About this episode
TL;DRAI literacy is becoming a baseline skill. This episode explores how organizations and individuals are actually building AI capability at work, with a focus on:* Self-directed learning and AI education at scale* Personalized learning journeys versus one-size-fits-all training* The shift from basic AI use to agentic workflows* The role of human strengths—creativity, judgment, and adaptability—in an AI-driven workplaceIn this episode, I’m joined by Erica Salm Rench, an AI educator and leader at Sidecar AI.Sidecar is an AI education platform and learning management system (LMS) designed to help organizations educate their employees on AI through self-directed learning. It combines structured courses, role-based learning paths, and hands-on use cases so individuals can build AI capability at their own pace while organizations raise overall AI fluency.Our conversation explores what AI education actually looks like beyond hype—how people are learning it, how organizations are rolling it out, and why understanding AI is quickly becoming a career differentiator rather than a technical specialty.AI Education Has Shifted from “What Is It?” to “How Do I Use It?”Erica explains that the conversation around AI in associations has changed dramatically over the last several years. Early on, organizations were hesitant to even talk about AI. Today, the question is no longer what is AI? but how can we use it to advance our mission, improve operations, and better serve our members?That shift brings a new challenge: helping people move from curiosity to competence in a way that feels approachable rather than overwhelming.Meeting People Where They AreOne of the strongest themes in our discussion is the importance of meeting learners at their current level of comfort and knowledge. AI education isn’t one-size-fits-all.This means combining:* Foundational AI concepts* Role-specific applications (marketing, events, operations)* A growing library of real-world use cases* Ongoing updates as tools evolveThe goal isn’t to turn everyone into a AI engineer—it’s to help people understand what’s possible and apply AI meaningfully in their day-to-day work.From Prompting to Agentic WorkWe spend time talking about the evolution from simple AI use cases—like writing emails or summarizing content—to agentic AI, where systems take action on a user’s behalf.This shift matters because it fundamentally chang
