#194: Agentic AI Timelines, Generalists vs. Specialists, Resume Tips, AI Learning Ownership, & Handling Model Updates

January 29 · 52 min · Episode 194

0:00-52:03

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Who actually owns AI learning: L&D, HR, or you?

Paul Roetzer and Cathy McPhillips break down the talent crisis, the rise of the generalist, and realistic timelines for AI agents. They explain the specific signals that tell you a pilot is failing due to human resistance rather than tech, why it is unlikely we will see a universal "GPT-4 moment" for agents this year, and the critical importance of maintaining human authenticity in an era of AI-generated content.

Show Notes: Access the show notes and show links here

Timestamps:

00:00:00 — Intro

00:06:11 — Question #1: Who owns AI learning: L&D or departments?

00:09:52 — Question #2: Hiring dedicated AI change management consultants.

00:11:54 — Question #3: Middle management’s role in normalizing adoption.

00:14:27 — Question #4: Signals a pilot is failing due to culture, not tech.

00:16:12 — Question #5: Balancing learning pace vs. rapid experimentation.

00:20:11 — Question #6: Hiring for critical thinking and AI skills.

00:23:31 — Question #7: Experience vs. Adaptability in talent acquisition.

00:25:35 — Question #8: Protecting and compensating AI leaders.

00:27:56 — Question #9: Using AI with confidential data restrictions.

00:30:35 — Question #10: Realistic timelines for AI agent advancement.

00:33:21 — Question #11: Managing model selection and "agent chaos."

00:37:24 — Question #12: The rise of the Generalist vs. Specialist.

00:41:14 — Question #13: Proving AI skills beyond certificates.

00:44:25 — Question #14: Trust and authenticity in AI content.

00:48:35 — Question #15: AI SDRs: Vendor questions vs. building in-house.

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.

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