Intelligencia AI’s CEO: Why ChatGPT Made Selling AI to Pharma Harder, Not Easier

November 2022. ChatGPT launches. The AI community erupts. Suddenly everyone’s an AI company. It’s the moment every AI founder has been waiting for, right?

Not for Dimitrios Skaltsas.

In a recent episode of Category Visionaries, Dimitrios Skaltsas, CEO and Co-Founder of Intelligencia AI, shared a perspective most AI founders won’t admit: ChatGPT made his job harder.

“It turbocharged all these, it kind of accelerated something that already started being in motion during COVID And self dept is not necessarily always a positive impact, right?” Dimitrios explains. “There are pharmaceutical companies actually are kind of shutting down or shutting out subject from their organizations because they’re like, okay, we cannot trust it yet, so don’t use it literally.”

While tech companies were racing to integrate ChatGPT, pharmaceutical companies were banning it. And that skepticism bled into every AI conversation.

Here’s how Intelligencia AI navigated selling serious AI during the noisiest hype cycle the industry has seen.

The Real Watershed Moment (It Wasn’t ChatGPT)

To understand why ChatGPT complicated things, you need to understand what actually transformed pharma’s attitude toward AI: COVID.

“The water said moment in our space in pharma was Covid,” Dimitrios says. “When it comes to, you know, pending the part time of how people do drug development and drug discovery, it’s a space where on average it takes about ten years for a drug that is in clinical trials eventually to make it to the patients, make it to market. And during COVID it was shown that whoa, can be done much faster.”

COVID proved pharmaceutical development could accelerate. That’s when the sector started investing in AI. But there’s a crucial difference: COVID-driven AI adoption was grounded in solving specific problems. ChatGPT was hype.

When Acceleration Becomes Noise

ChatGPT didn’t create interest in AI—it created noise. And in conservative industries, noise is toxic.

“There’s a lot of promise. There is a lot also of noise,” Dimitrios says. Suddenly Intelligencia AI wasn’t just competing with other serious AI companies. They were competing with every SaaS company that slapped “AI-powered” on their marketing, consultants selling “AI transformation,” and viral ChatGPT demos that had nothing to do with pharma.

The conversation shifted from “Can your technology solve our problem?” to “Why should we trust AI at all?”

The New Question Every AI Founder Faces

Pre-ChatGPT, conversations focused on demonstrating their specific solution. Post-ChatGPT, a new question appeared: “Why should we trust you?”

“Yes, AI is promised. Yes, we see the potential, but is it mature?” Dimitrios explains.

This is the hidden cost of hype cycles: They lower trust across the entire category. For founders selling complex technology to conservative buyers, you need to ride the wave of increased interest while distancing yourself from the noise making buyers skeptical.

The Depth vs. Noise Strategy

Intelligencia AI’s solution? Go deeper while others went wider.

“People who use both or multiple solutions, you know, they turn, tell us, okay, you’re not real competitors, because you do. Actually, I go deep where some of the cases, it’s a touch AI,” Dimitrios says.

When the market gets saturated with surface-level solutions, depth becomes your differentiator. While competitors added “AI-powered” to existing features, Intelligencia AI built patented methodology specifically for pharma’s drug development risk.

“There is some overabundance of AI and people have to cut through the noise,” Dimitrios notes. “Ultimately, it increases the burden of proving that you are the better solution, but that makes you stronger.”

The Explainability Advantage

ChatGPT’s black box nature became an advantage for Intelligencia AI. ChatGPT is impressive but opaque. For pharmaceutical companies making billion-dollar decisions? That’s a dealbreaker.

“In our case, again, in our industry, explainability is, goes a long way. People appreciate it. They dislike black boxes,” Dimitrios explains. “These are highly sophisticated users who want to understand and actually embed AI into their own pattern recognition, into their own decision making.”

Intelligencia AI had built for explainability from day one. When the hype cycle hit, this became their moat.

The Messaging Shift: From AI Company to Risk Solution

One smart move during the hype cycle: They stopped leading with AI.

“We have definitely more nuanced and more mature messaging now in the market,” Dimitrios says. The focus shifted from “We’re an AI company” to “We solve pharma’s drug development risk problem using AI.”

When everyone’s screaming about AI, being another AI company makes you noise. Being the company that solves a specific problem using AI—and can prove it—makes you signal.

The Long-Term Play: Consolidation

Dimitrios sees a bigger shift coming: “Another implication of what you’re saying is that a lot of money flow flew into the space and at some point likely there will be some consolidation. So there are companies out there who cannot necessarily continue as standalone companies because they haven’t necessarily found the appropriate go to market emotion and don’t generate enough revenue.”

For companies that built real solutions before the hype and maintained discipline during it, consolidation is opportunity.

The Framework: Navigating Hype Cycles in Conservative Markets

Here’s what Intelligencia AI’s experience teaches about selling during category hype cycles:

When hype increases, double down on proof. Everyone else is making bigger promises. You show bigger results.

When noise increases, go deeper. Surface-level AI is getting crowded. Build something that takes years to replicate.

When trust decreases, prioritize explainability. Black boxes might work in fast-moving markets. They fail in conservative ones.

When messaging gets generic, get specific. Don’t be “AI for pharma.” Be “the solution to drug development risk assessment.”

When capital floods in, maintain discipline. Prove your business model works before scaling it.

Dimitrios’s perspective on the AI hype cycle isn’t pessimistic—it’s realistic. “The world is changing. There will be more and more AI embedded in the workflows of pharmaceutical companies in our industry and more broadly across industries,” he says. “As with any probably new technology, you know, it will go through its waves.”

The founders who win aren’t the ones who ride the hype the hardest. They’re the ones who build real solutions that matter when the hype fades and buyers get serious about results.

ChatGPT made selling AI harder because it made everyone a skeptic. But skeptics don’t want less AI—they want better AI. And that’s exactly where the opportunity is.