KDR Talent Solutions

Data governance has always been a critical foundation for financial services firms In 2025, however, the landscape has shifted dramatically. The rise of AI is fundamentally reshaping how data is created, processed and used across financial institutions (although admittedly maybe less emphasis as yet on the how data is created). With more decisions becoming data-enabled and automated, the need for robust, transparent governance frameworks has never been greater. Meanwhile, new regulations like the EU’s Artificial Intelligence Act and a focus on ISO 42001 are introducing stricter requirements for explainability, data traceability and accountability in AI systems, raising compliance demands across the sector. Alongside these shifts, public scrutiny of how organisations manage personal data has intensified. Clients, investors and regulators alike now expect higher standards of data privacy, security and ethical usage. It is no longer enough to have a framework ‘on paper’; financia...

Demand for AI talent is booming, but filling roles can still feel challenging for some.  Despite a wave of AI bootcamps, MSc programmes and online certs, the real-world AI skills gap risks blocking innovation and slowing team scaling. So, what’s actually going wrong? And what do high-performing hiring managers do differently to fix it? Diagnosing the AI Skills Gap The talent pool isn’t empty, but the skill sets often don’t align with what’s needed in production environments. Many job specs still optimise for “AI research” rather than applied, product-focused AI. The result can then be a mismatch to required outcomes, not because candidates lack skill, but because their experience often lies in different contexts, like academic research or prototype environments, rather than fully integrated production systems.   Actionable fix: Stop hunting for unicorns and start mapping your needs to adjacent, trainable profiles. What do we mean by this? For example, let’s say you...