The AI era has produced no shortage of entrepreneurs promising to automate work. However, for Hari Vasudevan the challenge was never simply replacing human effort. Rather, it was understanding why critical work continues to break down despite decades of digital transformation.
That perspective comes from an unusual career path. Before founding KYRO AI, Vasudevan built Think Power Solutions into a multi-state engineering and utility services company across 14 states. The business operated in one of America’s more challenging industries: electric utility infrastructure, where projects routinely involve thousands of workers and strict regulatory oversight.
In that industry, while companies had invested heavily in software, many of the most important operational decisions still depend on spreadsheets and manual follow-up. Information there tended to move slowly, as it does in. many places.
The experience fundamentally changed how Vasudevan viewed technology. Rather than asking how AI could replace workers, Vasudevan began asking why workers were spending so much time compensating for less optimal operational systems in the first place.
As Vasudevan explained in a recent interview, “Own a real-world problem before you own a model. Spend time with the people who feel the pain: line workers, superintendents, project managers and executives.”
For the entrepreneur, AI starts with understanding workflows, not algorithms.
That question ultimately became the foundation for KYRO AI. Instead of building another productivity tool, KYRO focuses on operational intelligence, leveraging AI to connect project data across organizations and to automate the admin work that historically prevented large infrastructure projects from moving efficiently.
Infrastructure industries may prove to be among AI’s biggest opportunities. Utilities and large contractors collectively manage trillions of dollars in physical assets while relying on operational processes that remain surprisingly manual. Even relatively small administrative mistakes can create significant downstream consequences.
Vasudevan knows this firsthand. Earlier in his career, a seemingly routine disconnect between field operations and finance nearly resulted in a loss approaching $10 million. Rather than viewing it as an isolated mistake, Vasudevan saw it as proof that operational systems were failing. The experience convinced him that “the gap between what happens in the field and what shows up in the back office is not just an operational inconvenience—it is a direct threat to a company’s cash flow and long-term health.”
One lesson continues to influence his approach: founders often confuse being early with being wrong. Markets evolve on their own timelines, and many strong ideas fail because execution and market conditions haven’t aligned. Rather than abandoning ambitious ideas after initial resistance, Vasudevan advocates testing assumptions.
That philosophy also informs how he approaches AI. While much of the AI conversation has centered on replacing knowledge workers, KYRO’s strategy reflects a different belief: AI delivers its greatest value when it removes operational friction that prevents people from doing their jobs effectively.
The approach may prove increasingly relevant as governments and private companies invest heavily in modernizing infrastructure. Large capital projects are becoming more complex, labor shortages remain persistent, and organizations face mounting pressure to complete projects faster without sacrificing safety or compliance. AI’s role in that environment may depend less on generating new information than ensuring the right information reaches the right people at precisely the right time.
Entrepreneurship itself follows a similar principle. He often encourages founders to evaluate major decisions through a deceptively simple question: “What’s the worst thing that can happen?” The exercise isn’t about avoiding risk; it’s about understanding it well enough to move forward confidently.
It’s advice shaped not by theory but by experience. As enterprise AI moves beyond chatbots and copilots into the physical economy, founders with firsthand operational experience may become some of the industry’s most influential voices.
For Hari Vasudevan, the future of AI isn’t simply about making work faster. It’s about making complex organizations work the way they were always supposed to.
