Data integrity, executive skepticism, and turning AI-driven time savings into real gains—Paul Roetzer and Cathy McPhillips answer your questions from our latest Scaling AI class and offer informative, candid answers.
Show Notes: Access the show notes and show links here
Timestamps:
00:00:00 — Intro
00:04:51 — Question #1: How do we ensure data integrity, security, and privacy when we scale AI?
00:07:24 — Question #2: What exactly is an AI roadmap?
00:12:30 — Question #3: How can we maintain meaningful human oversight when AI systems operate at a speed that exceeds human comprehension?00:14:47 — Question #4: How do you feel about the impact of AI on highly regulated industries where adoption has been slower?
00:16:50 — Question #5: How does change management need to evolve in response to the rapid development of AI tools?
00:18:54 — Question #6: Changes are happening so quickly. How can professionals keep up? Are there trusted resources that stay current with innovations?
00:23:11 — Question #7: Do you have any tips for creating a tailored AI learning curriculum versus a “one-size-fits-all” approach?
00:24:51 — Question #8: For someone passionate about AI but not in a leadership position, how can i initiate change at an individual level?
00:28:42 — Question #9: How can you address resistance to change and skepticism toward AI, especially when the tools are available, but usage lags?
00:30:47 — Question #10: What’s your advice for someone leading a lean team who needs to pitch AI to executives with no time or interest in experimentation?
00:31:41 — Question #11: If a large organization has rolled out something like Copilot but no one is talking about AI or expanding beyond it, what are some tactical next steps to drive broader AI engagement?
00:34:21 — Question #12: As a director in higher ed, how can I motivate leadership to pursue something like Ohio State’s “AI Fluency” initiative?
00:38:00 — Question #13: Which AI tools do you like the best, and do certain ones work better for specific industries? How do you personally evaluate and select them?
00:40:49 — Question #14: How can startups or innovators best use Problems GPT, especially for category creation? Could you walk through an example?
00:45:54 — Question #15: What excites you most about AI’s potential for startups right now?
00:49:29 — Question #16: Have you seen companies using AI-generated efficiency gains to reinvest in people, like offering shorter workweeks or well-being benefits?
This week’s episode is brought to you by MAICON, our 6th annual Marketing AI Conference, happening in Cleveland, Oct. 14-16. The code POD100 saves $100 on all pass types.
For more information on MAICON and to register for this year’s conference, visit www.MAICON.ai.
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