AI readiness means women don’t just use systems. They build them too

• Women’s AI readiness requires more than just access to tools; it necessitates active roles in the design, deployment, and governance of AI systems.
• Persistent structural barriers, including unequal access to digital infrastructure and social norms, limit women's participation in the AI ecosystem.
• Achieving true inclusivity requires developing critical thinking skills alongside technical proficiency to navigate risks like AI hallucinations.
• Despite increasing entry-level participation, women remain significantly underrepresented in leadership and C-suite roles.

Access and Structural Barriers

• Digital inequality starts at the household level, where resources like laptops are often prioritized for male family members.
• The 2025 GSMA Mobile Gender Gap Report indicates that South Asia and Sub-Saharan Africa account for roughly 60 percent of the 885 million women worldwide who remain unconnected.
• Rural populations face greater exclusion than urban ones, creating a geographical disparity that hinders broad-based AI education and career entry.

Beyond Technical Skills

• Education must balance technical training with foundational skills like reasoning and adaptability to manage AI’s tendency to produce inaccuracies or "hallucinations."
• Critical thinking is essential for professionals to validate AI outputs, as demonstrated by legal challenges involving fictitious AI-generated case citations in the US and India.
• Educational institutions should focus on teaching independent inquiry, as technological tools evolve rapidly and may render specific technical training obsolete within a few years.

Leadership and Inclusion

• While women represent 31 percent of new AI roles in India and 35 percent of entry-level positions, they hold only 23 percent of leadership roles and 17 percent of C-suite positions.
• Gender-balanced teams are more effective at identifying biases and considering diverse perspectives during AI development.
• Moving beyond simple representation to active leadership is vital for building AI systems that are responsible, fair, and representative of the global society.