Artificial intelligence has moved rapidly from an experimental capability to a foundational pillar of RegTech, forcing financial institutions to reassess how compliance teams are structured and scaled.
Rather than signalling the end of human-led oversight, the emergence of advanced AI tools is redefining how people and technology work together, said ComplyAdvantage.
The central question is no longer whether compliance teams will be replaced, but how they will evolve as AI becomes embedded into daily operations.
That evolution was a central theme at CATALYST 2025, where senior practitioners from Mollie, Monzo Bank, PwC and ComplyAdvantage discussed how AI is reshaping financial crime compliance. The panel rejected the idea of a zero-sum contest between humans and machines, instead describing a future built on human-led automation. In this model, AI functions as a “digital coworker”, supporting compliance professionals by filtering data, identifying patterns, and enabling a more proactive approach to managing financial crime risk.
One of the clearest benefits highlighted was AI’s ability to absorb operational noise. As institutions grow, compliance costs have traditionally increased in line with headcount, particularly as alert volumes rise. AI disrupts this pattern by processing large volumes of low-risk activity at speed, allowing teams to focus on genuinely complex investigations.
Despite these efficiencies, the panel was clear that AI cannot replicate human empathy. Certain customer interactions, particularly those involving vulnerable individuals, require sensitivity that automated systems cannot provide. AI may rapidly identify a romance scam or flag a vulnerable customer profile, but the response still depends on human care and discretion.
Governance and accountability were another core theme. While regulators such as the Financial Conduct Authority are increasingly encouraging innovation through initiatives like live sandboxes, responsibility for AI-driven decisions remains firmly human-led. Institutions must be able to explain how and why AI systems reach specific conclusions. The panel likened AI agents to new employees, requiring onboarding, oversight and ongoing performance assessment to ensure they operate within defined risk appetites and regulatory expectations.
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