It’s safe to say that the pharmaceutical industry’s relationship with technology has evolved significantly over recent years. Although many criticized the industry for being slow to adopt the digital revolution, the opposite can be said for artificial intelligence (AI).
Once AI hit the scene, the pharma and biotech industries quickly embraced the technology and began finding ways to use and implement it. For Abid Rahman, head of AI Agency and innovation at EVERSANA, this is the next chapter in an ever-changing technological landscape.
“When I started,” he says, “the technology landscape was, of course, very different than it is today, but there were still some significant shifts happening. Social media was brand new to pharma. Video in a YouTube format was brand new. People were changing how they got information online versus the more traditional, pre-internet approach. So, we had some big challenges around ensuring that everything happened compliantly when it came to social media and video.”
He continues, “Then came the iPhone moment, then the iPad moment. Then there came the broader shift from desktops to smartphones. People were suddenly getting all their information on their mobile devices, and we had to figure out how to do all of that compliantly. As pharma started building apps to support patients, making sure those things happened in a user-friendly and compliant way became critical.”
AI is old and new again
For Rahman, AI is not a new part of the technological landscape. Various forms of AI have been around for decades, and it’s an element of technology he says he’s always embraced. However, he is quick to point out that today’s AI is very different from the AI solutions he built when he entered the pharma industry.
He says, “Traditionally, AI in pharma was primarily about machine-learning approaches: forecasting, understanding who to target, how to target them, and when. That has evolved considerably. When people talk about AI now, they’re mostly thinking about generative AI (ChatGPT, Claude, Gemini, etc.). That’s become the new face of AI and how we interact with it, and pharma is no different from any other industry in that respect.
“And then things shifted again in the last year or so toward what we call the agentic approach,” he continues, “which sits on top of generative AI. Where we were previously asking AI questions and getting answers, we’re now asking AI to actually do things for us. Not just ‘give me a response,’ but ‘create a PowerPoint deck with that response.’ Not just ‘give me information,’ but ‘go find the best clinics in my area’ or ‘tell me which doctors I should be seeing.’ Agents can do those things for patients, for doctors, for anyone in the industry.”
Entering the industry today
Early in his career, Rahman says he received an important piece of advice. According to him, he was taught that the most important thing to worry about isn’t the finances or even the technology. Instead, the key focus should be on people.
He says, “We serve people. We should never lose sight of that. Doing good for society, doing no harm, that should always be the core principle. You might succeed temporarily without it, but you won’t build anything lasting. That’s what I learned early on, and it’s still my North Star.”
“You might build something very quickly today that becomes irrelevant in a matter of months because the environment has already shifted.”
When it comes to providing advice of his own, he says, “Agility has always been important, but it’s more important now than ever. You might build something very quickly today that becomes irrelevant in a matter of months because the environment has already shifted. Being open-minded, being able to absorb a vast amount of rapidly changing information, and being willing to project and then adjust, that’s what it takes right now. Anyone who isn’t embracing change is going to be left behind.”
Real-world use cases
Rahman’s work is focused on delivering the most important aspect of AI: real-world use cases. The industry has made many promises about AI’s impact, and it’s time to start showing results.
One example Rahman highlights is EVERSANA’s AI Agency platform, which is designed to help pharmaceutical companies accelerate content creation, campaign execution, and customer engagement. Rather than using AI as a stand-alone tool, the platform combines generative AI, automation, and agentic workflows to support real-world commercial and medical use cases across the enterprise.
“What excites me most about the AI Agency platform,” he says, “is that it moves beyond experimentation and delivers measurable business value. We’re not just helping teams generate content faster. We’re enabling organizations to scale personalized engagement, automate complex workflows, and transform how content gets created and delivered. That’s where AI begins to truly transform the industry.”
