The Future of Instructional Design Needs a Conductor

A violinist can play every note on the page and still be out of tune with the orchestra. The timing might be wrong. The phrasing might pull in a different direction. A beautiful solo might overwhelm the passage it was supposed to support. Someone has to hear those differences, understand why they matter, and know what to do about them.

That is how I am beginning to see the future of instructional designers and learning and development professionals. As AI takes on more of the work involved in producing learning materials, I see our role moving toward the conductor’s podium. We still need to understand the instruments. We also need to take responsibility for how the whole thing comes together.

There is a catch, though. Standing in front of an orchestra and waving a baton does not make someone a conductor. The expertise has to be there before the direction means anything.

Much of the conversation about AI in our profession has centered on production. How quickly can we build a course? How easily can we generate a graphic? How much development can we complete with a few prompts? I understand the appeal. I have spent plenty of time wrestling with the mechanics of making something look and function the way I imagined it. There is satisfaction in that work, and real skill behind it.

But I do not think spending ten hours drawing a single graphic in Adobe Illustrator should be the measure of our professional contribution. Sometimes a visual deserves that investment. Sometimes those hours would be better spent discovering that the learner needs an entirely different kind of support. Our expertise should help us make that call.

The conductor metaphor matters because it gives us a way to think about that responsibility across the entire learning process, from analysis through evaluation.

Before anyone plays, we need to understand the performance we are trying to enable. What should people be able to do? Where are they struggling? What evidence tells us that learning is part of the answer? What conditions will they face when they leave the learning experience and return to work? Those questions establish the direction. Without them, we can assemble an impressive collection of materials around a problem we have barely understood.

Imagine a manager asking for training because employees keep making mistakes during customer handoffs. AI could help us produce a polished course explaining the handoff process. But a closer look might reveal that two departments are working from conflicting instructions, or that employees cannot access the information they need at the moment of the handoff. The course could be accurate, attractive, and completely beside the point. Someone has to recognize that before the production begins.

During design and development, the responsibility becomes one of listening across the parts. A scenario can sound believable while rewarding the wrong decision. A graphic can look impressive while hiding the relationship learners need to understand. A knowledge check can align neatly with the script while revealing very little about whether someone can perform the task. Each part might pass an individual review. The learning experience can still fail to hold together.

This is where the musical expertise comes in. We need enough understanding of learning, practice, feedback, accessibility, visual communication, and the work itself to recognize when something is out of tune. Then we need to diagnose the problem precisely enough to improve it. “Make this better” is weak direction for an orchestra, and it is weak direction for AI.

A conductor can stop a rehearsal and work with one section. I think we need that same ability to move between the whole experience and its individual parts. We might spend an hour refining a difficult practice decision, checking an explanation with a subject matter expert, or rebuilding a visual that AI keeps getting wrong. The point is to apply our attention where it matters most. We should be capable of stepping into the craft when the work calls for it.

That also means our expertise has to keep developing. If we cannot recognize a weak assessment, we cannot reliably direct AI toward a stronger one. If we have little understanding of the learner’s working environment, we may accept a plausible solution that would be awkward or impossible to use. Delegating production makes the quality of our judgment more consequential.

Our responsibility continues through implementation and evaluation. The experience has to reach people under conditions where they can use it. We need to see what happens when they try. Can they make the decision? Can they perform the task? What remains difficult, and why? A completed course tells us that we produced something. Evidence from its use helps us decide what deserves to stay, what needs revision, and whether we addressed the right problem.

I do not expect every instructional designer’s job to become identical. Some people will continue to specialize deeply in particular instruments, and that expertise will matter. But I want our profession to claim a broader responsibility for the performance, especially as more production becomes easier to delegate.

For me, that is an exciting future. It creates room to spend more of our time understanding problems, shaping practice, challenging weak assumptions, and making thoughtful decisions about what people actually need.

The baton will not give us that expertise. We have to bring it with us. When the violin is out of tune, our value is in being able to hear it, understand what is wrong, and help the whole orchestra find its way back.

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