AI, Skills, and Gender: Why Women Must Be at the Centre of the Economic Revolution happening now.
AI is not on the horizon — it is here, transforming economies and reshaping work at unprecedented speed. From predictive healthcare to generative design, AI is altering not only which jobs exist but the skills required to thrive. Governments are scrambling to respond, and recent developments on both sides of the Atlantic highlight the urgency:
In the UK, Skills England was launched in July 2024 and placed within the Department for Work and Pensions (DWP) in September 2025, taking over responsibility for apprenticeships, adult education, and training from the Department for Education. Under-19 education remains with DfE.
Days later, the US and UK signed a £31 billion “Tech Prosperity Deal”, covering AI, quantum, nuclear, and advanced infrastructure, with formal agreements on AI safety and shared testing.
On the surface, these look like major steps forward. But without deliberate intervention, these changes risk reinforcing existing gender and regional inequalities. For women — especially those already underrepresented in tech — this is not just a policy debate. It is an emergency.
The Risks: Policy Fragmentation and Gender Gaps
Fragmentation in the UK Skills System
Shifting adult skills policy into DWP may improve links between training and employment, but it risks creating gaps:
Split accountability: Under-19 learners fall under DfE, adults under DWP. Women re-entering the workforce after career breaks — typically over 19 — may struggle to navigate between departments, losing support in transition.
Funding decline: Since 2010, adult education budgets in England have been cut by 28% per learner in real terms. Participation has fallen by almost half: from 2.2m adult learners in 2010–11 to 1.2m in 2022–23. Cuts hit women hardest, especially those in low-income households and regions with limited provision.
Regional divides: A 2025 Guardian report warns that by 2035, 71% of Londoners will hold a degree, compared with just 29% in Hull & East Yorkshire. This “skills chasm” is most punishing for women, who face additional childcare and transport barriers in lower-qualification regions.
Employer under-investment: UK employer spending on training per employee is around half the EU average, leaving workers reliant on patchy public provision. Without regulation or incentives, women often in part-time roles are the least likely to be offered employer-funded upskilling.
Gender and AI Disruption
At the same time, the AI revolution is re-ordering labour markets:
Women hold 70% of administrative roles in the UK — roles most vulnerable to automation.
Women make up just 21% of UK tech teams, and one in three plan to leave due to poor progression and culture.
Globally, McKinsey estimates 45 million women’s jobs are at risk of displacement by 2030 unless they transition into higher-tech roles.
Unless training is designed to be flexible, affordable, and inclusive, women will be pushed out of the future economy just as AI wealth and influence peaks.
The Opportunity: Deglobalisation as a Gendered Advantage
Deglobalisation — the shift from long global supply chains to more regionalised, resilient, and localised workforces — is often framed as a risk. But for women and African economies, it can be an opportunity.
Youth and cost advantage: Africa’s population is the youngest in the world, with 75% under 35. Labour costs remain significantly lower than in the Global North, positioning African women as a cost-efficient yet capable digital workforce if upskilled for AI-enabled roles.
Remote and digital services: As firms seek resilience, they are turning to remote-capable, distributed teams. With the right digital infrastructure, African women could provide AI services, cloud support, data annotation, and software delivery at globally competitive rates.
Leapfrogging legacy systems: Freed from legacy tech systems, African economies can build inclusive digital public infrastructure — AI tuned to local languages, fintech for unbanked populations, and platforms designed for gender equity from the start.
Policy freedom: Emerging economies have more flexibility to legislate inclusively. Embedding gender equity in AI regulation — for example, mandating disaggregated data and bias testing — is easier to implement early.
In short: while deglobalisation pressures richer economies to localise, it creates space for women and African talent to enter global value chains as a credible, affordable, and efficient alternative workforce.
Why Niyo Labs Is a Scalable Solution
To bridge the risks and capture the opportunities, solutions must be gender-aware, outcomes-driven, and globally connected. Niyo Labs embodies this model.
Women-first programmes: Initiatives like SheBuilds (a virtual accelerator for women building tech products) and ElevateHER (a mentoring scheme with partners like Northrop Grumman) directly target the gender gap.
Flexible delivery: Remote and hybrid bootcamps, gamified and rewards based modular learning, and tailored mentorship make training accessible for women balancing work and caregiving.
AI-aligned curriculum: Certified courses in AI, data, cloud, and software engineering are directly linked to growth sectors.
Global partnerships: Backed by partnerships with Microsoft, Goldman Sachs, and UK public frameworks like G-Cloud, Niyo Labs has the credibility to scale.
Ambitious targets: With a goal to upskill 1 million people — and evidence of 90%+ progression into jobs or self-employment — it connects learning to real economic mobility.
Crucially, Niyo Labs straddles both UK and African markets. This positions it to help the UK close its gender and regional gaps, while also unlocking Africa’s youthful workforce for AI-enabled global demand.
A Call to Action
The restructuring of UK skills policy and the US-UK AI pact must not be treated as neutral bureaucratic or diplomatic milestones. They are fault lines along which inequality could deepen. For women, and especially for African women, the stakes are existential.
But the same shifts also open unprecedented opportunities: new funding, new frameworks, new supply chains. The question is whether women will be systematically included — or systematically left behind.
Niyo Labs proves that inclusive, scalable, AI-aligned training is possible. Governments and investors now face a choice: either double down on infrastructure without people, or channel resources into platforms that ensure women — half the population — are part of the AI economy.
Because if women are excluded, AI will not be progress. It will be regression with faster processors.
