The transition from designing physical buildings to shaping the digital future of Artificial Intelligence might seem like a leap, but for Priyanka Kuvalekar, it was a strategic evolution. Now a 31-year-old UX research lead at Microsoft in Redmond, Washington, Kuvalekar oversees the human experience behind Microsoft Teams Calling and its integrated AI features, according to Business Insider.
Her story is a roadmap for professionals who feel “locked out” of the tech boom because they didn’t study computer science. Having earned her initial degree in architecture in India, she successfully pivoted by focusing on how humans interact with technology rather than just the code behind it.
The Pivot from Physical to Digital Spaces
After a brief stint as a junior architect, Kuvalekar moved to Philadelphia in 2018 to pursue a master’s in user experience and interaction design. This move wasn’t just about a change in scenery; it was about shifting her design thinking from bricks and mortar to digital interfaces. Her journey through the tech ranks included roles at Korn Ferry and Cisco before she landed her current position at the tech giant in April 2025.
Her real breakthrough into the world of AI happened during her time at Cisco, where she led projects for Webex. To stay relevant, she didn’t just rely on her design skills; she actively pursued certifications in generative and agentic AI, learning the mechanics of Large Language Models (LLMs).
“I learned that you need to understand how to evaluate AI in practice. AI isn’t something you test once, and then it’s ‘done.’ It requires ongoing evaluation to ensure it continues to deliver trustworthy experiences,” according to Business Insider.
Why Human-Centric Design is the Future of AI
Kuvalekar argues that the biggest mistake newcomers make is thinking they need to be engineers to have an impact. Instead, she emphasizes that “fluency matters more than technical depth.” By understanding the limits of AI and how it recovers from errors, non-tech professionals can bridge the gap between engineering teams and the end-user.
Her work also highlights a critical social component: accessibility. She warns that while AI can automate tasks, it can also create new barriers for people with disabilities if not tested against assistive technologies like screen readers.
“Breaking into AI also taught me that you don’t have to build the technology yourself to make an impact, but you do need to understand it well enough to engage with it,” according to Business Insider.
For those looking to follow in her footsteps, Kuvalekar suggests building a portfolio that focuses on “AI-plus-people.” Rather than worrying about the backend, aspiring tech leaders should focus on the quality of the AI feature—asking if it stays within scope, handles interruptions gracefully, and remains inclusive across different languages. By documenting how these human insights influence technical decisions, professionals from any background can make themselves indispensable in the age of AI.