Eurostat’s provisional estimate puts the EU’s unadjusted gender pay gap at 11.1% in 2024: on average, women’s gross hourly earnings are 11.1% lower than men’s. This compares average earnings across the economy; it does not measure a pay difference between people in equivalent roles. The explanations are numerous: unconscious bias, negotiation gaps, career interruptions, occupational segregation. But one driver is systematically underexplored — information asymmetry.

What you don't know costs you

Salary negotiation is a game of incomplete information. Companies know exactly what they pay across the organisation, what the market rate is for every role, and what the budget ceiling is for your position. Most candidates walk in with a rough number from a salary aggregator — and that number is often understated, particularly for women, because women historically underreport salaries in surveys.

This information gap compounds over a career. A below-market starting salary anchors every subsequent raise, promotion, and lateral move. The result isn't just a pay gap at a single point in time — it's a compounding gap across decades.

How AI changes the negotiation equation

AI tools give individual candidates access to the kind of market intelligence that used to require expensive recruiters or insider networks. That shift matters most for anyone without access to those networks — and the data consistently shows women and first-generation professionals are disproportionately excluded from them.

  • Benchmark your compensation across roles, seniority levels, geographies, and company sizes in minutes — not weeks
  • Identify the precise gap between your current package and what comparable candidates are earning, with specifics by sector and location
  • Prepare for objections, script negotiation language, and practise responses before the conversation happens
  • Analyse job descriptions to identify scope creep that objectively justifies a higher salary band

What fair matching actually looks like

Pay transparency is moving from a policy conversation to a technical one. The EU Pay Transparency Directive (2023/970/EU) requires employers to share salary ranges with candidates, in the job advertisement or before the interview — but disclosure alone doesn't remove the anchor effect of a candidate's previous salary. Platforms that match candidates to roles based on demonstrated skills, not proxies like degree prestige or previous pay, remove that anchor at the point of application. When your match score reflects what you can do, not what you've previously been paid, the ceiling lifts.

This is the foundation Lyra is built on. Transparent, skills-based matching means the information disadvantage disappears before the negotiation even begins.

The practical step you can take today

Before your next negotiation: spend 30 minutes with an AI tool benchmarking your role against market data. Build your number from that data, not from what you think sounds reasonable. The shift in confidence alone changes how the conversation goes — and it starts with having the right information.