Boehringer Ingelheim and Moderna: Early Insights From Implementing AI in PromoMats

Biopharmas face increased pressure to accelerate content development while maintaining rigorous medical, legal, and regulatory (MLR) standards. As a result, AI in content review has evolved from experimental to tangible, delivering practical value in the MLR space. By managing repetitive, manual, and administrative tasks with AI, MLR professionals focus on higher-risk content and improve quality and compliance.

Content leaders including Tareek Turner, associate director of HPRC and content personalization/automation at Boehringer Ingelheim, and Jason Benagh, director of global marketing operations at Moderna, partnered with Veeva to help shape an industry solution designed to transform MLR.

In conversation with Alexis Cohen, vice president, global content business consulting lead at Veeva, Turner and Benagh reflected on their experiences as early adopters of Vault AI in PromoMats. They discussed how their organizations approached implementation and adoption, what surprised them during the process, and the lessons learned from introducing AI into a highly regulated environment.

Alexis Cohen: What value did your organization see in being one of the first to adopt Vault AI in PromoMats?

Tareek Turner: For Boehringer Ingelheim, being an early adopter meant more than gaining access to new technology, it was an opportunity to inform its future. We partnered closely with Veeva Business Consulting to help shape how AI would be implemented into our business processes and rolled out to the broader industry.

Jason Benagh: At Moderna, innovation and a first-mover mindset are deeply embedded in our culture. Being among the first organizations to adopt Vault AI in PromoMats was a natural fit. Early involvement through focus groups and product discussions gave us confidence in the technology and helped us prepare for successful adoption.

Alexis Cohen: How did you approach alignment with legal and compliance stakeholders?

Tareek Turner: We made legal and compliance our partners from the very beginning, engaging them early and often. We instituted bi-weekly touchpoints to keep them informed on roadmap updates, ensuring they could flag concerns and confirm we were compliantly adhering to standard operating procedures.

Jason Benagh: AI was already a strategic priority at Moderna, with MLR teams actively exploring AI use cases and building prompts. Introducing AI in PromoMats was less about convincing teams to adopt AI and more about providing them with a purpose-built, validated solution for their workflows.

Alexis Cohen: What surprised you most about implementing Vault AI in PromoMats?

Tareek Turner: Initially, our implementation focused heavily on KPIs: reducing cycle times, rejection rates, and rounds of review. The biggest surprise was realizing that true adoption came when we shifted focus to our people and how AI could support their day-to-day work. As users saw AI eliminating manual, repetitive tasks, they recognized its relevance and value to their specific roles.

Jason Benagh: We partnered with Veeva to help guide our rollout and the implementation was more straightforward than expected. The bigger surprise came after implementation, when users found creative ways to use the tool that we hadn’t anticipated. As capabilities evolved over time, so did use cases. It was exciting to see teams continuously discover new ways to incorporate AI into their workflows.

For example, reviewers discovered they could interact directly with AI in PromoMats to instantly locate alternative text or specific language buried within a piece of content. Instead of manually combing through documents or switching between tools, they could find exactly what they needed without ever leaving the review workflow.

Alexis Cohen: What challenges did you encounter and what lessons did you learn?

Tareek Turner: The most difficult, yet important, learning was that AI is not a magic wand that can fix weak operational fundamentals. If you put garbage in, you get garbage out. Working closely with our agencies to ensure proper submission readiness and machine readability was crucial.

Jason Benagh: One challenge was helping our agencies adapt their workflows. Initially, they were running AI checks at the end of the content development process, which led to significant rework and delays. We worked closely with our agencies to move AI reviews earlier in the process, allowing teams to identify and address issues before submission. The shift required process changes upfront but ultimately improved content quality and efficiency.

Alexis Cohen: With AI in place, what role do humans continue to play in the review process?

Tareek Turner: These AI capabilities are designed to assist, not replace. AI provides recommendations, but MLR expertise remains essential. AI in PromoMats allows our teams to focus on higher-value, contextual work.

Jason Benagh: AI in PromoMats doesn’t take humans out of the loop. We use AI to handle tedious, manual tasks, so our experts can focus on strategic and risk-based decisions. It’s all about accomplishing more with the same headcount.

Alexis Cohen: How are you measuring the success of AI and how do you plan to scale?

Tareek Turner: We use AI dashboards to compare historical data against current performance, aiming to reduce cycle times, rejection rates, and rounds of review. For scaling, we use a “crawl, walk, run” methodology, starting with our larger, more mature brands to minimize business disruption, and then apply those learnings to the next therapeutic area.

Jason Benagh: We already average a low 1.4 rounds of review, so our success metrics are heavily based on adoption and value. We are identifying who is using the tool and how many AI comments are being pulled through. Because our company mindset is AI-focused, we plan to scale globally soon.

Alexis Cohen: Looking toward the future, what excites you the most about AI in commercial content?

Tareek Turner: Having worked in process management for over a decade, I am most excited about the potential these capabilities have to optimize our entire end-to-end process and see how they all work together to make us as efficient as possible.

Jason Benagh: I’m most looking forward to the Claims Agent. Managing a claims database has been a major pain point for years and leveraging AI to manage claims dynamically within the system is incredibly exciting.

Learn more about how Boehringer Ingelheim and Moderna transformed insights from implementing AI in PromoMats into tangible value.