Scaling Practical AI Across Commercial Teams

EVERSANA’s AI journey began with classic predictive modeling  but its evolution into an enterprise-wide strategy is rooted in something deeper: a trusted data foundation and rigorous change management.  

Drew McCormick, Head of Data & Analytics at EVERSANA, explains how the organization is moving from gut instinct to data-guided decisions across a diverse portfolio: from agency marketing and strategy to patient services, benefits verification, field teams, and distribution. The focus is not just on tools; it’s on adoption at scale, human‑in‑the‑loop validation, and embedding technical talent with frontline teams to ensure AI recommendations are actionable, context‑relevant, and compliant.  

Looking ahead, Drew sees high‑impact growth in rare disease and oncology, including earlier patient identification and ambient, point‑of‑care intelligence to help clinicians and patients move faster through the healthcare system. 

Listen to the full episode of the Life Sciences DNA Podcast. 

How does EVERSANA ensure AI tools work in real‑world healthcare and commercial settings? 

Drew notes that AI only delivers value when it aligns with the realities of day‑to‑day work. Our team embeds functional reviewers, product testers, and technical partners directly alongside field teams, patient services agents, and benefits specialists to validate outputs in real time. This human‑in‑the‑loop approach ensures each AI recommendation fits the moment — whether supporting a doctor visit, guiding a patient through a therapy access hurdle, or helping a call center agent anticipate next steps. By co‑creating solutions with users instead of pushing technology from the top down, we build AI that feels intuitive, trustworthy, and genuinely helpful. 

What role does bottom‑up innovation play in scaling enterprise AI? 

To capture real pain points and accelerate adoption, our team launched an internal submission program that generated more than 150 AI use‑case ideas in just a few weeks. This model empowers employees across the business to propose opportunities where AI could remove friction, improve decision‑making, or streamline workflows. The result is a powerful feedback loop: teams feel ownership of the tools they use, and solutions evolve directly from frontline insights rather than abstract assumptions. 

Where will AI drive the greatest impact for patients and providers? 

Drew highlights rare diseases and oncology as major areas of opportunity over the next two years. AI and large language models can reveal patterns across disparate data sources, helping identify at‑risk patients months earlier, even before key biomarker testing. As clinical workflows evolve, he expects AI to move even closer to the point of care through EHR‑integrated agents and ambient tools that reduce administrative burden and support faster decision‑making for both clinicians and patients. 

Explore EVERSANA’s Data & Analytics capabilities.

Connect With An Expert!