From Models to Decisions: How AI is Transforming Public Health, Pharma, and Care Delivery

An Interview with Nita Madhav, Senior Quantitative Epidemiologist, Verily

 

Artificial Intelligence is transforming healthcare, public health, and life sciences, but the real challenge is turning AI-driven insights into meaningful actions that improve outcomes.

 

I interviewed Nita Madhav, Senior Quantitative Epidemiologist at Verily, who shares insights on operationalizing AI across public health, pharma, and healthcare delivery.

 

1. Can you tell us about your background and how your work in epidemiology has evolved alongside advances in AI and data science?

 

I'm an infectious disease epidemiologist and computational modeler, and I have spent the last two decades working across public health, healthcare, and the life sciences. Throughout that time, I've watched the field move from relatively limited datasets and computational tools to an environment where AI can analyze vast amounts of information in near real time. While the technology has changed dramatically, the core challenge remains how to turn data and models into decisions that people can actually act on.

 

2. How is AI transforming decision-making across public health, pharmaceutical research, and care delivery, and where are you seeing the greatest impact today?

 

AI is helping organizations move from reacting to disease events toward anticipating them. In public health, that means earlier detection and situational awareness. In pharma, it means accelerating research and development. In healthcare delivery, it means helping clinicians and health systems navigate increasingly complex decisions. The biggest impact is in helping humans make better decisions faster.

 

3. What lessons can healthcare organizations learn from public health and epidemiology when deploying AI at scale?

 

One important lesson is that a good model alone is never enough. Public health has always operated in environments with uncertainty, incomplete information, and rapidly changing conditions. Success depends not only on building models, but also on establishing trust, communicating uncertainty, and integrating insights into real-world decision-making. The same is true for AI.

 

4. What are the key takeaways attendees can expect from your session on "From Models to Decisions: Operationalizing AI Across Public Health, Pharma, and Care Delivery"?

 

We'll explore a challenge many organizations face today: generating insights is often easier than turning those insights into action. Drawing on examples from public health, pharma, and healthcare delivery, I'll discuss what it takes to operationalize AI successfully. Attendees will leave with a practical way to think about moving from model outputs to decisions, and a clearer understanding of why organizational adoption often matters as much as model performance.

 

5. Looking ahead, what emerging AI trends do you believe will most significantly influence public health, drug development, and healthcare delivery over the next few years?

 

I think we'll see increasing focus on embedding AI directly into decision-making workflows rather than treating it as a standalone technology. We'll also see growing interest in multimodal systems that combine clinical, operational, genomic, and other forms of data. But just as important as technical advances will be progress in governance, trust, and implementation. The organizations that benefit most from AI will be the ones that learn how to integrate it effectively into the way people work.

 

Why This Conversation Matters

 

Nita's insights demonstrate that the true value of AI in healthcare lies not just in building powerful models, but in successfully integrating them into real-world decision-making across public health, pharma, and care delivery.

 

Join Nita Madhav at the Global AI in Healthcare Virtual Conference to learn how AI is transforming public health, pharma, and healthcare delivery. Connect with leading AI experts, clinicians, researchers, and healthcare innovators exploring real-world AI applications.

 

Register today: https://www.eventbrite.com/e/global-ai-in-healthcare-virtual-conference-tickets-1988295787223

 

Group discounts are available for organizations interested in sending multiple team members. Contact us for details. events@globalbigdataconference.com