The Roadblocks to AI in Compliance — and How to Overcome Them

Artificial intelligence (AI) is becoming a cornerstone of compliance functions, offering efficiency, speed, and enhanced detection capabilities across financial crime prevention, audit, and risk management. Yet, its adoption is far from straightforward. Compliance leaders face unique challenges—regulatory barriers, technology limitations, and the demand for explainability—that slow implementation and require a thoughtful approach. 

Compliance functions are tightly regulated, and introducing AI adds layers of complexity. Unlike other business areas where technology adoption is relatively straightforward, compliance must balance innovation with the responsibility of safeguarding against risk. 

• Singapore has taken a proactive stance, requiring financial institutions to submit AI roadmaps to regulators. This structured approach aims to encourage responsible adoption while maintaining oversight.
• Europe has focused primarily on regulation, becoming the first region to pass an AI regulation act. European regulators emphasize caution and oversight, prioritizing risk management before acceleration.
• United States regulators are moving more quickly, with the White House recently publishing a paper encouraging AI use in financial services. Adoption is being driven by innovation, but with a growing emphasis on accountability. 

These regional differences reflect broader tensions: regulators want to encourage efficiency and innovation, but not at the expense of transparency and control. 

A key obstacle to implementing AI in compliance is the need for explainability. Compliance officers, auditors, and regulators cannot rely on “black box” systems where decision-making processes are opaque. Organizations demand clarity on how an AI model arrives at conclusions—particularly when those conclusions involve identifying suspicious behavior, potential fraud, or regulatory breaches. 

Explainability is not only a regulatory expectation but also a trust-building requirement. Without it, compliance leaders are unlikely to embrace AI fully. 

Although AI capabilities are advancing rapidly, they are not yet fully suited to the complexities of compliance. Regulatory texts, for example, are lengthy, technical, and full of dependencies across sections. 

The nuance of regulatory interpretation—such as handling definitions buried elsewhere in a text or reconciling cross-references—remains a significant challenge for general-purpose AI tools. 

To mitigate risks, organizations are increasingly adopting human-in-the-loop designs. This approach ensures that AI augments rather than replaces human judgment. AI handles the heavy lifting—analyzing customer behavior, generating alerts, or extracting regulatory obligations—while compliance experts validate results, make risk-based decisions, and maintain accountability. 

This model allows organizations to capture the efficiency, speed, and quality benefits of AI while ensuring oversight remains intact. Human judgment acts as a safeguard, addressing technology gaps and reinforcing trust. 

RegMatcher, developed by Sia’s teams, embodies this responsible approach to AI adoption. Unlike generic AI platforms, RegMatcher specializes in compliance by: 

• Breaking down regulations into obligations and mapping each to organizational documents, such as internal policies and procedures.
• Managing legal complexity including cross-references, footnotes, and definitions.
• Providing explainability features that allow users to see background processes, adjust models, and validate outputs.
• Ensuring flexibility and integration through an API-based design that adapts to existing workflows. 

By focusing on accuracy, explainability, and human oversight, RegMatcher reduces manual workloads while giving compliance professionals confidence in results. 

The challenges of implementing AI in compliance are real, but not insurmountable. Regulatory caution, technology limitations, and explainability demands all slow adoption—but they also ensure that implementation is responsible, reliable, and sustainable. 

As AI technologies mature, compliance professionals will transition from operational roles to advisory and oversight ones. This will allow them to focus on higher-value work in supervising its use, while AI agents manage routine tasks. The future of compliance will not be defined by technology alone, but by the balance between AI efficiency and human expertise.  

Sia supports organizations in harnessing AI to transform their compliance functions, combining regulatory expertise with advanced data science capabilities. We design and implement AI solutions that streamline processes like KYC, AML monitoring, and sanctions screening, reducing manual workload while improving accuracy and speed. Our approach enables clients to shift from reactive compliance checks toward proactive, risk-based strategies that anticipate issues before they arise.