
How to close the great divide in a rewired world
Learn strategies for leadership in a post-traditional era, focusing on responsibility, transparent communication, and understanding public sentiment...
Audio available

Artificial intelligence is the most significant technological shift of this century, and it is already a mirror of the bias entrenched across business and society. Beneath the headline lower adoption numbers sits a more nuanced picture. Women are not disengaged from AI. They are approaching it with rational caution, shaped by documented experience of harm, structural disadvantage, and institutional indifference.
The consequences are measurable: women leaving education, losing employment, withdrawing from public life, and exiting political leadership. Each loss narrows the pool of women shaping the AI systems that will govern the next generation. This is not a diversity issue at the margins. It is a governance failure and a strategic business risk. The central challenge is not competence. It is trust. Reverse that, and AI becomes the largest leadership opportunity women have had in generations.
We have united with Media Trust and Code For Good Now to launch the Closing the AI Gender Gap initiative, bringing together research and cross-sector collaboration to make AI worthy of the trust it asks for. We are inviting organizations, policymakers, and educators to join us to ensure the systems shaping our future are inclusive, trusted, and resilient.
This initiative will succeed with collective actions: adoption of a shared measurement standard for the AI gender gap, accountable disclosure of AI workforce diversity, and procurement aligned to move the market faster than regulation can.
Women are grossly underrepresented in both AI development and use. It's time to reframe the AI gender gap.
In terms of women's share of the AI workforce, they hold just 14% of AI executive roles and 18% of AI research positions.
Â
Among women with high digital literacy, the gender gap in AI use widens to more than 45 percentage points.Â
Â
Google's AI Works pilot found a few hours of training roughly doubled daily AI use and tripled weekly use among women over 50.
Â
Closing the AI gender gap requires making AI worthy of our trust, making its use safe and evenly judged, building fluency on that foundation, and finally acting together to hold the wider market to the same standard.
1. Build trustworthy AI and govern it as a shared responsibility. Treat fairness as a dimension of product quality and a leadership accountability, not a module bolted on at the end or a task quietly delegated to the women in the room.
2. Create the cultural conditions for safe and consistent use. Grant explicit permission to use AI, apply judgment evenly regardless of gender, and have leaders model their own mistakes openly. The environment drives the gap, not the individual.
3. Build capability as fluency in service of judgment. Women’s caution reflects judgment, not ignorance. The aim is to give them the fluency to act on what they already know, not to remediate a deficit that is not there.
4. Scale through collaboration and convene the standard. Align as a coalition of buyers, benchmark against a shared metric, and connect education, industry, and policy around a single standard of accountability.
Inaction carries a double cost: what organizations absorb, and what they forgo. A leaking talent pipeline drains institutional knowledge and leaves technical roles unfilled. Between 40,000 and 60,000 women leave the UK tech sector each year, at an estimated cost of up to £3.5bn annually. West Africa has lost an estimated $18.4bn in GDP to women’s exclusion from digital spaces. Meanwhile, doubling women’s participation in European tech could unlock €260 to 600bn in GDP gains.
The barrier is one we built, which means it is one we can remove. Early action costs far less than reactive remediation once these patterns harden into infrastructure.

Chief Innovation Officer, IMD

CEO , Media Trust

Founder, Code for Good Now

Professor of Strategy and Digital and Director of the Global Center for Digital and AI Transformation, IMD

3 hours ago • by Christine Graeff in AI Adoption
Learn strategies for leadership in a post-traditional era, focusing on responsibility, transparent communication, and understanding public sentiment...

April 24, 2026 in AI Adoption
HubSpot CPO Helen Russell says future-ready leaders must upskill for AI, stay close to operations, think like founders, and build trusted hybrid teams....

March 11, 2026 • by Heather Cairns-Lee in AI Adoption
AI may become one of the most significant leadership opportunities for women in decades. Its impact will depend on how capability, governance, and leadership are built around it....

To reap the promise of AI, leaders need to get the humans on board. In Issue 22 of I by IMD, explore the critical leadership challenge of AI transformation.
Â
Explore first person business intelligence from top minds curated for a global executive audience