AI and Women's Career Development: What Are We Learning from the Research?

AI is becoming part of career development. It is being used to support recruitment and job matching, develop skills, provide feedback and help people navigate career decisions. Yet when we looked specifically at AI applications supporting women's career development, the empirical evidence was still very limited.

In our scoping review, published in the International Journal for Educational and Vocational Guidance, we identified 13 empirical studies published between 2018 and 2025. The studies covered three broad areas: using AI to address bias and representation, supporting skills development and empowerment, and influencing career pathways and retention.

There are some promising applications. The bigger finding is how much we still do not know.

Three broad areas of research

What we can measure, and what we still need to understand

Most research has focused on what AI can do within career-related systems: identify bias, improve matching, analyse patterns or support particular tasks. There is much less evidence on whether these applications lead to meaningful and sustained changes in women's careers. We also found limited use of career-development theory and inconsistent attention to ethics, transparency and governance.

Principles need to be matched by evidence

This connects closely with the new Cedefop EU reference framework for lifelong guidance. The 2026 framework recognises AI as part of the lifelong guidance ecosystem and calls for its use to be accompanied by attention to human involvement, bias, privacy, transparency, digital inclusion and ongoing evaluation.

Our review suggests that these principles need to be matched by stronger evidence. If AI is going to play a role in career guidance, we need to evaluate not only the technology, but what it does to career development over time, for whom, and under what conditions. That includes looking at agency, self-efficacy, career outcomes and differences across women's social and economic circumstances.

That feels like the more important conversation to have as AI becomes part of career guidance practice.