The Gender Gap in European Tech Is Becoming an AI Problem

For years, the gender gap in European technology could be discussed as a representation problem. In the age of artificial intelligence, that description is becoming inadequate.

The people gaining experience with AI today are positioning themselves for some of the most consequential jobs of the next decade. The people building AI systems will influence how businesses operate. The managers deciding where those systems are deployed will control investment. The leaders who understand the technology will be better positioned to shape corporate strategy.

This turns an old representation gap into a question about who participates in the next wave of economic value creation.

Women remain heavily underrepresented in technical roles

Women accounted for just 19.5% of ICT specialists employed in the European Union in 2025, according to Eurostat. The EU simultaneously wants to reach at least 20 million ICT specialists by 2030, roughly twice the current workforce, while improving gender balance. Our review of the latest women in tech statistics sets out how that figure varies across member states.

That means Europe cannot easily separate its skills problem from its representation problem. It needs more technical talent overall, and one of the largest underrepresented pools of potential talent is women.

AI could widen gaps that already exist

Recent McKinsey research describes a particularly difficult transition. Women accounted for around 19% of European tech roles in the research analysed for 2025, but only 13% of management positions and 8% of senior management roles. Its analysis also found shrinking demand in some entry-level technology roles as AI changes how companies structure work.

Entry-level jobs have historically provided a route into the industry. If parts of that work are automated while the fastest-growing opportunities require more specialised skills, people who already have networks, experience and access to advanced projects gain an advantage.

The definition of a technology career is expanding

There is also a reason for optimism. The AI economy is not limited to researchers training frontier models.

Skills England now groups workplace AI capability across technical, non-technical and responsible or ethical skills. Its 2026 framework reflects something happening across the wider labour market: professionals in many functions increasingly need to understand how to use, assess and govern AI tools. Our guide to the AI skills that actually matter in 2026 translates that into practical career decisions.

Engineers need technical capability. Product managers need to understand what models can and cannot do. HR teams need to understand automated decision-making. Executives need enough technical literacy to question AI investments. Legal and policy teams need to interpret risk. Designers need to understand human interaction with intelligent products.

Europe's commercial incentives are enormous

AI adoption is accelerating quickly. The European Commission reported in its 2026 Digital Decade package that nearly 20% of EU enterprises were deploying AI, with adoption increasing sharply during 2025. Yet skills remain a major constraint on digital transformation.

Companies therefore face two choices. They can compete over an already constrained pool of experienced AI professionals, or they can expand the pool. Upskilling women already working in software, data, product, operations and leadership is one of the most obvious ways to do that.

Representation at the top matters too

The conversation cannot stop at entry-level recruitment. If women enter technology but remain underrepresented in senior positions, they remain underrepresented where investment and product decisions are made.

Leadership visibility also changes what younger professionals believe is possible. A junior engineer who regularly sees women leading engineering organisations receives a different signal from one who encounters women primarily in junior and support functions. The Women in Tech EMEA Summit agenda is built around that kind of visibility, with technical and leadership sessions delivered by practitioners.

The AI transition gives Europe a chance to reset

The technology industry does not need to reproduce its existing workforce composition inside AI. AI adoption is still developing. New jobs are being created. Established roles are being rewritten. Organisations are deciding what AI capability means for engineers, managers and executives.

The next gender gap in technology is being created now. It will be determined partly by who receives access to AI projects, who receives training, who is promoted into technical leadership, who has a voice in AI governance and who is encouraged to see themselves as part of this new economy.