From regulation to acceleration

According to KPMG’s latest Venture Pulse report, UK firms secured $5.5bn (£4.1bn) in venture capital investment in Q1 2025 alone – more than Germany and France combined.

This achievement coincides with the EU’s landmark €1.3bn (£1.1bn) commitment to accelerate AI adoption and digital infrastructure.

For capital markets firms operating across the UK and Europe, the message is clear: AI innovation and regulation are converging, and firms must be ready to scale responsibly.

Despite the acceleration of AI adoption in capital markets, firms must still learn how to harness the technology’s ability to process vast amounts of data and execute tasks at speed so employees can focus on higher-value activities.

AI in capital markets meets regulation

The EU’s recently enacted AI Act stresses the need for explainability, risk categorisation, and ethical governance in AI systems. European capital markets firms thus face the dual pressures of keeping pace with AI-driven competition and embedding compliance into every layer of AI deployment.

Productivity is another focal point. While many firms have seen efficiency gains from AI, the EU’s investment suggests that scalability, cross-border data interoperability, and automation of high-volume processes will become the bedrock of digital competitiveness.

Empowering the workforce

Firms must invest in continuous learning and AI training programs to ensure employees can collaborate effectively with AI tools. Establishing internal centres of excellence can help employees develop AI literacy and drive innovation.

With Europe injecting billions into building out its AI infrastructure, the onus is on firms to ensure their workforces can operate within it.

Establishing robust governance and ethical frameworks

A lack of robust AI governance risks deployment of systems that lack transparency and accountability, increasing the likelihood of regulatory penalties. As such, firms should establish clear ethical guidelines on AI usage, including implementing real-time compliance monitoring systems that allow AI decisions to be audited continuously.

However, human oversight remains critical and should be embedded throughout AI workflows to ensure automated decisions align with human-designed objectives.

In the context of the EU’s AI Act, investment in systems that generate transparent decision trails is essential for demonstrating compliance with regulatory expectations.

Securing successful AI adoption

For AI to deliver sustainable value, firms must go beyond traditional “human-in-the-loop” models and create predefined intervention points where experts guide AI-driven decision-making without causing workflow disruptions.

Here, data quality is essential. Without high-quality, unbiased datasets, AI models can generate inaccurate predictions that compromise decision-making. Firms can mitigate this risk by implementing robust data management strategies to ensure AI systems operate with maximum reliability.

Preparing for the future of AI

The EU’s AI investment shows that it doesn’t just want to regulate AI; it wants to lead in its responsible development, meaning firms must adopt strategies that align innovation with regulation. Here, traceable AI will play a central role in satisfying compliance demands and client expectations for transparency.

Meanwhile, data automation will be vital to scaling AI across front- and back-office functions, becoming a key enabler of the EU’s broader digital agenda.

Dan Reid is the chief technology officer of Xceptor

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May 12, 2025 at 12:03PM