Handling Situations When AI Gets Something Wrong

Think you’re asking the right questions about AI?

In this episode of The Artificial Intelligence Show, Paul Roetzer and Cathy McPhillips tackle questions from our audience about AI adoption, from reimagining business models to managing risk in regulated industries. With candid insights, real-world use cases, and a few unexpected laughs, this “AI Answers” session reveals where companies are getting stuck, how to move past resistance, and the most critical AI skills professionals need to help shape their future.

Show Notes: Access the show notes and show links here

Timestamps:

00:00:00 — Intro

00:06:48 — Question #1: How have you seen AI get introduced to a financial services firm as they are highly regulated?

00:09:10 — Question #2: What guidance would you give leaders who want to fundamentally reimagine business models for the next decade?

00:15:08 — Question #3: How do your five steps for scaling AI apply when an organization has one person leading company-wide adoption?

00:19:28 — Question #4: How do you actually convince leadership to commit the resources and build true AI enablement across the business?

00:22:49 — Question #5: If a company isn’t actively using AI agents yet, do they still need to consider policies and guardrails around them?

00:26:22 — Question #6: For independents or loosely connected teams, is it even possible, or advisable, to share a single enterprise AI account? 

00:29:59 — Question #7: If a company doesn’t have an AI Council but leadership wants a vision for each department, where can someone start learning what AI can realistically do in each function? 

00:33:14 — Question #8: What are your best practices for training newer AI users?

00:35:06 — Question #9: How do you drive stronger engagement in AI enablement trainings when individual contributors already feel too busy with their day-to-day work to spend time learning AI?

00:36:16 — Question #10: What is the best way to handle a situation where AI got something wrong?

00:40:41 — Question #11: For new and early-career professionals, what essential skills or habits are most critical for proactively shaping the future with AI, rather than just reacting to it?

00:47:08 — Question #12: How should marketers weigh the legal and reputational risks of AI-generated content when companies can't always claim ownership?

00:49:50 — Question #13: Relative to all the expectations around AI, where have you seen it fall the shortest in practice?

00:52:06 — Question #14: A lot of people are learning how to prompt AI more effectively, but how do you also train and guide it to be used ethically in the workplace? 

00:54:56 — Question #15: Of the five essential steps to scaling AI, which step is the most challenging for organizations? What do you see leading organizations do differently? 

This episode is brought to you by Google Cloud: 

Google Cloud is the new way to the cloud, providing AI, infrastructure, developer, data, security, and collaboration tools built for today and tomorrow. Google Cloud offers a powerful, fully integrated and optimized AI stack with its own planet-scale infrastructure, custom-built chips, generative AI models and development platform, as well as AI-powered applications, to help organizations transform. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.

Learn more about Google Cloud here: https://cloud.google.com/  

This week’s episode is also 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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