Faruk Capan: AI is impacting every industry. I’ve seen it firsthand in the marketing and digital space, and I’ve told our employees, AI won’t replace you, but someone who understands how to use AI may.

So, what does this mean for GLP-1 care? I’m not a doctor, but I think where it has the greatest potential for impact is by removing friction points that can slow down access, overwhelm clinicians, and frustrate patients. Think about benefit checks or document-heavy workflows: AI can compress what takes hours into minutes while staying compliant. AI tools can help to find the most relevant education or action step for a provider or support team in real time. AI can help create and scale high-quality, empathetic communication without burning out staff.

The magic isn’t AI replacing clinicians; it’s AI doing the tedious, repetitive work so humans can focus on coaching, motivating, and managing the whole patient.

Aaron Uydess: It really starts with the patient and the data they generate every day – from their bathroom scale, their watch, their phone, and so on. Then, you layer in the HCP and the insights captured in their EHR. On top of that, pharmacies are critical since they touch both insured and cash paying patients. And finally, payers play a key role. When you knit all of this together, you get a fuller picture of things like abandonment, adherence, cost, and patient outcomes.

Faruk Capan: AI is incredibly powerful at designing a smarter “front door.” In the GLP-1 space, this could mean the technology could quickly capture medical history, check for comorbidities, analyse coverage options, and determine whether a patient is better suited for telehealth, in person care, or lifestyle support first.

In this case, patients could get routed to the right next step from the start, not bounced around. Layer in automated benefits verification and prior authorisation preparation, and you reduce a tonne of work for clinicians. For patients, it feels seamless. For care teams, it’s a relief. For the system, it’s the only scalable way to manage unprecedented demand.

Aaron Uydess: I’d focus on underserved populations. These are the individuals who often have the least access to care, the least ability to pay out of pocket, and yet they experience some of the heaviest impacts of obesity, higher Medicaid spend, rising insurance costs, lost productivity, and more – especially in the US.

We’ve already built strong solutions for well-insured patients and for those who can pay cash. Now, we have a real opportunity to serve the many, not just the few, by improving quality of life, reducing long term healthcare costs, and boosting productivity. And across Europe and other parts of the world, the same concept applies – serving those in need is both the right thing for society and will benefit companies.

Faruk Capan: We’re still missing several key pieces. The first is trusted data pipes. This includes consistent, privacy-safe ways to unify clinical, claims, socioeconomic, and affordability signals. All the sources are there, but how do you put them together to ensure all the data is safe and secure?

Second, we need better governance for AI operations. Clear rules for model oversight, bias monitoring, prompt auditing, and population-level performance tracking. Some industries are putting more guardrails here than others.

And finally, and this is connected to the second point, we need more workflow-ready rails so insights flow directly into patient services platforms, provider tools, and payer processes. We’re close, but the industry needs shared standards. When we align data quality, safety, and interoperability, AI becomes not just scalable, but equitable, and that’s when we’ll really improve care options.

Aaron Uydess: It’s a great question, but a complex one. I’d build a system that truly incentivises better health. That means making healthy food more affordable, improving education around obesity, and giving doctors stronger training. It also means expanding affordability options, shifting subsidies to reward healthy choices, and making it easier for individuals and families to choose better every day. GLP-1s would be part of the solution – but not the solution. They’d be a tool within a much broader, more holistic approach.

In the end, if we get it right, we can create a healthier world, but it’s going to take time and a lot of collaboration.

Faruk Capan: I don’t think there is a magic wand out there to solve a single challenge. Rather, it takes all of us working together. At EVERSANA, we’ve waived our wand and have built direct-to-patient platforms that help patients and could be very applicable to GLP-1 products. We’re moving the needle, and we’re showing the industry that we can remove access barriers that patients have faced.

It’s not easy, but it wasn’t easy to set up a true outsourced commercialisation model, and we did that. Sometimes you must dream the impossible to make it a reality.