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The available Pakistan-specific figures do not tell us how many women build AI. The Ministry of IT and Telecom reported that women made up 29% of Pakistan’s IT workforce, but that figure covers IT broadly, not AI roles. It is evidence of women’s presence in the wider technology sector—not an answer to how many women are developing, researching, deploying or governing AI in Pakistan.
There are signs of institutional activity, including a national Gender-Responsive AI School launched in July 2026. But a launch and a set of training pathways are not yet evidence of who completes the program, enters AI work or advances in it. The honest picture is that Pakistan has some broad workforce indicators and emerging initiatives, while the AI-specific workforce remains uncounted in the cited material.
What do we know about women in Pakistan’s technology workforce?
In a release dated 8 March 2025, Pakistan’s Ministry of IT and Telecom said women were 29% of the country’s IT workforce and 20% of professionals in Software Technology Parks (STPs). The release does not state the figures’ measurement period or methodology. They should therefore be treated as ministry-reported indicators, not as a census or a measure of AI employment.
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The distinction matters because IT includes many occupations beyond AI. A broad workforce share cannot establish women’s representation among machine-learning engineers, AI researchers, data scientists, product teams or people responsible for AI governance. Nor does it show how representation varies by seniority, pay or retention.
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Women-led startups are a separate indicator
The same ministry release said 30% of startups incubated by National Incubation Centers “last year” were women-led and described a requirement that at least 25% of founders be women. “Last year” is relative to the March 2025 release; the statement does not specify the reporting period more precisely. The reported share and the requirement are different measures, and neither tells us what share of AI startups are women-led. These are ministry claims, not independently assessed outcomes in the cited material.
Why is the AI-specific picture hard to see?
Counting “women in AI” depends on what counts as AI work. A narrow count might include people who develop models or conduct AI research. A wider one could include data and software roles, product development, deployment, risk assessment, policy and public-sector oversight. Without a stated definition and consistent occupation-level data, percentages from different sources may not be comparable.
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The evidence cited for Pakistan does not establish the number or share of women in its AI workforce, their distribution across technical and non-technical roles, their seniority, or their pay and retention patterns. It also does not document barriers through interviews with women working in Pakistan’s AI sector. Those are unanswered questions, not proof that women are absent or that any particular barrier is dominant.
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What is Pakistan doing to bring gender into AI?
A national Gender-Responsive AI School
In July 2026, Pakistan’s Ministry of IT and Telecom, UN Women Pakistan and KOICA launched the Gender-Responsive AI School Pakistan. The stated learning pathways cover AI foundations; gender-responsive and ethical AI; governance; prompt engineering; AI agents; and public administration. UN Women Pakistan’s representative described the initiative as a national Training of Trainers program with tailored pathways for government branches, civil society and the private sector.
The launch establishes that a program exists and identifies what it intends to teach. The cited announcement does not establish its long-term reach or results: it does not show how many people complete the training, whether participants gain AI roles or influence policy, or whether outcomes differ by gender or sector.
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UN Women and the United Nations in Pakistan also reported that a regional initiative had trained more than 5,000 policymakers, UN personnel, civil-society leaders and young innovators since 2024. That is a regional initiative figure, not a count of people trained by Pakistan’s new national school.
A broader digital inclusion strategy
UNESCO reported that the Ministry of IT and Telecom launched a Digital Gender Inclusion Strategy at the Digital Nation Summit in August 2024, following work with the Pakistan Telecommunication Authority. This documents a strategy and collaboration; the cited account does not quantify changes in women’s digital access, employment or AI participation resulting from it.
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How does AI policy connect to women’s participation?
UNESCO’s account of a May 2025 policy dialogue said Pakistan’s draft national AI policy had five pillars: AI Innovation Ecosystem; Awareness & Readiness; Secure AI Ecosystem; Transformation & Evolution; and International Cooperation and Collaboration. The dialogue focused on the Secure AI Ecosystem pillar, with participants calling for transparency, inclusion, rights protections, coordination and institutional capacity, including attention to vulnerable communities.
That account describes the draft and discussion at the time; it does not establish the policy’s later adoption or current status. The substantive point is that participation is not only a question of technical training. Decisions about safety, data, rights and public-sector use can shape whose needs AI systems address and who has influence over their design and oversight. The cited dialogue records priorities voiced by participants, not proof that those priorities have since been implemented.
What evidence would answer “where are the women building it?”
A useful answer requires Pakistan-specific evidence that separates AI from the larger IT sector and makes the population being counted clear. That means more than a single national percentage.
- Define the work: distinguish AI research and model development from adjacent software, data, product, deployment and governance roles.
- Show the workforce structure: report women’s representation by occupation, seniority, sector and employer type, with the date, method and coverage stated.
- Track pathways and retention: connect education and training to hiring, career progression, pay and continued employment rather than counting enrollment alone.
- Measure initiatives over time: report who participates in programs such as the AI School, who completes them, and what happens afterward, without conflating announced goals with outcomes.
- Include women’s accounts: interviews and other direct evidence can identify barriers and differences that aggregate workforce figures cannot explain.
UNESCO’s 2026 South Asia Outlook Study illustrates why regional findings need careful labeling: it uses education and labour-force statistics, bibliometric analysis, LinkedIn Economic Graph data and interviews, but covers Bangladesh, Bhutan, India, Maldives, Nepal and Sri Lanka—not Pakistan. Its conclusions cannot substitute for country-level evidence about Pakistani women.
There is also a useful framework for examining AI’s effects on women’s working lives: job requirements, hiring, career progression and workplace upskilling. UNESCO, the Inter-American Development Bank and the OECD used these dimensions in 2022. They help organize questions for Pakistan-specific research, but they are not findings about Pakistan’s AI workforce.
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