AI adoption in risk and compliance

Introduction

The momentum behind artificial intelligence (AI) in risk and compliance is undeniable. Once a future-facing concept, AI is now a present-day reality for a majority of organizations. Moody’s latest global study, a follow-up to our 2023 report, surveyed 600 risk and compliance professionals and found the industry has moved beyond exploration and into active implementation.

However, the journey from adoption to transformation reveals a critical gap between AI’s promise and its current, practical impact. While enthusiasm is high, the results on the ground are more moderate, highlighting the real-world challenges of integrating this powerful technology.

The AI adoption boom

The pace of change is accelerating dramatically, with the report revealing a significant leap in AI adoption:

• More than half of professionals — 53% — are now actively using or trialing AI, a steep climb from just 30% in 2023.
• Awareness is nearly universal, with 91% of respondents aware of AI’s role in the risk and compliance function.
• Large language models are the most common technology, with 62% of companies now accepting or encouraging their use, a stark contrast to 28% in 2023, when most firms had no official stance.

A reality check: The gap between expectation and impact

Despite the surge in adoption, the benefits aren't always meeting the initial hype. While 84% of professionals agree AI offers significant advantages, the on-the-ground reality is more nuanced:

• Nearly half of respondents (46%) describe the current impact of AI as moderate.
• Only 30% report seeing the significant benefits they expected.
• Those merely considering AI perceive greater potential benefits in areas like accuracy and cost savings than those already using it, suggesting that experience has tempered expectations.

The key barriers to widespread impact

So what’s creating this gap between promise and practice? The report identifies several key hurdles that appear to be preventing organizations from achieving transformative results at scale.

One key barrier is not technology but rather people, with 41% of respondents citing a lack of internal expertise or skills as the top challenge to adopting AI at scale. With technology like ChatGPT in hundreds of millions of devices, skills are being developed quickly, which is an easy way to familiarize yourself with the technology. We expect this 41% of respondents to decrease as more users leverage this tech in their personal lives.

Other significant challenges include:

• Regulatory uncertainty or compliance risk (33%)
• Difficulty integrating with legacy systems (30%)
• Insufficient budget or resources (27%)

The path forward: From moderate to transformative

Closing the gap may require a focused, strategic approach that goes beyond simply deploying new tools. The report highlights three critical areas for organizations to focus on:

1. Get your data in order: Data quality is a powerful predictor of AI success. The study found that 59% of active AI users rated their data as high quality, compared with 69% of non-users who reported their data was inconsistent or unstructured. Better data promotes AI use, and AI use drives better data.
2. Invest in people and processes: With a lack of skills being the top barrier, success depends on upskilling teams. The most cited safeguards professionals want are comprehensive training (44%) and a strong AI governance framework (43%). This demonstrates a clear need for education and guardrails to help build trust and competence.
3. Redefine the role of the professional: The future of compliance is about working alongside AI as a digital coworker. An overwhelming 96% of respondents believe their roles will change, becoming more strategic. They anticipate their work will evolve to:
   1. Take on more strategic or advisory responsibilities (61%)
   2. Focus on exception handling and oversight (54%)
   3. Act as supervisors of AI systems (47%)

Conclusion

While the industry has proactively adopted AI, the initial wave of implementation has revealed that technology alone is not a silver bullet.

Closing the gap between AI's promise and its practice will be aided by a strategy focused on improving data maturity, investing in human expertise, and building robust governance. As organizations master this balance, the "moderate" impact of today will evolve into the transformative efficiency, accuracy, and insight of tomorrow.

To dive deeper into the key findings from our global survey, visit moodys.com/kyc/ai-study