AI, women and the gender gap in Singapore
Singapore is aggressively pursuing AI leadership, with PM Lawrence Wong’s Budget 2026 initiatives — including a National AI Council, better AI literacy in education, and SkillsFuture incentives like free premium AI subscriptions — aiming to capture major economic gains from projected global job creation and regional investment.
However, a Nineby9 report warns of a widening AI gender gap in Singapore and the region. Women face “double exposure”: they hold more jobs vulnerable to AI displacement (e.g., administrative and service roles — 33.8% of disrupted jobs are held by women vs. 28.8% by men, per LinkedIn data), while remaining heavily underrepresented in AI-technical, augmented, and decision-making roles (only ~29% globally).
Unlike the slower-building STEM gender gap (~35% women in Singapore’s STEM workforce), AI’s rapid spread affects most white-collar sectors, risking faster exclusion. Gen Z women are especially vulnerable, with fewer entry-level stepping stones and lower AI training rates.
Leaders interviewed highlight key issues and solutions:
Women often adopt cautious, thorough approaches to AI experimentation, which can be undervalued in speed-rewarding cultures — though these traits may become strengths as AI matures into governance and reliability phases.
Optional, after-hours upskilling disadvantages women with caregiving responsibilities.
Structural fixes needed: integrate training into work hours, build internal AI communities, offer psychological safety, and — crucially — provide active sponsorship (senior leaders advocating for women in high-visibility AI projects) rather than just mentorship.
Positively, current generative AI tools lower technical barriers, enabling non-technical women (e.g., educators, business owners) to automate routine tasks, boost productivity, and focus on human-centric work — potentially leveling some playing fields when embraced boldly.
While official data shows no clear disproportionate employment impact on women yet, forward-looking risks include slower career progression, reduced visibility in digital leadership, and less influence over how AI is shaped and deployed.
Singapore’s AI ambitions will only fully succeed if inclusion is deliberate: embedding equitable reskilling, sponsorship, and diverse voices in national strategy and company practice. If addressed proactively, AI could narrow — rather than widen — gender inequalities. If ignored, it risks entrenching them at unprecedented speed.







