The Value of a Claims Library in the AI Era

Oct 28, 2026 | Jordan Tieman

AI adoption in life sciences changes how biopharmas create promotional content, but it hasn’t replaced the need for foundational data hygiene. A claims library is more than a repository or an auto-substantiation tool. Claims — maintained as structured, connected records — provide essential context across the content lifecycle.

From understanding where messaging is used and determining the level of review a material requires, to giving AI a reliable source of approved information, claims form a compliant content foundation for the future.

Yet, many organizations still underuse claims libraries or don’t fully see the value in leveraging the digital connections between claims and content. The following situations demonstrate why a structured claims library is an indispensable asset.

1: We need to know where this claim is used, asap

Imagine receiving a Warning Letter or Label Update that invalidates a specific product claim. Leaders need a full remediation plan and a comprehensive list of all material using that claim — and they need it now.

For organizations without a structured, auto-linked claims library, this triggers an all-hands-on-deck emergency. It often pulls in team members who work in other areas. Operations teams must halt other work to manually scan hundreds of assets, a process that can take days and is prone to human error.

One organization facing this scenario estimated that it would take a four-person team four days to locate an invalidated claim across their entire content universe. Linking claims records to materials avoids such fire drills and ensures swift remediation and updates.

This situation isn’t just about regulatory response. Teams need claims traceability for everyday content operations.

2: Our AI content creation tool needs a compliant source

Generative AI can create content quickly but cannot, on its own, determine which claims are current or approved for a particular use case. When AI tools are pointed at unstructured, historical marketing materials rather than a structured library, they frequently pull outdated, unapproved, or out-of-context claims. AI inherently prefers structured data.

A well-maintained claims library provides the precise context, categorization, and approved messaging AI needs to generate compliant content. Without it, biopharmas risk scaling non-compliant messaging at the speed of AI.

Consider a marketer asking an AI tool to create an email using approved efficacy and dosing messages. If the tool draws primarily from historical materials, it may have to infer which messages are relevant, or worse, pull in outdated claims. AI is only as useful as the information it accesses. A claims library gives AI structured, current context instead of forcing it to infer approved messaging from a collection of documents.

3: Not every material needs the same level of review

Modernizing the medical, legal, and regulatory (MLR) review process increasingly includes tier-based or streamlined routing. To accelerate the review process, organizations are differentiating how a piece of content is reviewed based on a simple question: Are these claims new, updated, or exact matches to previously approved claims?

• Exact matches: If material consists entirely of exact, previously approved claims, all review groups may not need to review the underlying science again. Reducing the review functions required for specific materials enables the content to move through the MLR process faster.
• New or updated claims: In this pathway, MLR reviewers are instantly aware they must invest time investigating supporting evidence and usage of the claim.

Without a structured library acting as the baseline for comparison, reviewers treat every claim as potentially new, manually scanning past materials to verify if a phrase has been approved before. A claims library provides the immediate context reviewers need to understand the required level of effort, accelerating the review process and improving their experience.

4: Our claims library is the source of truth for more than our MLR team

A claims library serves as a common reference point for creating or adapting brand content. Marketing teams, agency partners, global teams, and local markets all need to understand what messaging is approved and how it can be used. As organizations create more derivative content than ever before, that need increases. For example, global teams invest significant resources developing core messaging and supporting evidence, but without visibility into claims usage downstream, it’s difficult to understand whether local teams are adopting global material.

A structured claims library provides a central view of approved messaging to support consistency across channels and geographies. It distinguishes approved claims from messaging that hasn’t been used. This global-to-local consistency ensures alignment of all channels and markets. The inherent traceability in a digital library allows global teams to actively measure the ROI of their messaging investments by tracking which core claims are being deployed in local campaigns.

The bottom line about claims management

AI is taking on more of the low-value tasks MLR reviewers and marketers previously handled — from editorial and compliance checks, to claims identification and substantiation. Agentic AI and the humans who use these tools require access to reliable, structured data to function compliantly. Whether you use external generative AI platforms or internal referencing engines, a structured claims library is the indispensable core of a compliant, scalable strategy.

Learn how a unified claims library in Veeva PromoMats delivers efficiency and traceability.