The Invisible Risk: Undisclosed AI Use Inside Your Third-Party Ecosystem

Most organizations believe they understand how their vendors process critical data. What many do not understand—until it is too late—is how often AI systems are now processing that data the organization never approved, reviewed, or even knew existed.

This is not a theoretical risk. It is an emerging reality across regulated industries.

AI Has Entered the Supply Chain Quietly

Vendors are under immense pressure to improve efficiency, reduce costs, and scale delivery. AI offers an obvious solution. As a result, many service providers have embedded AI into their operations—customer support, data analysis, monitoring, and automation—without explicitly disclosing its use to clients.

In many cases, this is not malicious. It is also not transparent.

The issue is not whether vendors can use AI. The problem is whether you authorized it.

Why Undisclosed AI Use Is a Governance Failure

When a vendor introduces AI into a service handling your organization’s data, several fundamental assumptions change:

• Data flows shift beyond originally approved architectures.

• Processing purposes expand beyond the contractual scope.

• Model training or inference risks emerge.

• Sub-processors may be introduced indirectly.

• Regulatory obligations may be triggered without awareness

  
  

If your organization cannot answer whether vendors are using AI, then governance has already failed—regardless of how strong your internal controls may be.

Third-Party Risk Programs Were Not Designed for AI

Most TPRM programs focus on traditional controls:

• Data security

• Access management

• Incident response

• Business continuity

  
  

Few programs explicitly address:

• AI-based processing of client data

• Use of external models or APIs

• Model governance and approval

• Data retention and secondary use via AI

• Explainability and auditability of automated decisions

As a result, AI risk often sits completely outside existing vendor oversight.

The Regulatory Exposure Is Expanding

Across industries, regulators are increasingly concerned not only with how you use AI—but how your vendors use it on your behalf.

Organizations are being asked:

• Did you approve the AI use case?

• Did you assess the risk?

• Did you define boundaries for data use?

• Can you prove governance was enforced?

  
  

If a vendor’s undisclosed AI use becomes public, the accountability does not stop at the vendor. It extends to the organization that entrusted them with data.

Why Policies Alone Do Not Protect You

Many organizations assume that contractual language prohibiting “unauthorized data use” is sufficient.

It is not,

Without:

• Explicit AI disclosure requirements

• Defined approval gates for AI use

• Ongoing monitoring and attestations

• Evidence of enforcement

  
  

There is no practical way to ensure vendors are operating within acceptable risk tolerance.

Governance Must Extend Beyond the Enterprise

Effective AI governance cannot stop at your internal systems. It must extend into your third-party ecosystem.

This requires:

• Clear expectations for AI use and disclosure

• Integration of AI risk into vendor assessments

• Ongoing oversight, not one-time due diligence

• Alignment with emerging standards such as ISO/IEC 42001

  
  

The question is no longer whether vendors are using AI. The question is whether your organization is governing it.