Scale Changes Everything

For John ‘JG’ Chirapurath, MBA ‘01, the library was never just a place for books—it was an entire system. Long before leading data and AI efforts across global technology companies or helping scale startups, Chirapurath’s earliest memories involve walking to the library with his grandmother. Watching her methodically sort through an abundance of books, returning them to precise locations, he began to also see order where others only saw stories. 

For Chirapurath, it was a system; a structured set of rules, columns and relationships that makes it easy to find things. An early introduction to seeing data in the world around him shaped how he learned to think about information, systems and scale—a fascination that ultimately led him to the University of Chicago for his MBA and into a career defined by building at scale, a journey he continues today as the president of DataPelago. 

Learning the Cost of Scaling

A "lifelong technologist," Chirapurath's enthusiasm for the topic deepened at the University of Maryland. As he pursued a graduate degree in computer science, he came to appreciate engineering not just as a discipline but as a craft. "It is vital that you love what you are doing," he said. For Chirapurath, that love came from discovering the freedom to explore—a shift that shaped how he approaches work to this day.

From there, his future and his career started to take form, and at The University of Chicago Booth School of Business, Chirapurath co-founded his first startup and with it launched his entrepreneurial journey. His goal in business is a simple one: To grow simple ideas and conceptual solutions into constructive, real-world applications. He first set out to do that through Sarvega.

Sarvega pioneered intelligent data center switches before being acquired by Intel—a journey now preserved as a Harvard Business School case study. But for Chirapurath, the outcome was more personal than academic.

"Building a startup is like building your perfect home. You find a piece of land, study it, and design every detail. Then a much larger company comes in and buys it from you. At that point, the dream isn't yours anymore. Where you planned a patio, there's now a wall. Where you saw French doors, there's a window. It becomes their dream," he reflected. "But the house still stands. And you learn you can build another."

What Chirapurath really took away from Sarvega was clarity. He had a talent for scaling ideas and bringing products to market. That understanding set the trajectory for everything that followed.

In 2017, as cloud computing accelerated at Microsoft, Chirapurath was asked to lead data and AI at Azure—a business that would grow to serve millions of enterprises. He later joined SAP's executive leadership, overseeing the company's data and AI portfolio. At each turn, he focused on mastering growth rather than just ownership.

Today, he has a clear understanding of how he fits into the world of business and technology. “The only thing I am is a student of scale”, Chirapurath shared. 

Applying Scale

From enterprise platforms to startup efficiency

After decades spent scaling systems inside the world's largest technology companies—most recently as Chief Marketing and Solutions Officer at SAP—Chirapurath is applying that same discipline to a startup opportunity. The problem he is working to solve is that cloud infrastructure is evolving faster than the tools used to process data within it.

The shift, he notes, has already happened. "If you look at the largest share of cloud spend today, it really all comes down to data processing," he states. This holds true because a lot of today's data processing still relies on frameworks and approaches developed more than a decade ago. The misalignment is an inefficiency that continues to drive up costs. "It's like taking a race car, pulling out its engine, and putting an average engine inside it," Chirapurath explains. 

Recently appointed as the president of DataPelago, Chirapurath is working to change that by making data processing economical. The company built a universal engine that works with any data type, framework, and hardware. Most enterprises today run data workloads designed for infrastructure that no longer exists—like running modern software on a decade-old operating system. DataPelago optimizes execution for what's actually there, improving performance by as much as 10x and cutting costs by as much as 80%.

"I want a shot at changing the world," he said. "And I think I can do that." 

As AI models grow more complex and data-hungry, the inefficiencies Chirapurath aims to solve become bottlenecks not just for businesses, but for responsible AI development itself. It's a problem he's been thinking about for years, dating back to his time at Microsoft.

The Ethics of Scale

It is clear that decades of working at scale have shaped Chirapurath’s view of AI’s risks and responsibilities. 

AI mirrors human behavior, which means it inherits the same flaws. 'It is how what you teach a child manifests as that child's expression of themself in the world,' he explains. Bias and ethics become critical when AI affects real people directly. Chirapurath learned this early in his time at Microsoft and at SAP, where he was added to the company's ethical AI initiative. There, he helped establish two core principles of ethical AI that still guide his thinking: 

• Transparency by design. Systems must be built to explain how they reached an answer.
• Fairness by design. Systems must be built to identify and eliminate bias from the outset.

He sees the automation that AI exemplifies not as replacement, but as evolution. "You use the tools available to do your job 10× faster, free up time, and push yourself. That's what human evolution looks like." It's a view that aligns with the Center for Applied AI's mission to develop and apply AI responsibly for social benefit, a focus on ensuring technology serves people, not the other way around.

Facing the Future

Chirapurath's philosophy is straightforward: Just because you are afraid of something doesn't make it go away. Embrace it and see how you can use it to reach your goals and aspirations.

Chirapurath remarked, "It isn’t coming. It's already here. So you might as well learn how to use it to your benefit."

At the University of Chicago, students are in a unique place to push themselves. If you're lucky enough to go to an institution like Chicago, Chirapurath believes, you owe it to the ethos and the history of the university to continue that journey of discovery, inquiry, and ultimately, to make yourself stronger and better.

His advice to students? Face the opportunities that AI brings. Grow with it. Don't run away.