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Why Grounded AI is Only Half the Answer for COI Compliance: illumend CEO Kristen Nunery Explains

By Lauren Towner · 16 September 2026

In brief: illumend CEO Kristen Nunery argues that grounded AI COI compliance requires cross-document reasoning to accurately connect contracts and insurance certificates, preventing hidden risk exposure.

Key facts
Documents Processed45 million
Agreements Managed1.2 million
Coverage Gaps Identified2 million
Founded2025
Press Release: Why Grounded AI is Only Half the Answer for COI Compliance: illumend CEO Kristen Nunery Explains | Featured Image by FF News

Kristen Nunery, CEO of illumend and founder of myCOI, is calling on business leaders to demand more from grounded artificial intelligence (AI) in Certificate of Insurance (COI) compliance. Nunery details her point of view in a new article titled "Grounding Is Half the Answer in COI Compliance."

The issue affects organizations that rely on vendors, contractors, tenants, franchisees, and other third parties to maintain contractually required insurance coverage, including businesses in construction, commercial real estate, retail and franchising, and government.

Grounded AI is an approach that bases its outputs on defined, authoritative information rather than relying solely on the general knowledge acquired during model training. In COI compliance, that information includes an organization's contracts, leases, insurance requirements, vendor classifications, required endorsements and approved exceptions.

Nunery's position is that grounding AI in an organization's insurance requirements provides a standard for evaluating compliance, but it does not provide sufficient evidence to make a reliable decision. AI systems must also connect information across contracts, certificates, endorsements, schedules, and amendments - and explain how that evidence supports each determination.

Modern AI can accurately extract policy numbers, coverage limits, carriers, and expiration dates from certificates. The distinction, Nunery argues, is that document extraction determines what an insurance document says, while compliance analysis determines whether the full body of evidence satisfies the requirements for a specific vendor, contract, project, or business relationship.

"COI compliance is a document-relationship problem before it is a document-reading problem," Nunery said. "An AI system can read every individual document correctly and still reach the wrong conclusion if it cannot understand how the agreement, certificate, policy, endorsement, and schedule relate to one another."

What Grounded AI Means for COI Compliance

Grounded AI is anchored to a defined source of truth rather than relying on general information absorbed during model training. In COI compliance, the relevant source of truth includes an organization's contracts, leases, insurance requirements, vendor classifications, project standards, required endorsements, and approved exceptions.

Grounding changes the question the system answers. An ungrounded system may assess whether a vendor appears adequately insured, even though "adequately insured" has no universal definition. A grounded system evaluates whether submitted evidence satisfies the requirements governing that specific third-party relationship.

The key difference is that grounded AI evaluates insurance evidence against requirements established by the organization rather than relying on a generalized model-generated standard of adequate coverage.

"Grounding gives the AI the standard instead of asking it to invent one," Nunery said. "A system that cannot tell you where its definition of compliant came from does not really have one."

Why Is Grounded AI Only Half the Answer?

Even a system perfectly grounded in an organization's requirements can reach the wrong decision if it fails to connect all relevant evidence.

For example, a certificate may indicate that additional insured coverage is present while an attached endorsement covers only ongoing operations. If the governing agreement also requires completed operations coverage, approving the vendor based solely on the certificate could leave the organization exposed if a claim arises after the work has ended.

Every document in that example could be read accurately. The incorrect decision would result from failing to connect the certificate and endorsement with the requirement established by the contract.

For businesses, this means accurate extraction is necessary but insufficient. A reliable COI compliance system must determine how information in one document changes, supports, limits, or contradicts information in another.

"Cross-document reasoning tells the system what the complete evidence means, while grounding tells it which requirements that evidence must satisfy," Nunery said. "Remove either one, and the resulting determination is a guess wearing a confident tone."

Nunery advocates for grounded AI systems that evaluate related insurance documents as one body of evidence. A system should determine whether a required endorsement exists, applies to the correct policy, names the appropriate legal entity or project, and satisfies the governing contract. It should also recognize when amendments, schedules, project requirements, or approved exceptions change the compliance decision.

In practical terms, grounding establishes the compliance standard, while cross-document reasoning determines whether the available evidence actually meets that standard.

Why Traceable AI Decisions Matter in COI Compliance

Nunery argues that every AI-supported compliance determination should identify which requirement applied, which documents were evaluated, and why the system reached its conclusion.

"A compliance determination that cannot be reconstructed is not defensible, however confident the system sounded when it made it," Nunery said. "Auditability should be treated as a fundamental requirement for grounded AI, not an optional reporting feature."

Traceability becomes critical during audits, contractual disputes, and claims. A confidence score or pass-fail label does not establish that the system applied the correct agreement, reviewed the relevant endorsements, considered approved exceptions, or evaluated the complete evidence.

A traceable COI compliance decision should allow a reviewer to reconstruct the path from the governing requirement to the supporting documents and the resulting determination.

Human oversight must also remain part of the process. AI can accelerate reviews and identify potential deficiencies, but a person should approve a determination before a third party is declared compliant - particularly when evidence is incomplete, policy language is unusual, or an exception applies.

How illumend Uses Grounded AI for COI Compliance

illumend is an AI-powered third-party insurance compliance and risk management platform backed by myCOI's institutional data foundation. During onboarding, illumend configures an organization's insurance requirements based on standards derived from its contracts and leases. The platform then evaluates submitted evidence against the defined requirements, reviews endorsements with each submission, identifies specific deficiencies, manages renewals, and documents the reasoning behind each determination.

"Grounding AI in an organization's requirements is the right place to start, but it is only half the answer," Nunery said. "Risk and compliance leaders should demand systems that understand the complete compliance picture, apply the correct requirements consistently, and produce decisions that can withstand scrutiny when an audit, dispute, or claim occurs."

Frequently asked questions

What is the difference between grounded AI and cross-document reasoning?

Grounded AI establishes the specific requirements an insurance submission must satisfy based on authoritative data, while cross-document reasoning evaluates how contracts, certificates, and endorsements work together as evidence. Reliable COI compliance requires both: grounding defines the standard, and cross-document reasoning determines if the evidence meets it.

Why is document extraction alone insufficient for COI compliance?

Document extraction identifies data like policy numbers and limits, but compliance depends on how that information relates to contractual requirements. A system can extract every field correctly and still make an incorrect determination if it fails to evaluate the relationships between different insurance documents.

How should organizations prepare for grounded AI implementation?

Organizations should document requirements in their contracts and leases, including differences by vendor type and jurisdiction. They must identify required endorsements and approved exceptions to establish a defined source of truth. illumend then configures these standards so the AI evaluates evidence against actual requirements.

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Companies in this story: illumend

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