Скачать или смотреть AI Education, Personalized Learning, and the Future of Work

TL;DR

AI 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 workplace

In 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 Are

One 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 evolve

The 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 Work

We 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 changes how work gets done. Instead of just assisting with tasks,

AI begins to:

Automate multi-step workflows

Scale work that previously required human labor

Act as a force multiplier rather than a one-off toolWe agree that while much of this is still clunky today, the direction is clear: agents are becoming a core part of how work will be organized.

Personalized Learning Is the Future of Education

A major insight from the episode is that personalized learning journeys will define the next phase of education—especially in fast-moving domains like AI.

Erica describes how Sidecar uses AI within its learning environment to:

Act as a learning assistant

Answer questions in real time

Reinforce concepts

Help learners connect theory to application

This mirrors a broader trend: education becoming less about static courses and more about continuous, adaptive support.

The Psychology of Learning AI at Work

We talk openly about fear—fear of job loss, fear of falling behind, fear of not being “technical enough.” Erica makes the case that leaders have a responsibility to educate their teams, not just for organizational performance, but for people’s long-term career resilience.

From a psychological perspective, AI education:

Reduces anxiety by replacing uncertainty with understanding

Increases confidence and autonomy

Helps people see AI as a collaborator, not a threat

Spending even 20–30 minutes a day learning AI can quickly change how people see their own future at work.

Human Strengths Still Matter More Than Ever

One of my favorite parts of the conversation is where we zoom out to the human side of all this. As AI removes technical barriers, the differentiator becomes human qualities—creativity, resilience, judgment, adaptability, and the ability to ask good questions.

AI doesn’t replace these traits. It amplifies them.

Used well, AI allows people to overcome past limitations, work around weaknesses, and bring their ideas to life faster than ever before.

What Listeners Should Take Away

AI literacy is becoming a baseline skill. The people who thrive won’t be the most technical, but the most curious, adaptable, and intentional about learning how to work alongside intelligent systems.

Education—done thoughtfully and continuously—is the bridge between fear and opportunity.

Where to Find Erica

Erica is highly active on LinkedIn and can be found through Sidecar AI, where she and her team are building education-first pathways into AI for associations, nonprofits, and mission-driven organizations.