Regulatory AI’s Expanding Role in AML/KYC

Introduction

2025 was a landmark year for the growth of real AI use cases in BFSI (banking, financial services, and insurance). AgenticAI gained considerable industry momentum in tandem with the more established Generative AI. We anticipate this momentum to continue to extend to AML/KYC. With Forbes predicting that Agentic AI has the potential to change the future of business operations, there is a lot of excitement about what AI can achieve for RegTech in the year ahead.

Despite their reputations as more regulated industries, banking and insurance have been fast adopters of AI. In fact, research from S&P global shows that 54% of financial services firms had deployed AI initiatives as of January 2025. This is up from 40% the year prior, suggesting a steady embrace of AI across the industry. 

Since many workflows for AML/KYC programs are already process-driven, the potential for similar growth in AI applications for this space is considerable. For example, legacy KYC document verification processes are often rules-driven, missing the ability to act on valuable context from unstructured data.

Given AI’s potential to augment the efficacy, efficiency, and scale of AML/KYC solutions, we believe that 2026 will be an inflection point in AI adoption for these use cases.

What might this look like in the year ahead? Based on our research, field observations, and industry experience, we expect to see the following in the upcoming year:

• New use cases in the emerging BaaS segment
• A more robust AI ecosystem surrounding AML/KYC
• A refreshed focus on AI ethics and responsible innovation

AI Successes Lead to Innovation in Adjacent Areas

Following early successes in regulatory and compliance AI implementations in consumer and corporate banking, expect to see more AI penetration in the emerging Banking-as-a-Service subvertical.

Banking-as-a-Service. Banking-as-a-Service (BaaS) industry continues its strong growth, it is expected to receive more regulatory scrutiny, opening the door for AI solutions to help. In BaaS, traditional financial institutions are servicing upstart digital entities that aren’t subject to typical industry regulations, standard regulatory and compliance concerns (including AML/KYC, as well as fraud detection, among others)

This creates additional layers of regulatory complexity. Part of traditional banks’ value proposition to their non-bank digital partners may be the ability to manage their AML/KYC requirements, they will likely look to AI to mitigate these challenges. We expect to see innovations regarding secure task handoff and process automation.

We expect the regulatory needs of BaaS providers and their banking partners to continue to evolve, as their unique data protection and security needs come into focus. Given the reputational and financial risk inherent in this new fintech frontier, we predict this will be a top priority for partner banks.

Regulatory AI Product and Service Ecosystem Shapes Up

As more regulatory AI use cases emerge and reshape current compliance processes, platform and ecosystem approaches will become crucial to optimizing AI benefits. Many Chief Compliance Officers may look to solutions that not only fit RegTech objectives, but can also work with IT departments to construct a tech stack that plays well with existing IT systems.

The ecosystem  approach also yields a promise of end-to-end visibility within AI-enabled process automation. As AML/KYC programs cannot live on an island within financial institutions, ecosystems can promote crucial information sharing and handoff within larger customer onboarding, verification, and reporting processes. While seamless end-to-end process automation has been a goal of many institutions for some time, the rise of agentic AI is expected to expand the possibilities of what can be achieved.

While commercial AI ecosystems should develop around AML/KYC, financial institutions still have “build vs. buy” considerations. Depending on unique business needs, data architecture nuances, and sensitivity of data, there are situations in which building in-house solutions may make more sense. Due diligence in selecting technologies for AML/KYC processes can be key to avoiding expensive enforcements resulting from procedural breakdowns.

Institutions May Increase Focus on Ethical AI and Responsible Innovation

Undue bias, job displacement, and privacy are among some of the core concerns as AI applications are implemented and scaled in AML/KYC programs. Additionally, while not ethical considerations on their face, security and exception handling are areas that amplify these considerations.

In the future, we expect AI leaders might dedicate more intentional efforts toward applying ethics and responsible innovation in BFSI. Understanding the intersection between ethics and business resilience, institutions should not only watch for ethical considerations at implementation but will also monitor and adjust throughout the technology lifecycle.

We predict organizations may focus on the following in the upcoming year:

• Fairness in AML/KYC processes. We expect institutions and technology providers to take extra care when training their AI models to avoid unfair biases. Additionally, AI’s ability to improve accuracy in identity verification will likely reduce the chance of errors that can lead to unfair actions being taken against a potential customer. 
• Targeting bad actors. New technology often means new ways of committing financial crimes. However, AI has the potential to help banks and their customers avoid the painful costs associated with fraud. In 2026, we anticipate an evolution of AML frameworks that have been mostly untouched for the last 50 years.
• Increasing transparency.  A lack of understanding into how AML/KYC AI models make decisions have served as a barrier to adoption. Moving forward, we predict institutions to make more efforts to understand what is happening within models to increase “explainability” and transparency. 
• Strengthening governance. As AI becomes a larger part of AML/KYC processes, institutions should respond by building appropriate guardrails and governance mechanisms. In 2026, we expect to see auditing, bias prevention, and legal and ethical compliance continue to be emphasized. 
• Ensuring data privacy and consent. With autonomous AI features expected to become more commonplace in 2026, we expect financial institutions to ensure their data privacy and security policies and frameworks account for AI agents.

Adapting to 2026 Trends Will Be a Team Effort

The pace of AI innovation has accelerated, and financial institutions will not be immune to the changes it brings to current AML/KYC processes. However, there are steps organizations can take to be proactive and set themselves up for success.

• Listen carefully to the signals on the ground. It will be easy for organizations to get lost in a maze of new regulations, guidelines, technologies, and partnerships. Leaders should be extra attentive to industry announcements and expect everything but the status quo. 
• Proactively guide teams through change. In an industry that has historically moved at a measured pace, regulatory and compliance teams may feel overwhelmed as AI’s organizational footprint grows. Adopting compliant change management techniques can assist with transitions. Transparency at every stage of change will also be key. 
• Collaborate intelligently. With new technology partners and ecosystem possibilities emerging, there will be the potential for unprecedented network effects, including more unified processes. We expect financial services firms to evaluate potential technology partners carefully, leveraging highly controlled proofs-of-concept and sandbox environments. At the same time, regulatory needs may complicate these potential collaborations and institutions should consider these at the earliest stages of technology evaluation.

In Closing

As AI becomes more deeply woven into the fabric of financial services, 2026 should be a year of both expansion and refinement for AML/KYC. Institutions that stay alert to regulatory signals, invest in responsible innovation, and collaborate strategically will be best positioned to harness AI’s full potential for AML/KYC. The organizations that balance agility with accountability should be able to do more than just keep pace with change, they can help define the next chapter of regulatory transformation.