At AdLab 2025, one highly anticipated panel brought together experts to discuss how bridging real-time optimization of claims and media data is driving a new era of Health Intelligent™ solutions. Moderated by DeepIntent Chief Analytics Officer John Mangano, “Unlocking Health Intelligence: Bridging Data, AI and Real-World Outcomes” featured Mike Bregman, Chief Data and Product Officer at Havas Media Network; Mike Caruso, SVP of Biddable Media at SSCG Media Group; Kate Gattuso-Duffy, Global Lead of Media Measurement, Optimization, & Web Analytics at Pfizer; and Bill Veltre, EVP and Head of Media at Deerfield Group. Collectively, their work spans pharma brands, media agencies, advanced analytics, and AI enablement. 

Together, they tackled some of the industry’s most urgent questions: How can we move faster without compromising privacy? How do we make AI practical and purposeful in our workflows? And most importantly, how do we stay grounded in the patient outcomes that matter most?

Here are five of the most actionable takeaways from their presentation.

Real-time optimization begins with foundational work in data unification. Today’s healthcare marketers must bridge fragmented dashboards and data siloes to unlock decision-driving insights.

Kate Gattuso-Duffy illustrated the challenge: “There are so many dashboards that we have to look at… Ideally, we stop talking about dashboards, and we start talking about how our data connects, and we use AI to drive decisions. How can we bring that data infrastructure together while all of the different data models have their own structure, their own piece?”

Expanding on this idea, Bill Veltre emphasized the importance of aligning internal teams around unified data. “When you’re talking about an internal analytics team that’s trying to do a mixed model, their data sets and what they’re looking at are ultimately very different than what my media team is ultimately optimizing off of,” he explained. “We want to make sure that we’re bridging the gap.” Doing so turns fragmented data into actionable insight. 

Rather than applying a one-size-fits-all approach, agencies are seeing success by designing AI tools and interfaces that match specific job functions. Mike Bregman outlined four key personas: planners, insights pros, buyers, and citizen data scientists. Each persona requires different types of AI support, from strategy planning to creative testing to writing code. 

“We’re not trying to unpack every use case,” he said. “We’re actually trying to think about the user. How do we help the user to be that much smarter with AI?” Mike Caruso expanded on this with an example from SSCG, sharing that they’ve “built specific AI agents for every one of those kinds of personas…You now have purpose-built applications that speak specifically to a data analyst or to a planner or to a biddable campaign manager.”

By aligning AI tools to specific user roles, teams are helping people work smarter and faster—augmenting human decision-making rather than overwhelming it.

Agility was a recurring theme throughout the panel, whether in planning cycles, optimization processes, or organizational training. Panelists agreed that one of AI’s core values lies in compressing what used to take weeks or hours into minutes.

Gattuso-Duffy captured this shift when she said, “Our process to create a report needed to take 95 steps before. Now it takes three.”

Reframing agility as not just speed but time reallocation, Caruso said, “If your data is automatically pulling or you’re able to get insights quicker, it should give you more time to learn about what your patients are truly looking for, what their challenges are, what the HCPs challenges are in prescribing, and really understand the brand.”

The next step for brands is to rethink their marketing operations, using automation and intelligent systems to shorten cycles and allow faster decision-making at every level.

As data connectivity and AI advance, so must legal governance—especially in healthcare, where innovation cannot come at the cost of patient trust or regulatory risk. The legal environment is evolving rapidly. As John Mangano put it, “While there certainly are AI privacy experts, the reality of it is…if any one of them went on a sabbatical, they’d come back with outdated knowledge.”

Amid this swirl of change, panelists identified some things that are already clear. “Guardrails are going to be really important,” said Gattuso-Duffy, recalling the years-long groundwork that preceded the shift from CTRs to outcomes-based metrics. “How do we test? How do we do cool new things?” The answer is “first testing with the data sets we feel confident are privacy compliant.”

Bregman noted that every one of Havas’ 300+ AI use cases includes a legal review. “There’s a lot of gray areas right now,” he said. “We’re figuring it out in real time.” 

Panelists affirmed what often goes unsaid: the main point of healthcare marketing is to improve patient outcomes. As tools evolve, measurement must evolve, too—from proxy metrics like impressions to healthcare metrics like new patient starts, treatment adherence, and HCP prescribing activity. 

Veltre put a fine point on it, saying, “AI is great, tech is nice, data is awesome, but at the end of all of that, it’s a patient, and we have to make sure that we don’t lose sight of that.” Gattuso-Duffy emphasized the satisfaction of seeing analytics translate into real impact. “There’s nothing better than…seeing a report and saying, ‘we increased our new patient starts by X amount and that helped us do X more things with the dollars.’”

With AI accelerating insight generation and campaign iteration, marketers are better positioned than ever to close the loop between media and health outcomes.

Real-time optimization in healthcare marketing isn’t a buzzword. It’s becoming a strategic necessity. But it requires thoughtful changes to how data is structured, how teams work, and how outcomes are defined. 

For healthcare marketers, the challenge is now to operationalize these insights: to build systems that are smarter, faster, safer, and above all, accountable to the real-world outcomes that matter most. 

Curious for more insights from AdLab 2025? Click here.