Artificial Intelligence (AI) is rapidly evolving from a promising tool to a core capability in healthcare marketing. As the industry prepares for 2026 and beyond, experts are examining what AI-powered audience intelligence truly means - not just in concept, but in real-world application.
In a recent MM+M Podcast and accompanying article, Jamie Avallone, Chief Data Officer, and Iris Lin, Product Science Lead, shared their perspectives on the future of audience intelligence, discussing how to move beyond surface-level analytics toward strategies grounded in behavioral insight.
AI’s Value Begins with the Right Data
While AI and Large Language Models (LLMs) are reshaping how life sciences organizations understand and communicate with healthcare professionals and patients, the impact of these technologies hinges on the quality and relevance of the data powering them.
Traditional approaches often rely on siloed or retrospective datasets, limiting the ability to generate actionable insights. As Iris noted during the discussion:
“It’s data first - but also precision, and identifying the right problem with the data you do have.”
The conversation highlighted several key principles:
Behavioral data is essential for training AI systems that reflect real engagement patterns
Holistic, longitudinal signals outperform isolated data points in predictive modeling
Data strategy and problem framing are as important as the algorithms themselves
Moving Beyond Metrics
Healthcare audiences are complex, and traditional KPIs no longer offer a complete picture of how, when, and why individuals engage. Iris emphasized that organizations must shift from looking at outcomes in isolation to examining the journey that leads to them.
This more sophisticated form of audience intelligence supports:
Identifying decision-making drivers and content preferences
Tracking shifts in behavior across time and channels
Informing real-time content and channel strategies with predictive insight
Rather than relying on assumptions or static personas, organizations can build a clearer, behavior-based understanding of how their audiences evolve.
Human Insight Still Matters
Despite the growing capabilities of AI, the discussion reinforced that human oversight remains essential. Domain expertise provides the context AI lacks - especially in a highly regulated, emotionally complex field like healthcare.
Jamie explained that “AI can scale insights, but it doesn’t replace strategic thinking. The best results come when technology and expert interpretation work together.”
Key considerations included:
The need for domain-specific knowledge to guide and validate AI outputs
The role of cross-functional teams in ensuring relevance and compliance
The importance of maintaining ethical standards and data stewardship throughout
Looking Ahead to 2026
As the healthcare industry becomes increasingly data-driven, audience intelligence is moving from retrospective analysis to proactive strategy. Those investing in high-quality behavioral data, purposeful AI integration, and expert interpretation are better positioned to anticipate audience needs and drive more relevant engagement.
For organizations seeking to modernize their communications approach, the path forward lies not just in adopting AI - but in aligning it with strategic clarity and real-world insight. This reflects Intelligent Commercialization™ in action - connecting proprietary data, AI, and platforms like Cognitev™ and Predictev™ to turn behavioral signals into smarter decisions.
The full conversation is available in the MM+M Podcast episode here.