Right now, it’s impossible to truly know how AI will affect instructional design in the future. The reality is that this technology is changing too quickly, and no one really knows what will happen. I’ve definitely heard from folks that are scared the whole field of instructional design could disappear and we’ll all be replaced by AI. I’ve also seen predictions from people optimistic about AI who expect it to transform and improve the whole field within two or three years.

While I’m loathe to make too many predictions, I expect the reality will be somewhere in the middle. I don’t think most instructional design jobs will disappear, but I do think the field will change as we integrate more AI tools to augment our work.

The image above was generated with Playground AI. AI to augment and adapt, not replace instructional designers

For the most part, AI tools won’t replace instructional designers. One of the challenging aspects of this field is that it covers a lot of different tasks and requires a wide range of skills. We need to do aanalysis, writing, working with SMEs, visual design, etc. What makes instructional design challenging also means it’s harder to replace us.

In general, I think instructional designers will use AI to augment their work, not replace them. Instructional designers who learn to adapt their practices and processes to use AI will likely be more successful.

Self-driving cars and adaptive cruise control

Think about technology in cars. Self-driving cars have been promised as “just a few years away” for more than a few years now. But driving is a complex task that requires a bunch of different processes and reactions. While there are some cars that can operate independently in some conditions, the technology still has a lot of problems. We’ll continue to see research and advancement in the field of self-driving cars, but the safety and other concerns mean it won’t be widespread for a long time.

However, while we don’t have fully-self driving cars, we do have driving technology that is helpful. Take adaptive cruise control, for example. Instead of setting a single speed on your cruise control and manually adjusting when you need to slow down, adaptive cruise control adjusts the speed for you. You set the maximum speed, and then the car adjusts based on the distance between you and the car ahead of you. The technology takes an annoying task that used to require manual effort and makes it easier.

In the short term, the improvements in AI for instructional design are going to be more like adaptive cruise control than self-driving cars. AI tools can help you with certain parts of your role, but it won’t replace you. It’s worth finding the ways that AI can make your job easier.

AI voices

While instructional design overall isn’t going to disappear, the voice over field is going to be hit hard. AI voices are much better now than they were even a year ago, and I continue to see new tools and improvements all the time. I know several IDs who are already using primarily or exclusively AI voices.

Personally, I think the AI voices are OK for short content, especially didactic or instructional narration. They still fall short for scenarios and more emotional or conversational content though.

For example, I recently had a script for a Vyond video where one character exclaims, “Typical!” In my voice over script, I included a direction for the voice over artist to roll her eyes while she said the line. And yes, I could “hear” that body language in the final recording. We are a ways away from being able to get that kind of nuance from AI voices. It was absolutely worth hiring a voice actor to humanize that script.

I expect that elearning will continue to shift to AI voices because they’re “good enough” for a lot of content. I don’t think real voice over is going to disappear entirely, but I think it will become more of a premium product.

Tech writing and software training

While I don’t think ID is going to go away, I think jobs designing software training will be affected. Tech writing, software training, and procedure documentation jobs won’t disappear completely, but AI can perform really well in these areas.

A large percentage of technical documentation and software training will be initially captured with tools like Scribe AI and guidde. People will be needed to identify what’s needed, record the process, and clean up the results. But even right now, the tools can speed up the process enough that one person can do work that used to take a whole team.

Faster content generation. Should we?

In a recent discussion on LinkedIn, someone talked about how we can now generate content in minutes with AI. We can…but do we want to?

Faster creation of lower quality content isn’t a win for the L&D field. Some organizations will get seduced by that. It’s just like how some organizations have opted to offshore work and then been disappointed in the results.

When you see how fast AI can create content, it’s initially amazing…until you look at it in detail and start to see the flaws. Sometimes it would take more time to edit and improve AI-generated content than to just write it yourself.

In practice, I think people will find ways to be more efficient in certain parts of the process of creating training. However, most companies won’t find AI-generated training valuable enough to pay for. Yes, you can generate content quickly with AI. You still need to spend a lot of time reviewing and correcting it. SME review becomes even more important for AI-generated content because it’s so critical to have someone check the accuracy.

Improving efficiency in creating training

I am finding it helpful in certain areas, and AI does improve efficiency in some tasks. For example, Claude is really good at taking big storyboards or scripts and turning them into nicely formatted voice over scripts with file names. That’s a boring administrative task that I used to spend time doing manually. Now, I can give Claude a prompt and a document, and then work on something else while it sets up a clean script for me.

Robyn Defelice is working on updating the ATD research on how long it takes to develop training. I’ll be interested to see what Robyn’s newest research finds. My prediction is that AI won’t have shifted things much yet in this round of the research. Most organizations are just dipping their toes into AI. Certain areas will go faster (like AI voices), but most of the rest is currently experimentation and piloting, not production. I don’t think the use of AI is widespread enough to really shift the time estimate benchmarks yet. (But we’ll see when Robyn publishes the updated version–maybe I’ll be wrong!)

Adaptive learning experiences

Another way AI will be used in instructional design is creating adaptive learning experiences. In the short term, I expect this to look like some of the AI-enabled elearning Garima Gupta has been demonstrating. Many of us in the field have wished for year that we could automatically assess and provide feedback on open-ended responses in elearning. Now, it’s possible to create those exercises, giving the AI tool a rubric or standards to use to provide feedback.

Chatbots are another way to provide adaptive learning experiences. Character.ai is careful to remind you that everything it does is made up, but you can use that right now to get personalized language learning, a virtual partner to practice interviewing, or help with writing. Especially in parts of the world where teachers are in short supply, this kind of personalized learning experience could make a huge difference for learners.

Right now, most organizations seem to be approaching AI-generated content with caution, and I don’t think they’re wrong. One of the ways AI will affect instructional design will be that we will curate and create these chatbots and adaptive experiences. AI tools will need training and guardrails before they’re ready for widespread use in organizations, and that’s a role instructional designers can potentially do.

How AI will affect instructional design: Short-term and long-term effects

The general trend with new technology and predictions is that people overestimate the effect of technology in the short term and underestimate the effect in the long term. I think that’s a lot of what we’re seeing now in how people assume AI will affect instructional design. People assume we’re going to see huge changes right away, but it’s actually going to take longer.

Given that, we’ll probably see some small improvements in efficiency in the process of creating training in the next few years, with larger changes in a few specific areas like AI voices. I also think we’ll start to see AI used in learning experiences like chatbots and personalized learning, but most organizations will move cautiously.

The big revolutionary changes won’t really be visible for 15-20 years. I don’t think anyone can accurately predict that now. AI feels like a big shift, but it’s too early to really be able to see what things will look like that far out when we’re so early in this process of change.

I’m putting these early thoughts on my blog now with the intention to revisit this down the road. Maybe a year from now I’ll realize I was wrong, and I completely underestimated how fast everything would shift. But based on everything I’ve seen so far, I don’t think the changes will be drastic yet.

Upcoming events

Tuesday, October 31, 3:00 PM EDT: Level Up Your Elearning: Character Creation for Scenario-Based Learning. Part of TLDC’s free event From Instructional Design to Dungeons & Dragons: The Chronicles of Educaria.

In Dungeons & Dragons, character creation is the foundation of epic storytelling. In learning and development, the creation of characters plays a pivotal role in scenario-based learning. For this session, you will complete activities focused on shaping character backstories, defining their objectives, and constructing challenges that spark curiosity and foster learning. Learn tips for creating characters who are both relevant to your training context and interesting enough to spark attention. A good character for scenario-based learning is one your learners can identify with and that draws them into the story. Just like in RPGs, creating characters for workplace training scenarios requires a bit of imagination. Plan to actively participate in this session and practice creating both protagonists or player characters (PCs) and additional non-player characters (NPCs).

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