Behind the Buzz—How Starbucks Approaches AI
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In this episode of The Intelligent Leader, host Shashank Garg sits down with Megan Brown, the Director for the Global Center of Excellence for Advanced Analytics and Data Science at Starbucks. With two decades of experience in analytics, Megan brings a wealth of knowledge in applying machine learning, statistical methods, and cognitive psychology principles to data-driven business strategies. She shares insights into how Starbucks navigates the complexities of international data systems, balances efficiency with trust, and the ways data and AI are reshaping business decision-making.
Megan delves into the challenges and opportunities surrounding data infrastructure, explaining how managing multiple data platforms without a unified view can create trust and usability issues. She discusses the importance of maintaining clear, accessible data for decision-making and illustrates how a slow, cautious approach toward adopting generative AI is helping Starbucks streamline routine processes. Megan also highlights the cultural shift required to integrate AI into business operations and underscores the significance of bringing stakeholders on board throughout this transformation.
Looking ahead, Megan offers practical advice for AI readiness, stressing the need for foundational data trust and responsible AI usage that aligns with Starbucks' mission and values. She advocates for starting with manageable AI projects that support efficiency before advancing to broader, business-facing applications. Megan's final thoughts encourage listeners to keep an open mind and adopt a balanced, optimistic view on AI's role in evolving the future of work.
Key Quote:
“You're not going to have one bot to rule them all. You're going to have a bunch of little bots doing their specific jobs. Maybe at some point you'll have a secondary layer, a tertiary layer, great, cool. But you need to build those little bots first, and you need to figure out if they need to talk to each other, how you need to track them, like, how you're maintaining them, all of these basic tech things that we don't know yet, right? And so you need that in place. Whatever AIOps is going to be, , before you really have thousands of agents talking to each other, potentially making, , prescriptive decisions for your company, right? Like, where's your checks and balances in that?”
- Megan Brown
Time Stamps:
- (01:11) Megan's Role and Responsibilities
- (03:41) Navigating the Hype Cycle in Data Science
- (07:06) Building Trust in Data and Analytics
- (15:02) Generative AI and Future Trends
- (24:54) Advice for Data and Business Professionals
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