Robin Sutara on Responsible AI, Governance, Diversity, and People Behind Data

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Future of Data and AI

Data Science Dojo

8 episodes

5 days ago

Throughout history, we've chased the extraordinary. Today, the spotlight is on AI—a game-changer, redefining human potential, augmenting our capabilities, and fueling creativity. If you're curious about AI and how it is reshaping the world, you're in the place. Our podcast dives deep into the trends and developments in AI and technology, weaving together the past, present, and future. This podcast explores the profound impact of AI on society, through the lens of the most brilliant and inspiring minds in the industry. Learn more about us: https://hubs.la/Q02q-dj20

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Robin Sutara on Responsible AI, Governance, Diversity, and People Behind Data

Future of Data and AI

56 minutes 56 seconds

5 months ago

Robin Sutara on Responsible AI, Governance, Diversity, and People Behind Data

🎙️ Future of Data and AI Podcast: Episode 06 with Robin Sutara

What do Apache, Excel, Microsoft, and Databricks have in common? Robin Sutara!

From being a technician for Apache helicopters to leading global data strategy at Microsoft and now Databricks, Robin Sutara’s journey is anything but ordinary. In this episode, she shares how enterprises are adopting AI in practical, secure, and responsible ways—without getting lost in the hype.

We dive into how Databricks is evolving beyond the Lakehouse to power the next wave of enterprise AI—supporting custom models, Retrieval-Augmented Generation (RAG), and compound AI systems that balance innovation with governance, transparency, and risk management. Robin also breaks down the real challenges to AI adoption—not technical, but cultural.

She explains why companies must invest in change management, empower non-technical teams, and embrace diverse perspectives to make AI truly work at scale. Her take on job evolution, bias in AI, and the human side of automation is both refreshing and deeply relevant. A sharp, insightful conversation for anyone building or scaling AI inside the enterprise—especially in regulated industries where trust and explainability matter as much as innovation.