Bridging AI, Business Analytics and Leadership

Image

Tech investor, entrepreneur and UC Davis MBA alumna Shilpi Sharma recently visited our MSBA Advanced Statistics course to deliver a masterclass on how to bridge the gap between data, business, and AI-driven innovation.

Sharma has focused her career on solving societal challenges through AI and data. She co-founded Kvantum, an AI-based consumer intelligence and marketing attribution company, which grew into a multimillion-dollar business.

In 2021, Kvantum was acquired by Yum! Brands, an American multinational fast-food corporation, where she served as chief strategy officer until 2024. Today, Shilpi serves on the Investment Committee for Tin Alley Ventures, a $125M fund backing deep-tech startups, and is an investor and limited partner at Portfolia, a firm focused on women’s health, sustainability, and longevity. She has advised major companies, including Apple and Google, and is dedicated to technology-driven innovation.

Sharma, a 2007 MBA graduate, played a pivotal role in the founding of the UC Davis MSBA program. Her firm conducted a conjoint analysis that helped determine the location of the program in San Francisco. The program welcomed its inaugural class in the fall of 2017.

As a guest lecturer, Sharma shared several gems about how to use AI effectively, both from a technical and strategic perspective.

Solving Problems, Bridging Business and Driving Innovation

• Addressing Real-World Challenges with AI

Sharma emphasized that AI’s value isn’t always glamorous, but it can profoundly impact industries and solve overlooked challenges. For example, in her work with Yum! Brands, she leveraged AI to create content personalization strategies that significantly improved customer engagement. This highlights how AI can drive practical, impactful solutions when paired with clear business goals.

• Bridging Data Science and Business

One of her key messages was that data scientists must understand the business context. "Just because you have the data doesn’t mean you can use it in an algorithm," she said, emphasizing the importance of asking the right questions during data collection, model training, and deployment. Her perspective reinforced the need for alignment between technical capabilities and business objectives.

• Innovation Through Collaboration

Sharma’s belief that ecosystems need to work better together—from founders and investors to the end users—was a powerful reminder that collaboration is key to scaling innovation. She shared examples of how AI workflows, from data collection to model maintenance, thrive in environments where teams align on goals and execution.

• The Importance of Incremental Value

In discussing AI model deployment, Sharma stressed the importance of showing incremental value. Whether it’s through testing (like kiosk recommendations) or ongoing monitoring, the goal should always be to demonstrate a clear, measurable impact.

Image

Navigating Careers in AI and Analytics

I am deeply interested in data and its applications since I work at a company bringing AI to its customers. So, hearing Sharma's story was incredibly motivating.

Sharma’s ability to connect high-level strategy with actionable insights reminded me that the true power of AI lies in its ability to make a tangible difference.

Whether it’s helping to locate a graduate degree program or driving personalization for a global brand, understanding the combination of data and thoughtful application is essential to be an industry leader.

Beyond the technical takeaways, her journey as a founder and global advisor also left me reflecting on my aspirations. Her advice to “think bigger” about the impact we can make through technology was the perfect note to end on. It was a session that will help shape how we approach our careers in AI and analytics.