Building High-Impact Data Teams in an AI-Driven World
No two data organizations are the same—where a data team sits within a company fundamentally shapes its priorities, influence, and definition of success. In an AI-driven world, where data is more critical than ever, understanding how to structure and operate data teams for real business impact is key. Drawing from my experience leading data teams across different organizational structures—reporting into finance, product, engineering, and now as a standalone function—I’ll break down the pros and cons of each model and what it means for how data professionals can drive value. While foundational needs remain mostly consistent across organizations, the way data teams prioritize and execute must adapt based on business context. Whether you're an IC evaluating your impact, a manager structuring your team, or a leader navigating AI’s evolving role in data work, you’ll leave with a clearer understanding of how to build and position a data team for success. Most importantly, you’ll learn how to align your work with what the business truly cares about—no matter the company’s structure or the latest AI advancements shaping the field.