The AI revolution in corporate KYC. Is it here to stay?

Yes, and it is already transforming how banks manage identity, risk, and compliance.

Generative AI is the fastest-adopted technology in history, but speed of adoption has not always translated into enterprise impact.

In corporate banking, many Gen AI pilots have stalled before delivering measurable results. Often because they were treated as innovation experiments rather than embedded operational capabilities. But the landscape is shifting. We are now seeing agentic AI being adopted at scale, moving beyond prototype into real operational impact.

For institutions that approach AI strategically, with trusted data foundations and governance built in, the technology is proving transformative. Especially when combined with Corporate Digital Identity (CDI).

The reality: KYC remains a slow and complex challenge

Despite years of digital transformation, Know Your Customer (KYC) and client onboarding and review processes remain cumbersome. Manual data collection, repetitive client outreach, and slow internal approvals continue to cause friction.

Banks face persistent pain points:

• Fragmented data and incomplete entity records
• Repetitive documentation requests that frustrate clients
• Lengthy approval cycles that drive high abandonment rates
• Inconsistent risk assessments across jurisdictions

Why AI offers a breakthrough

AI, and in particular agentic AI, is uniquely positioned to resolve these challenges. It enables automation of the most data-intensive and error-prone elements of KYC. Turning complex manual processes into scalable digital workflows.

Modern AI models can:

• Automate data extraction and summarization from documents, pulling key data points from incorporation certificates, shareholder records, or regulatory filings
• Support entity resolution and Ultimate Beneficial Ownership (UBO) identification, matching entities across multiple data sources to build a complete view of a corporate structure
• Accelerate case reviews, surfacing key insights, summarizing evidence, and reducing analyst workloads
• Enable perpetual KYC (pKYC) frameworks, shifting from periodic snapshots to continuous, dynamic risk assessment

When implemented effectively, these capabilities can cut KYC and review cycle times, reduce manual errors, and enhance both compliance and customer experience, critical differentiators in wholesale banking relationships.

But the challenge is scale

Despite the clear opportunity, most banks still struggle to move AI from proof-of-concept to production. Despite $30–40 billion in enterprise investment in generative artificial intelligence, pilot failure is officially the norm. 95% of corporate AI initiatives show zero return, according to a sobering report by MIT’s Media Lab.

Additionally, Over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls.

The reason? Most AI initiatives are launched as experiments, disconnected from real workflows, business KPIs, and governance frameworks. Implementation costs, data silos, and regulatory uncertainty often outweigh early enthusiasm. Without a robust data foundation, even the most sophisticated AI models cannot overcome the fundamental challenge: garbage in, garbage out.

AI is not a plug-and-play solution. Its success depends on integration, governance, and trust, and that starts with data.

The data foundation: Corporate Digital Identity (CDI)

AI models are only as effective as the data they learn from. In corporate banking, data is often fragmented, inconsistent, and manually maintained. This challenge is particularly acute for institutions operating across multiple jurisdictions, where entity data must reconcile divergent regulatory requirements and naming conventions.

CDI addresses this challenge by providing a unified, verified, and dynamic representation of a legal entity. It aggregates information from registries, regulators, ownership filings, and trusted third-party sources into a single digital profile.

This is where EC360 from Encompass makes the difference. Built to automate and orchestrate corporate identity data at scale, EC360 provides the dynamic foundation that enables banks to operationalise AI safely and effectively.

When paired with AI, EC360 and CDI deliver powerful outcomes grounded in clean, connected and fully explainable data:

• Real-time collation of public and private sources is normalized, standardized and deduped. Resolved at entity level with consistent data collation and lineage
• Clean, connected data that ensures AI models operate on reliable, current information, reducing false positives and enabling accurate risk scoring
• Faster entity resolution and UBO discovery, supporting risk-based due diligence aligned with FATF standards and jurisdictional requirements
• Standardized automation rules ensure consistent data collation
• Auditable, explainable outputs aligned with regulatory expectations for model governance and transparency
• Reduced client friction through data reuse and digital verification accelerating time-to-revenue

Together, CDI and AI form the backbone of a new, intelligent approach to KYC. Subsequently, enabling banks to reallocate resources from initial customer verification to deeper, more strategic risk management and relationship development.

Embedding AI strategically

To realize these benefits, banks must shift the focus from experimentation to measurable business outcomes:

• Reduced onboarding and periodic review times
• Lower operational and compliance costs through intelligent automation and exception-based workflows
• Improved data accuracy and transparency, supporting both regulatory reporting and strategic decision-making
• Enhanced customer experience and retention, particularly critical for high-value corporate and institutional relationships

This requires more than technology. It calls for alignment between compliance, technology, and business teams. With governance built in from the start; secure access, comprehensive audit trails, explainability, and regulatory readiness. The integration of compliance logic directly into smart contracts, as demonstrated in Swift’s September 2025 blockchain ledger initiative with embedded AML and KYC checks, illustrates the convergence of these capabilities at the infrastructure level.

With EC360, these principles are embedded by design. Its ability to connect real-time data, enforce governance, and surface explainable results gives banks the control and confidence needed to operationalise AI responsibly.

With the right foundation, AI doesn’t replace human expertise, it amplifies it. In a Human in the Loop (HITL) model, analysts stay at the center of judgement, investigation, and oversight, while AI handles the data-intensive groundwork. This augmented decision-making model represents the practical reality of AI deployment, moving beyond the hype of full automation.

The verdict: AI in corporate KYC is here to stay

The global Anti-Money Laundering and KYC in Banking Market, valued at $131.86 billion in 2024, is projected to reach $241.13 billion by 2033, exhibiting a CAGR of 6.88%. Within this landscape, leading institutions are prioritizing CDI and KYC capabilities as foundational infrastructure. Recognizing that competitive advantage in AI-driven compliance depends on solving the entity data challenge first.

The real question is how banks will embed AI to achieve lasting value.

Institutions that pair AI innovation with a robust CDI strategy are already setting the standard: faster onboarding, greater compliance confidence, and a significantly improved client experience. In parallel, the convergence of blockchain technology is creating new opportunities for trusted, interoperable digital identity frameworks that transcend institutional boundaries.

AI is here to stay. CDI is what makes it work.