Birlasoft and Oracle hosted an exclusive roundtable of CHROs and senior HR executives from across various industries in London to discuss the challenges, opportunities, and imperatives of EU Pay Transparency. What followed was not a discussion about legal obligations. It was a conversation about HR transformation.
With enforcement deadlines fast approaching, the discussion revealed both strategic concerns and actionable paths forward for organizations navigating the evolving regulatory landscape.
The roundtable was opened with a common, clear understanding: the directive demands gender-neutral pay structures, consistent data on job functions and skills, and the ability to justify pay differences exceeding 5%. But beneath the surface, the conversation quickly turned to organizational readiness, data integrity, and the cultural mindset shift required to make fairness measurable.
As one attendee pointed out:
“It’s not about how long someone’s been working, it’s about whether their skills are truly relevant — and in demand — today.”
This statement cuts to the core of a larger issue: traditional compensation frameworks no longer reflect the true value of talent. Time served is not enough. Skills matter more. But how to track it properly? Every leader in the room acknowledged a familiar point of pain: the fragmentation of systems.
Many organizations had robust HCM platforms in place (such as Oracle HCM), but performance, payroll, and benefits data remained siloed. Allowances weren’t tracked, skill data was incomplete, and regional interpretations of the directive varied widely, especially between different countries in Europe and the UK.
What’s emerging is a critical insight: HR cannot comply with what it cannot see.
Enter AI: Not a Future Solution, a Present Necessity
AI was one of the most discussed and most promising tools of the day. From GenAI-powered agents to multi-modal learning models that interpret unstructured HR data, we’re seeing AI move from a buzzword to an operational ally.
At Birlasoft, we showcased how AI can:
- Predict trends in gender pay gaps
- Automate role-based compensation mapping
- Enable real-time self-service access to policy-driven pay answers
- Drive clean, centralized data for compliance-grade reporting
However, a word of caution was also offered: AI is only as good as the data feeding it. Using a live HCM system as an “experimental sandbox” can lead to poor outcomes. Instead, HR leaders should rely on secure analytics tools, such as Oracle EPM, to test, model, and validate outcomes first.
As the conversation evolved, three clear priorities emerged for HR leaders:
1. Assess the Data
Most companies don’t yet have a “single source of truth” for pay, performance, and skills. A targeted assessment can help identify the blind spots.
2. Activate Your HCM System’s Full Potential
Many organizations are underusing their HCM platforms. Unlocking features like role-based skills mapping or pay grade calibration can deliver both compliance and clarity.
3. Invest in Scenario Planning
Pay transparency is as much about preparedness as it is about reporting. Leaders must model potential grievances, recruitment challenges, and cultural shifts that may arise once employees have greater access to wage data.
One point echoed around the table: the business case for transparency is no longer just compliance — it’s reputation. Employees will ask questions. Candidates will compare offers. Boards will demand visibility. And the cost of non-compliance? It’s not just financial — it’s cultural.
As we wrapped up, there was a shared recognition: this directive is not a burden. It’s a strategic moment. One that can elevate HR as a data-driven, value-defining function at the center of business.
It’s no longer enough to talk about fairness. We must show it. Measure it. Report it. And defend it — with the systems, strategy, and skill sets to back it up.
