Episode

290. You're Not Behind (Yet): How Leaders Need To Adapt With AI | Danielle Clark

Podcast
the Learn-It-All™ podcast
Published
Apr 21, 2026
Duration seconds
3001
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not_requested
Canonical source
https://www.learnit.com/podcast
Audio
https://episodes.captivate.fm/episode/1cb6fefc-39c2-43e3-8ae6-687a0b4e2b75.mp3
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Summary

AI is not waiting for your team to catch up. If leaders keep treating artificial intelligence like a side experiment instead of a business shift, they are going to fall behind. In this episode of the Learn-It-All™ podcast, Damon Lembi sits down with Danielle Clark, VP of Global Talent at eBay, to unpack what AI leadership actually looks like inside a global company, and why the real challenge is not that the tech is not ready. It is that most humans are still learning how to work with it. Danielle breaks down how leaders can guide teams through AI adoption, workplace transformation, and the future of work without creating panic, resistance, or empty hype. She explains why the best leaders are not starting with shiny tools. They are starting with the core problem, the workflow, and the outcome they are trying to achieve. From AI upskilling and employee enablement to AI in recruiting, onboarding, coaching, and learning and development, this conversation explores how organizations can build more capacity, move with more velocity, and still keep the human side of work front and center. Danielle shares what it takes to create momentum at scale, how eBay approached AI essentials and ambassador networks, why human judgment still matters most, and what leaders must do now if they do not want their teams and themselves to get left behind. In This Episode, You’ll Learn: Why the strongest AI leaders are not obsessing over every new tool, but are instead leading with confidence, empathy, vulnerability, and clarity through constant change Why Danielle says the companies getting traction are the ones willing to throw everything up in the air and rethink workflows from the ground up, instead of just tweaking old processes Why framing AI around tasks, workflows, and outcomes reduces f…