What Pharma Marketers Need to Know About Recent Gartner Predictions About AI and What It Means to Them

Faruk Capan, chief innovation officer at EVERSANA, recently spoke with Pharmaceutical Executive about a recent report from Gartner about the future of AI. According to the report, a significant number of proprietary AI platforms won’t last beyond 2029, and may fail even before that. Capan responded to the report while also offering his own views on the future of the tech.

Pharmaceutical Executive: Gartner’s latest AI research suggests that half of agencies’ proprietary AI platforms will become obsolete by 2029. Is this relevant to every agency platform?
Faruk Capan: Gartner's recent study certainly caught our attention. Directionally speaking, I think Gartner is right about most AI platforms. But it simply cannot be a blanket statement. What they’re cautioning against isn’t AI itself, it’s closed, agency‑only platforms that operate as black boxes. Platforms that are built narrowly for marketing execution, without integration into the broader enterprise AI ecosystem, are the ones most at risk. The future belongs to platforms that are open, interoperable, and enterprise‑ready, not those that try to compete with hyperscalers instead of partnering with them.

We’ve seen a lot of the big holding companies in the agency space building platforms like this. That’s why we took a different approach because we knew we needed to think client first.

PE:What should CMOs and brand leaders read into this report? Is it accurate in your opinion?
Capan: The biggest thing I’d recommend all CMOs do is own their AI strategy. Yes, outsourcing elements can be effective, but don’t outsource the whole thing. The Gartner study highlights the risk of dependency: if your AI platform only works inside one agency relationship, that’s a vulnerability. I agree with the core insight. AI decisions are increasingly being made at theenterprise level, often led by CIOs, and marketing needs to plug into that reality. Brands that win will be the ones that choose platforms designed to travel with them, not stay behind if relationships or vendors change.

PE: Not every platform is built differently. What’s your take having launched your AI Platform with Google that contradicts this Gartner study?
Capan: When we set out two plus years ago to really reimagine what an AI powered agency could be, we wanted to create something that was scalable, secure and client centric. We knew what we could do but also knew we couldn’t do it alone, and that’s where our partnership with Google really came into play. By partnering with Google Cloud, we ensured our platform benefits from ongoing innovation, scalability, and governance that no single agency could replicate alone. That approach directly addresses the obsolescence risk Gartner is warning about.

One advantage we believe we bring to customers is that our platform is end-to-end, it’s wholistic and complete. It reflects the full, tried-and-true pharmaceutical marketing workflow that has been established and effective over decades. We believe this brings unmatched differentiators for clients and longevity in the marketplace.

The other fact that can’t be under considered is the value in working hand-in-hand with Google.When they evolve their technologies, our platform evolves, which ultimately helps our customers.

PE:What values or attributes should brand leaders really look for when considering AI platforms for marketing?
Capan: There are four key values we think brand leaders should consider when looking at AI platforms. The first is portability, can this platform move with your organization as your needs evolve? Next is data ownership and governance. Who keeps control of the data, especially in regulated environments like pharma? In our model, clients own it all.Third, you should consider interoperability.Does your AI model integrate with enterprise systems and not just marketing tools? The right tools absolutely should. And finally, look for human augmentation—AI should elevate talent and decision‑making, not just automate output. I say it all the time, but our platform is 80% AI, 20% human in the loop. That last 20% is the most important part, because without highly trained, talented, passionate people, you’ve got nothing. You must make sure what any AI tool kicks out is relatable, authentic, and human approved. These attributes matter far more than flashy demos or proprietary claims

PE: Gartner cautions against scaling AI too quickly. What are the most common mistakes you see pharma marketing teams make when trying to operationalize AI?
Capan: In the last year, we’ve seen a lot of challenges and mistakes clients and prospects have faced on their AI journey. But I’d argue that the biggest mistake is starting with tools instead of use cases.

What do I mean? It’s really easy to say “we need to use AI, go use this”. Teams rush to scale AI for content generation or automation without first defining the value it can drive for an organization – and truly measurable value like better personalization, faster insights, or improved patient engagement. A second issue is underestimating change management that needs to occur. AI adoption isn’t just technical. Rather, it’s cultural, operational, and regulatory. Scaling before those foundations is in place creates noise, not impact. And if you just “jump into it,” you’re at a larger risk of confusing teams, negatively impacting quality, and causing more damage than good.Always start with the question “can AI help this process?” If the answer is yes, it's likely tools can build it.

PE: Looking ahead, what will differentiate pharma brands that simply “use AI” from those that gain a sustained competitive advantage from it?
Capan: I mentioned it earlier, but I think the difference will be integration and intent. Brands that treat AI as a tactical add‑on will see incremental gains at best. Those that embed AI into how they plan, decide, and learn across the enterprise will move faster and smarter over time.

But it won’t happen overnight, even as fast as things move. On our agency team, we continue to have training on tools like Gemini Enterprise 9+ months into our journey because there is so much to learn, especially as it evolves so quickly. Sustained advantage comes from continuous learning systems, strong governance, and platforms that evolve alongside the business. AI isn’t the advantage by itself; the way you operationalize it is.

But what also separates us are our expansion plans to areas like medical communications, market access, media offerings, and broader commercialization. This makes our platform even more wholistic and future proof.