Companies Struggling to Harness AI for Compliance, New Report Finds

While interest in AI-driven compliance solutions continues to surge—particularly within financial services and risk management—the latest FinCrime Frontier 2025–26 report underscores a critical challenge: technology alone cannot compensate for weak data foundations. According to the landmark study, only 11% of compliance professionals say they are "very confident" in their data quality, with more than half admitting to fragmentation or gaps that hinder meaningful AI-led outcomes.

Firms are eager to automate compliance workflows with AI, but without accurate, complete, and well-governed data, these systems can't deliver reliable results," the FinCrime Frontier report notes — highlighting confidence issues around data quality and governance.

Experts from AML Intelligence have similarly emphasised that many organisations simply lack the data governance, clean data pipelines, and quality controls necessary to make AI work effectively in compliance. In fact, a majority of companies surveyed — 58% — admit to having data gaps that block effective use of AI for key compliance functions such as risk detection, transaction monitoring, and regulatory reporting.

"AI can be a powerful tool for compliance, but only when it's built on trustworthy data. Our role is to help organisations get that data right — so their AI delivers real, reliable results," explains the AML Intelligence commentary on FinCrime Frontier.

The report's findings suggest that merely adopting AI tools is not enough to ensure success. Instead, firms must build a strong "data foundation" — clean datasets, robust metadata management, and transparent data processes — to support trustworthy AI outcomes.

The FinCrime Frontier study explicitly calls out poor data quality and fragmented data as critical barriers that slow progress on AI adoption and automation. This reinforces broader industry understanding that data maturity is fundamental to AI maturity: without accurate, consistent, and governed data, even advanced machine learning models struggle to produce reliable, auditable outputs.

As regulators increasingly expect firms to demonstrate how AI-driven compliance systems make decisions, poor data quality could not only limit operational efficiency but also expose organisations to new regulatory and reputational risks. With growing pressure on firms to modernise compliance through AI, MHC Services helps organisations strengthen the data underpinnings that make AI truly effective and auditable.

MHC's experts work with clients to assess data integrity, implement quality controls, and establish clear governance structures — ensuring compliance teams can rely on accurate, complete, and traceable information, which is the cornerstone of any successful AI strategy.

By providing end-to-end data management and compliance solutions, MHC enables firms to bridge the gap between ambition and execution. From data cleansing and metadata mapping to lineage tracking and regulatory alignment, the company helps businesses create a solid, compliant foundation that supports both innovation and oversight.

As the FinCrime Frontier report makes clear, those who invest in data readiness today will be the ones leading the way in AI-driven compliance tomorrow.