Artificial intelligence is pushing beyond simple task automation in the Control Room, moving into conflict identification, workflow automation and pattern detection. As these applications mature, the stakes around data quality, trust, governance and accountability are rising sharply, and firms that get it wrong may soon face regulatory consequences.
These issues dominated a recent Control Room Executive Roundtable hosted by MCO in London, where senior Control Room and compliance leaders assessed where the industry stands and where it is heading.
Adoption is happening in phases rather than through a single overhaul. Most firms represented at the event are already automating smaller, repetitive tasks, although measuring the impact remains tricky. The next step, agentic workflows that allow AI to handle parts of a process more independently, is expected to take considerably longer. In the longer term, AI may become woven into how Control Room processes function, but participants focused on where it can deliver practical value now.
MCO’s Global Compliance Outlook, based on research by the Harris Poll, reflects this uneven progress. Some 47% of respondents are piloting AI solutions, while others already run AI in production for analytics and risk scoring, surveillance and alerting, and document review.
The value of any use case depends on the problem it solves and how reliable its output is. Automating an administrative task demands far less than an AI-supported process feeding into decisions on conflicts or sensitive information. More data is not automatically better either. In conflict checking, extra information may surface hidden relationships, but it can also add noise and raise the cost of sourcing and maintaining data. Timing matters too, as earlier information in the deal lifecycle could flag a conflict before a pitch or mandate begins.
Participants compared the current moment to the early shift towards SaaS platforms, which raised similar questions about trust, data and control. With little tolerance for error in the Control Room, firms must decide where humans stay involved, how outputs are validated and what level of explainability and auditability is needed.
Regulatory exposure is a growing concern. The group debated how long it might take before poor AI governance triggers enforcement action. MCO’s research found 42% of respondents named regulatory enforcement and unclear rules as a leading AI risk. Governance, testing, monitoring, documentation and the ability to reconstruct decisions are becoming core implementation requirements.
The workforce faces disruption too. Repetitive tasks most suited to automation are often how junior compliance staff learn about data, workflows, exceptions and judgement. If that work disappears, firms must find new ways to develop talent, a pressing issue given existing recruitment challenges.
MCO argues that a robust Control Room framework, with centralised management of sensitive information, conflicts and deal reviews, offers the foundation needed to evaluate where AI can add value while preserving the context behind decisions.
Copyright © 2026 RegTech Analyst
Copyright © 2026 RegTech Analyst
