Agentic AI for MLR:
The Highest-Impact Area of Content

Feb 03, 2026 | Alexis Cohen

With widespread deployment of AI in commercial biopharma, a key learning has emerged: Aligning AI with high-value business needs can deliver benefits beyond productivity gains, driving greater strategic value to an organization. In the content supply chain, that high-value area is medical, legal, and regulatory (MLR) review.

“MLR is the backbone of this industry. Without this team, we cannot get content out.” Senior vice president and regulatory operations director

Content volume keeps rising as the industry craves highly personalized and impactful material — yet MLR resources are stagnant or decreasing. MLR review is the core of the content lifecycle and an obvious target for AI optimization and promised returns, enabling faster delivery of accurate, compliant treatment information for HCPs and patients.

Moreover, applying AI in MLR has a compelling business impact by structurally improving processes, freeing highly skilled experts for strategic work where human input is critical. The value is not just in providing a shortcut for reviews, but as an aid to make processes more effective while maintaining high-quality material.

As one regulatory operations director and senior vice president puts it, “MLR is the backbone of this industry. Without this team, we cannot get content out.” For many biopharmas, Veeva Vault is the platform of choice for MLR processes and therefore is a high priority for Veeva as we develop purpose-build agentic AI solutions for the industry.

Transforming MLR through agentic AI

Built natively into the Vault Platform, Veeva AI for PromoMats introduces intelligent AI agents directly in users’ core processes to perform quality checks, provide document insights, and assist reviewers. Quick Check Agent and Content Agent streamline MLR review to deliver personalized, impactful, and compliant material faster.

Agentic AI, which can manage multi-step processes autonomously, is uniquely capable of handling compliance pre-checks and flagging risks while avoiding a rework of the end-to-end content supply chain. Compliance and final direction remain firmly human-led.

AI agents deeply embedded in a commercial content platform work in concert with other technology and process improvements — such as tier-based review, content reuse, and claims management and harvesting — to drive efficiencies and produce the most relevant assets with faster approval times.

Quick Check Agent and Content Agent are the first of numerous Veeva AI agents that will work together in PromoMats to retool end-to-end content operations. Agentic MLR will follow, supporting the fastest path to approved content. Collectively, these AI agents not only help MLR, but enable marketing teams and their agency partners to deliver better content to the reviewers, accelerating the delivery of compliant content.

Test, learn, and scale AI within the MLR framework

Data, content, and now AI agents work in core applications like PromoMats and Veeva Vault CRM to optimize industry business processes and deliver impactful content to customers. The shared infrastructure allows for a frictionless lifecycle where digital assets and metadata flow organization wide. For example, once promotional content is approved, documents are immediately available in Vault CRM for distribution. The deeply embedded AI agents understand business rules and logic, use application-specific prompts, and access data and documents securely.

With this foundation, biopharmas can focus on identifying high-value AI use cases with the ‘Test, Learn, Scale’ framework:

1. Quantify the tangible business value and change impact for each use case to prioritize investments and projects.
2. Reshape processes and drive adoption with a defined subset of workers.
3. Redistribute time gained to higher-value tasks across the content model.
4. Measure ROI and remove process or adoption barriers.
5. Scale:
   • Globally, attending to language and local regulations.
   • Across brands or therapeutic areas.
   • To additional use cases and AI agents that become available.
   • Support AI investments with key industry learnings

Framework for success prior to scaling AI

Even at this early stage of AI adoption in MLR, there are reliable KPIs to use as guides. For example, measure short-term qualitative factors such as reviewer trust and longer-term quantitative results including time savings.

It’s not too early to set KPIs

In addition, biopharmas can shore up AI investments with industry insights and learnings:

Prepare people and processes for AI with efforts equal to those in making technology decisions. MIT findings back this idea: “Most [AI projects] fail due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations.” Distinguish between short- and long-term AI initiatives to achieve the desired outcomes at the lowest cost. Short-term pilot tests are often necessary but can quickly consume more than their share of resources, negatively affecting long-term AI ambitions. Understand current governance and compliance models for AI solutions and prepare to make any changes needed. Engage compliance professionals early in the process of incorporating AI, allowing them to help define the rules and mitigate risks.
• Periodically evaluate ROI from AI so teams continuously measure and adjust without process and adoption barriers, especially as the technology improves. Successful change with AI requires optimizing with humans in the loop.

We believe AI is meant to enhance the MLR experience by automating manual and repetitive work while humans maintain critical-thinking efforts — such as the difficult judgment calls needed in content approvals. Content teams are excited about a future where AI agents support them in being more productive and responsive to HCPs and patients.

In fact, in a recent Veeva PromoMats survey of 101 content professionals from 10 biopharmas, participants said they expect 38% of the MLR process to be AI-driven by 2028. And they cited ‘faster MLR review times’ as the number one anticipated benefit of AI in promotional copy approvals.

Focusing AI agents on the high-impact area of MLR provides biopharmas with a clear path to scale the technology, maximize its strategic value, and ultimately meet growing needs for rapid, compliant content delivery. A deep understanding of compliance and MLR is critical to making AI work in content, positioning Veeva and Veeva Business Consulting to guide biopharmas along this journey.

Uniquely equipped with the investments of time, resources, and effort on AI projects that deliver measurable business value, we are helping the industry and its people work in a more efficient and connected way.

Ensure your teams are prepared to leverage the full impact of AI agents with Veeva Business Consulting’s in-depth analysis.