How AI Can Make Hiring and Promotion Fairer for Women

Women account for 42% of the financial services workforce, yet remain underrepresented in senior roles.

A joint paper from Nationwide, Bain & Company and Cambridge Judge Business School argues that responsible AI can help close the gap by reshaping recruitment, progression and leadership.

The authors contend that AI can be used to reduce underrepresentation, not reinforce existing inequalities across the sector.

AI as a leadership choice

Dame Debbie Crosbie, Chief Executive of Nationwide Bank and Women in Finance Champion, says: “AI is not just a technology choice for financial services, it is a leadership choice. 

“Used well, it can help make recruitment and progression fairer, widen access to opportunity, and shine a light on talent that might otherwise be overlooked.”

Only 8% of FTSE 350 CEOs are women, despite women holding 36% of leadership roles, according to the paper. The authors set out practical steps to make hiring and promotion criteria consistent, measurable and auditable.

Standardising decision-making, improving transparency and using explainable models can help firms identify and advance overlooked talent. This is presented as leadership work, not just a technology project.

The paper argues firms that link AI initiatives to clear inclusion goals are better placed to deliver fairer outcomes. It also stresses the need for leadership accountability and visible metrics.

Automation risk and the adoption gap

The research examines how automation affects roles by gender. In high-earning countries, 3.5% of male employment is at high risk of automation, compared with 9.6% for female employment.

Engagement with AI is also uneven. Men are more likely to experiment informally with Gen AI, while many women hesitate to adopt these tools.

Feryal Erhun, Professor of Operations and Technology Management and Academic Director of the Wo+Men’s Leadership Centre at Cambridge Judge Business School, says: “As AI and automation accelerate, there is a real risk that women will be disproportionately disadvantaged, but there is also a genuine strategic opportunity to reset long-standing structural inequalities.

“That is precisely why this research matters. The question is how to ensure that women are the architects and governors of AI in financial services.

“Our aim is that this work provides institutions with a practical blueprint for ensuring AI becomes a force that closes, rather than widens, the gender gap in financial services and provides actionable insights.” 

The paper encourages targeted training, access to tools and sponsorship to close the engagement gap.

UK regulation and sector momentum

The paper highlights the Women in Finance Charter and the UK’s emerging, principles-based approach to AI regulation as a powerful combination. This mix is presented as a model that supports adoption with trust.

The authors argue that the UK is well placed to encourage peers in the US and EU to adopt governance, which couples innovation with accountability. Strong board representation, combined with robust oversight, can accelerate progress.

Nishma Gosrani, Partner at Bain & Company, says: “The pace of change in financial services is unlike anything we have seen. Agentic AI is no longer confined to back office automation; it is moving into the front office, becoming the first touchpoint with customers and reshaping the roles of advisers, underwriters and relationship managers.

“Yet only a small fraction of firms have truly embedded it into how they operate, and fewer still can evidence the value. Closing that gap demands rigour and governance, not just ambition. Get it right and AI becomes a source of trust. Get it wrong and it becomes a liability.”

Firms which embed rigour in model development, testing and oversight can turn AI into a source of trust with customers and colleagues. Those that do not risk compounding bias and eroding confidence.

What boards should do now

Leaders should decide where AI can make recruitment, assessment and progression measurably fairer, and test outcomes by gender. Clear standards and regular audits can evidence progress.

They should map roles with the highest automation risk, and invest in reskilling and redeployment plans that protect women equitably. Workforce planning must be data-led and transparent.

Organisations should close the engagement gap by giving women access to tools, training and stretch assignments as designers, users and governors of AI. Sponsorship and mentoring remain critical.

Boards should build governance with clear data controls, auditability and accountability that reduce bias and build trust. Firms should report progress openly to colleagues, customers and regulators.

With deliberate leadership and responsible adoption, AI can accelerate women’s progression, strengthen performance and set a standard the wider sector can follow.