers to entry, progression, leadership opportunities, access to training and development. This is widening existing inequalities and worsening challenges.	47	16%
No Reason Given	The response does not provide a substantive answer to the question.	10	3%
Other	Responses highlighted a small number of sector-specific observations, including impacts on education, healthcare and specialist professional services, as well as concerns about fairness and access to progression opportunities.	7	2%

18. In your experience, to what extent are changes to skills, roles or career pathways due to emerging technologies affecting who applies for, or succeeds in, tech roles within your organisation or sector?

A total of 560 respondents answered this question.

Response	Percent
To a great extent	38.04%
To some extent	35.00%
Hardly at all	7.68%
Not at all	1.79%
Don’t know	10.89%
I have not seen changes to the skills, roles, or career pathways in my organisation or sector due to emerging technologies	6.61%

19. Please describe the changes you are noticing in who applies for, or succeeds in, different tech roles? What do you think may be driving these changes?

A total of 478 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
AI and Emerging Tech Skills Are Essential for Employment, Causing a Shift in Tech Roles	Employers place greater emphasis on AI literacy and emerging technology skills, raising entry thresholds and prioritising demonstrable, up-to-date technical abilities, leading some tech roles to become less relevant and creating new, high-demand positions in AI research and digital specialisms.	124	44%
Diversity and Inclusion Barriers Persist in Tech Recruitment, Especially Due to Use of AI	Underrepresented groups, including women, minorities, and older applicants, face significant and evolving barriers in tech recruitment (e.g. recruitment bias from AI, reduce personal feedback, and make it harder for some candidates to demonstrate their skills or stand out) and progression due to systemic bias, lack of networks, exclusionary job descriptions, and the impact of tech culture and AI tools.	113	40%
Employers Prioritise Practical and Soft Skills over Traditional Credentials, Reducing Entry-Level Positions	Adaptability, leadership, and practical experience are increasingly valued by employers compared to academic qualifications or technical specialism, which coupled with AI and automation, has decreased the number of junior tech positions, leading to increased competition and challenges for new entrants.	89	31%
More Applicants from Non-Traditional and Diverse Backgrounds Are Entering the Workforce	Despite the persistent barriers, more applicants from multidisciplinary, non-traditional, and diverse backgrounds including career switchers, self-taught individuals, and returners are increasingly entering tech roles.	57	20%
Economic, Social, Political and International Factors Reduce Diversity and Mobility	Personal connections and self-promotion increasingly influence success in tech roles. Economic challenges, policy changes, class-based inequalities, and increased overseas applications impact diversity and mobility in tech roles, with remote work and visa sponsorship further influencing applicant profiles.	43	15%
Other	These highlight challenges relating to training and career development, mismatches between role expectations and job descriptions and sector specific examples.	15	5%
No Reason Given	The response does not provide a substantive answer to the question.	8	3%

20. To what extent, if at all, have each of the following helped women and people from under-represented groups to enter, stay in, and progress in the tech sector?

• Training or upskilling opportunities: 563 respondents provided a response to this statement.
• Team or organisational culture: 560 respondents provided a response to this statement.
• Access to leadership roles or decision-making spaces: 563 respondents provided a response to this statement.
• Funding or resources: 561 respondents provided a response to this statement.
• Policies or regulations (inside or outside organisations):

562 respondents provided a response to this statement.

Response	To a great extent	To some extent	Hardly at all	Not at all	Don’t know
Training or upskilling opportunities	34.81%	39.25%	15.28%	5.68%	4.97%
Team or organisational culture	43.39%	30.71%	14.29%	7.14%	4.46%
Access to leadership roles or decision-making spaces	38.37%	29.48%	18.29%	7.82%	6.04%
Funding or resources	31.02%	30.66%	19.25%	8.73%	10.34%
Policies or regulations (inside or outside organisations)	21.89%	31.49%	26.51%	9.61%	10.50%

21. At which stages in education or work do you think support is most important for helping women and people from under-represented groups enter, stay in, and progress within the tech sector?

A total of 568 respondents answered this question. Respondents could select more than one option.

Response	Percent
At school (e.g. subject choices, early exposure to tech)	79.58%
Further education or training (college, apprenticeships, bootcamps)	61.80%
Entering the tech sector for the first time	67.08%
Early-career development	66.20%
Moving into management for the first time	51.94%
Progressing into senior leadership roles	61.80%
Returning to work after time out (parental leave, caring responsibilities, illness)	77.99%
Experiencing major life or health transitions (e.g. menopause, disability-related…)	56.87%
Later-stage careers	37.85%
Don’t know / None of these	0.88%
Other (please specify)	7.04%

22. Please tell us why you think these stages matter, and what contributes to women or people from under-represented groups facing barriers at these points.

A total of 390 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Workplace Culture	Hostile and male-dominated workplace cultures. Inadequate flexible working options and insufficient support in the workplace during life events, for carers or for returning parents. Persistent systemic, structural, and cultural issues -including racism, outdated workplace structures, financial barriers, and undervaluing of diversity - significantly hinder equitable opportunities for women and underrepresented groups (ethnicity, disability, or socioeconomic background) throughout their tech careers.	220	56%
Absence of Role Models, Mentorship, Networks or Skills Training	Limited access to skills training, upskilling, recognition of non-linear career paths, and support for career changers or returners restricts entry, retention, and advancement for women and underrepresented groups in tech (ethnicity, disability, or socioeconomic background). The lack of visible role models, mentorship, and access to professional networks undermines confidence, belonging, and career progression for women and underrepresented groups in tech.	216	55%
Impact of Early Education and Stereotypes	Early exposure to technology, positive reinforcement in education, and combating gender stereotypes and societal expectations are critical to encouraging girls and underrepresented groups (ethnicity, disability, or socioeconomic background) to pursue and persist in tech careers.	168	43%
Bias	Unconscious and explicit bias in recruitment, promotion, pay, and workplace interactions. Neurotypical, gender, and racial bias. This includes compounded intersectional disadvantages, where women and underrepresented groups facing additional disadvantages, such as ethnicity, disability, or socioeconomic background, experience compounded barriers that require intersectional approaches.	106	27%
Undervalued Diversity and Ineffective Diversity Initiatives	Diverse perspectives and representation are valuable for innovation and problem-solving in tech yet are often undervalued or overlooked in male-dominated environments. Diversity initiatives often lack effectiveness and accountability, highlighting the need for systemic policy and practice changes to ensure equitable opportunities and wellbeing for women and underrepresented groups at all career stages. Countries with higher female participation in tech offer models and lessons that the UK could adopt to improve gender and diversity outcomes.	43	11%
No Reason Given	The response does not provide a substantive answer to the question.	19	5%
Other	Responses highlighted the different barriers individuals may face at different life and career stages, the importance of transferable skills and career flexibility, and organisational challenges relating to communication, coordination, and implementation of support.	13	3%

23. Which initiatives and interventions, if any, have helped women and people from under‑represented groups develop and progress in their tech careers?

A total of 377 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Accessible Training and Career Support Increases Tech Diversity	Accessible, practical training programmes - including coding bootcamps, apprenticeships, internships, and returner initiatives - enable women and underrepresented groups to gain relevant skills and re-enter or progress in tech careers. So does training focused on building confidence, communication, self-advocacy. Remote options help reach wider audiences. Offering financial support through grants, scholarships, subsidised training, and access to resources such as devices and internet reduces barriers to participation and make support more accessible.	193	51%
Sponsorship, Mentorship, and Visible Role Models Help Advance Women and Underrepresented Groups	Mentoring, sponsorship, and visible role models - especially from underrepresented groups in leadership - are crucial for supporting, inspiring, and advancing women and underrepresented groups in tech careers.	165	44%
Networks and Peer Support Foster Belonging	Participation in networking groups, community organisations, peer-led networks, and professional societies provides support, learning opportunities, and a sense of belonging that fosters career advancement for women and underrepresented groups.	125	33%
Organisational and Leadership Culture Enable Inclusion	Sustained organisational culture change, leadership commitment, and accountability for diversity and inclusion are essential for creating environments where women and underrepresented groups can thrive. Culture needs to provide psychological safety, equal respect and be free from microaggressions, bullying, and harassment, and help employees recognise bias.	96	26%
Flexible Working and Family Support Retain Talent	Flexible and remote working arrangements, including job-sharing, family-friendly policies, parental leave for both parents, returnerships, and support for those with caring responsibilities are essential for retaining and enabling career progression for women and underrepresented groups.	80	21%
Inclusive Recruitment, Transparent Hiring, and Promotion Practices Increases Diversity	Proactive company policies, targeted recruitment, quotas, and transparent hiring and promotion practices are necessary to create equal opportunities and increase diversity in tech. This includes sourcing candidate from alternative pathways like returnerships and apprenticeships.	68	18%
Early Outreach to Young People Encourages Tech Careers	Early engagement through school-based initiatives, coding clubs, STEM ambassadors, and exposure to tech careers encourages young women and underrepresented groups to consider and pursue tech careers.	62	16%
Intentionally Intersectional Initiatives Address Unique Challenges	Programmes specifically designed for subgroups within underrepresented communities, including black women, minorities, and economically disadvantaged groups, address unique challenges and foster inclusion.	32	9%
Supporting Male Allyship Promotes Equity	Training focused specifically on male allyship helps women and underrepresented groups progress in tech careers and fosters equity and inclusion.	10	3%
No Reason Given	The response does not provide a substantive answer to the question.	29	8%
Other	This category focused on the need for practical support and opportunities, recognition of effective industry-led initiatives, support for mid-career professionals, and access to appropriate workplace resources.	8	2%

24. Which initiatives and interventions, if any, have helped women and people from under-represented groups influence decisions or shape emerging technology areas?

A total of 307 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Diverse Representation in Leadership and Decision Making	Underrepresentation of women and other underrepresented groups in senior leadership, executive roles, boards, advisory groups, and decision-making forums. Barriers to accessing leadership positions, lack of diverse voices in governance, and limited influence over strategic direction.	123	40%
Mentoring, Networks, Training and Visible Role Models	Mentoring programmes, sponsorship relationships, peer networks, and community-based support that help women and underrepresented groups navigate careers, build confidence, and access opportunities. Including formal schemes (e.g. employer-led mentoring, sponsorship programmes) and informal or grassroots networks. Accessible networking opportunities, visibility of role models, and communities of practice (e.g. across AI, data, design, ethics) that enable knowledge-sharing, collaboration, and safe spaces for experimentation and peer support.	107	35%
Inclusive Culture and Equitable Workplaces	Workplace cultures and policies that are inclusive, equitable, and supportive. Zero tolerance for bias and harassment, manager and staff training on recognising and addressing bias, and policies for flexible working and career breaks that help retain and advance diverse talent. Male allyship, investment in equitable practices. Transparent diversity targets to remove barriers. Intersectional approaches, ensuring initiatives support those facing multiple barriers (e.g. women of colour, parents, people with disabilities).	73	24%
Education, Training and Skills Development	Accessible, high-quality training and development opportunities for women and underrepresented groups at every career stage, including technical skills and broader confidence, leadership and business skills. STEM education and advanced technical training (for example in AI and emerging technologies), and wraparound learning in areas like negotiation, communication and financial acumen that empower individuals to thrive in business.	47	15%
Targeted Funding to Increase Access for Underrepresented Groups	Targeted funding, grants, and support for female-led startups and diverse tech initiatives enhance access and influence, though further support is often needed.	29	9%
No Reason Given	The response does not provide a substantive answer to the question.	85	28%
Other	Responses highlighted the role of government and regulatory action, organisation-wide approaches to inclusion, and the importance of influence and stakeholder engagement. Some respondents also raised concerns about bias within AI systems themselves.	14	5%

25. Which, if any, initiatives or interventions that have previously been used now feel less effective as the tech sector changes, and what changes or alternatives would you suggest?

A total of 266 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Symbolic Diversity Initiatives Lack Lasting Impact	Short-term, compliance-driven diversity interventions - such as one-off awareness campaigns, unconscious bias training, and diversity pledges - are widely seen as ineffective in addressing systemic barriers and driving sustained cultural or structural change in the tech sector. Traditional one-off diversity training and compliance led initiatives are increasingly insufficient on their own.	88	33%
Traditional Education Pathways are Outdated	University degrees, graduate schemes, coding bootcamps, and generic training are increasingly viewed as insufficiently aligned with current tech sector requirements, especially with the rise of AI and automation.	70	26%
Mentoring and Sponsorship Require Reform	Existing mentoring, internal women’s groups, and networking events are often seen as echo chambers or insufficient, prompting a need for structured sponsorship, clear progression opportunities, and broader support beyond affected groups.	68	26%
Leadership and Lack of Diversity in Decision-Making Continues to Hinder Inclusion	Persistent all-male leadership and underrepresentation in design and product development continue to impede inclusion in tech.	65	24%
Insufficient Support for Women Returners, Parents, and Carers	Existing interventions often fail to provide adequate support for women returners, working parents, and carers, highlighting the need for funded childcare, flexible working, and targeted reskilling.	42	16%
No Reason Given	The response does not provide a substantive answer to the question.	53	20%
Other	Responses focused on government action, accessibility and support for disadvantaged groups, more participatory approaches to engagement, concerns about AI bias, and the importance of recognising and valuing women’s contributions.	29	11%

26. Is there anything else that you would like to share to inform the work of the Women in Tech Taskforce?

A total of 260 respondents answered this question.

The table below summarises the key themes identified from responses to this question, alongside the number and proportion of responses associated with each theme.

Theme Name	Theme Description (From Responses)	Mentions	Percentage
Career Entry Pathways, Progression, Promotion and Visible Representation	Improved communication, recruitment practices, and visibility are essential to address barriers related to access and awareness for women pursuing tech careers. Structured support, grants, and recognition of non-traditional, interdisciplinary, and midlife routes into tech are vital for women changing careers, returning after breaks, or entering through alternative pathways. Removing barriers to promotion, lack of women in leadership, glass ceiling, lack of sponsorship, visibility, and governance representation.	102	39%
Culture and Discrimination	Unconscious bias, discrimination, sexism, gender pay gap, exclusionary or male-dominated cultures, lack of psychological safety, inappropriate behaviour, or leadership failing to act on inequality.	66	25%
Intersectionality	Efforts must prioritise intersectionality and true inclusion by addressing the needs of underrepresented groups - including older women, neurodivergent women, women from diverse backgrounds, and those from different regions - and ensuring their representation in the tech sector and Taskforce.	64	25%
Education Pipeline, Early Engagement and Awareness of Tech Careers	School experiences, girls in STEM, teacher capability, curriculum, role models, outreach, and awareness of tech careers.	50	19%
Structural Interventions and Funding	Funding gaps, grants, investment, support for female founders, government policy, quotas, and regulatory interventions.	38	15%
Flexible Working and Caring Responsibilities	Flexible working (hours, location), parental leave, childcare, elder care, return-to-work support, retention challenges, and career breaks.	34	13%
Male Allyship and Shared Responsibility	Achieving gender equality in tech requires active male allyship, shared responsibility, and accountability from those in power to foster diversity and drive change.	12	5%
No Reason Given	The response does not provide a substantive answer to the question.	43	17%
Other	Responses focused on the wider impacts of technology on society and the workforce, the value of soft and transferable skills, collaboration with community organisations, and ensuring technology is used to address real-world challenges.	26	10%

Conclusion

This call for evidence received 570 submitted responses from across the UK tech sector, including individuals in technical and leadership roles, founders, academics, students, charities and organisations.

Together the responses provide a valuable evidence base of the barriers affecting the entry, progression and leadership of women and other underrepresented groups in tech, alongside the opportunities and challenges presented by emerging technologies.

Across the responses, participants consistently identified the need for action across the career lifecycle, including improving access to skills and training, creating more inclusive workplace cultures, supporting flexible and non-linear career pathways, and ensuring that the opportunities within the sector are accessible to all.

The evidence gathered will inform the ongoing work of the Women in Tech Taskforce and contribute to a stronger understanding of the experiences and priorities of those working across the UK tech sector.

1. 1 Dealroom, UK innovation 2025 review, January 2026. $ to £ conversion is based the Jan 2026 mid-market exchange ↩

2. GCSE Computing entries dip but gender gap continues to narrow ↩

3. Time-series - A level subject entries and grade by gender ↩

4. Time-series - A level subject entries and grade by gender ↩

5. WeAreTechWomen - Lovelace report Unlocking £23.5 Billion: The Value Of Keeping Women In Tech, July 2025 ↩

6. Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval ↩

7. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023. ↩

8. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023
   University Of Washington Gender, Race, and Intersectional Bias in Resume Screening via Language Model 2024. ↩

9. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023. ↩

10. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023. ↩

11. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023
    University College London Research published in BMJ Health & Care Informatics 2022. ↩

12. Tech Talent Charter, Diversity in Tech 2024, based on data collected in 2023. ↩

13. University College London Research published in BMJ Health & Care Informatics 2022. ↩