The New Instructional Designer: What AI Changes and What It Doesn’t

Welcome & Series Roadmap

Hello, and welcome to the Designing with Love Podcast. I am your host, Jackie Pelegrin, where my goal is to bring you information, tips, and tricks as an instructional designer. Hello, instructional designers and educators. Welcome to episode 107 of the Designing with Love Podcast. As we move through our 2026 season, where we blend solo episodes and guest conversations, I'm also taking you through a special 12-episode solo series called the AI Ready Designer. We're keeping it practical, clear workflows, simple guardrails, and human-centered learning that doesn't get lost in the hype. In today's episode, we're starting with the big picture: what AI is changing in instructional design, what's staying the same, and where your role becomes even more valuable as tools make content faster and easier to produce. By the end, you'll have a simple way to think about your role so you can focus on the work that matters most. So grab your notebook, a cup of coffee, and settle in because we're going to make this feel doable. Before we jump in, a quick note. This is a 12-episode arc, and each episode builds on the last. In this 12-episode AI ready designer series, we'll move through five AI ready checkpoints each time. So you always leave with something practical you can apply right away. Alright, let's jump into checkpoint one. Here's what's changing speed and volume. AI makes it easier to draft learning objectives, outlines, quiz questions, scenarios, rewrites, summaries, basically the first pass of content. And that's helpful. But the real shift is this. Because content is easier to produce, there's a growing expectation that learning should be faster, cheaper, and good enough. So you might start hearing things like, can we just have AI generate the course? This should be quick, right? We already have the information. Just turn it into training. And if content is what people think we do, then that can feel unsettling. But here's the anchor for the whole episode. AI increases output. It does not guarantee impact. That brings us to what doesn't change. No matter what tools exist, instructional design is still about people and performance. The core questions don't change. Who are the learners? What do they need to do differently? What is getting in the way right now? What does success look like on the job? And how do we know it worked? AI can help generate content, but it can't truly understand your learner's context, such as culture, constraints, motivation, trust, and the reality of how work gets done. So when AI feels overwhelming, come back to this. The purpose of instructional design doesn't change. So here are four things that never automate empathy, context, trust, and accountability. Now let's talk about the risk because faster isn't always better. When content becomes easy to generate, mistakes become easy to scale. And in learning design, skill mistakes aren't just annoying. They can be expensive. They can harm credibility, and sometimes they can even create compliance or safety issues. I've seen this before in my work, so I want to tell you that it happens. Here are a few common risks when AI is used without guardrails. Risk number one, polished but wrong. AI can produce something that sounds confident, but it can be inaccurate, incomplete, or outdated. Risk number two, generic training that ignores the real problem. If we jump straight into course building, we often miss the real barrier, like unclear processes, bad tools, missing incentives, or poor manager support. Risk number three, accessibility and inclusion issues. AI generated content can accidentally introduce confusing language, culturally narrow examples, non-accessible formatting, or scenarios that don't fit your learner population. And finally, risk number four, the copy-paste credibility trap. If learners sense something that is shallow or generic, trust drops fast. And once learners stop trusting the training, it becomes harder to get buy-in, no matter how good your next course is. So here's a simple practical guardrail you can use starting today. If it's high stakes, it's human reviewed, always. That means areas like policies, safety, compliance, medical, legal, sensitive HR topics, and anything that could impact someone's well-being or employment, AI can assist, but it doesn't get the final say. Now, if that's the risk, what's the opportunity? Here's the good news. AI makes content production cheaper, so learning strategy becomes more valuable. This is where your role upgrades. You become the person who brings clarity to the work by aligning stakeholders on the real goal, designing practice and feedback, planning for transfer to the job, transfer planning, setting quality standards, and measuring what changed, not just what was completed. In the AI era, the designers who stand out aren't the ones who type faster. They're the ones who can say, sure, we can generate assets quickly, but first let's make sure we're solving the right problem with the right experience. So here are three role upgrades you can keep in your ID toolkit. Upgrade number one, from builder to learning architect, you're designing the system, not just the assets. Upgrade number two, from deliverables to outcomes, you're accountable to impact, not just completion. And finally, upgrade number three, from content creator to quality and ethics gatekeeper. You protect learners from confusion, bias, and misalignment. And now I want to make this simple with a framework you can use for the rest of the series. Whenever AI feels like too much, I want you to come back to this three-layer ID stack. Intent, experience, and assets. So let me break this down for you. Layer one, intent. Intent is the what and the so what. What problem are we solving? What does success look like? What changes on the job? And what is the metric or evidence? Layer two, experience. Experience is the how learning actually happens. This includes practice, feedback, reflection, application, scenarios, coaching, and support tools. This is where learning becomes real. And finally, layer three, assets. Assets are the deliverables. This includes slides, scripts, videos, job aids, quizzes, and facilitator guides. Now here's the key. AI is strongest in the asset layer because it can help you draft, rewrite, expand, condense, format, and generate variations. But intent and experience, that's where you, as the instructional designer, earn your key. So the next time someone says, can AI just make the course? You can say, AI can help with the assets, but we still need intent and experience. Otherwise, we're just making content. That's the framework. Now let's make it real with a quick field note. Here's a scenario I have seen many times in one form or another. A stakeholder says, We need training by Friday. Can you use AI to generate it? Instead of jumping into creating slides, I would ask two questions. What do you need people to do differently by Monday? What's happening right now that's causing the problem? In this scenario, it turns out it wasn't a knowledge issue. It was a workflow breakdown and unclear expectations. So instead of a 45-minute course, you can create a one-page job aid for the workflow, a five-minute scenario-based micro lesson, and a manager checklist to reinforce the change. AI can help draft the first version fast, but the real win is choosing the right solution. Alright, here's your checkpoint challenge for the week. Open a note and write the following words in three columns intent, experience, and assets. Now think about your current project and task. Which layer am I spending the most of my time on? Which layer needs the most attention to actually drive results? If you realize you're living in the asset layer, there's no shame. That's where many of us get pulled, myself included. But this week, I want you to practice shifting up one layer from assets to experience or from experience to intent. Even one small shift changes the quality of the entire solution. If this episode helped you, share episode 107 with an instructional designer friend that you know who is trying to make sense of AI right now. Also, I made a quick interactive resource called the AI Ready Designer Compass. It walks you through intent, experience, and assets so you can apply today's framework to your next project in under five minutes. And coming up next in this series, we're going to get even more practical because in the next episode, I'll show you how to use AI without losing your design voice by building a simple workflow that protects quality while saving time. AI is changing the speed of instructional design, but it doesn't change the purpose. Tools can generate content, but you generate clarity. In a world where everyone can produce learning materials faster, the designers who stand out will be the ones who protect quality, focus on transfer, and keep learning. As I conclude this episode, I would like to share an inspiring quote by Robert Green. The future belongs to those who learn more skills and combine them in creative ways. Thanks for spending time with me today. Until next time, keep it practical, keep it human, and keep designing with love. Thank you for taking some time to listen to this podcast episode today. Your support means the world to me. If you'd like to help keep the podcast going, you can share it with a friend or colleague, leave a heartfelt review, or offer a monetary contribution. Every act of support, big or small, makes a difference, and I'm truly thankful for you.