Perspective
What If the Future of Instructional Design Is a Job You Don’t Want?
AI’s promise to free designers for more analytical work leaves a harder question unanswered: what if making things was the part they loved?
Imagine an instructional designer opening a project that would once have occupied the better part of a week. There is a script to develop, a visual approach to explore, a branching conversation to work through, and the familiar challenge of making a complicated subject feel understandable. These are not merely production tasks to this person. They are the work: the places where experience, taste, curiosity, and a little stubbornness become something another person can use.
Now imagine much of that first draft arriving in a few minutes. The designer still has decisions to make, and the output still needs attention, but the balance of the day has shifted. More time goes to reviewing what a system produced. Less goes to the slow, occasionally frustrating process of discovering an idea by making it.
In the usual telling, this is the happy part of the story. The designer has been liberated. With production out of the way, they can concentrate on strategy, performance analysis, curriculum architecture, and the science of learning. The profession moves upward, everyone becomes more valuable, and the tedious work disappears into the machinery.
It is a reassuring story, especially if the work being described as tedious happens to be work you never enjoyed. It is considerably less reassuring if someone has just described your favorite part of your job.
The promotion nobody asked for
There is a peculiar assumption inside the phrase “higher-level work.” It suggests that the natural ambition of someone who makes things is to spend progressively less time making them. We recognize the problem when a talented teacher is expected to become an administrator or a skilled designer is promoted into managing other designers. Yet in conversations about AI, a similar transition can be presented as an uncomplicated gift. Of course instructional designers want to become more strategic. What else would they want?
Some do. Some have spent years trying to get invited into conversations that happen before a course request arrives. For them, any reduction in repetitive production may create room for the work they have been fighting to do. Others entered the profession because they liked explaining difficult ideas, writing believable dialogue, creating visual experiences, or building something that finally made a subject click. Their ambition was to become excellent at that craft. An expanded calendar of stakeholder interviews and measurement discussions may be worthwhile, but it is not automatically the career they were hoping for.
That distinction deserves more respect than it usually receives. Reluctance to exchange creative production for analytical work does not, by itself, indicate laziness, fear, or a refusal to grow. It may reflect an honest preference about how someone wants to spend the working hours of their life. A profession can change in ways that make economic sense while becoming less personally satisfying to people who once loved it. Both things can be true without anyone needing a motivational lecture.
None of this means analysis is new to instructional design. It has always belonged in the work. But a responsibility appearing in a professional model does not tell us how much opportunity a particular designer has had to practice it. Consider someone whose assignments arrive with the audience, delivery format, deadline, and supposed solution already settled. Their job may formally include analysis while their actual working life rewards getting the approved material built. Telling that person to “focus on strategy” skips over the conditions that shaped their experience.
A skills gap is not an identity problem
We need to distinguish between people who do not yet know how to do this work and people who do not want it to become the center of their professional lives. The two can overlap, but they require different responses. Someone who wants to investigate performance problems needs practice, feedback, useful questions, and access to evidence. Someone who is mourning the loss of creative ownership needs a conversation about the work itself. Another competency framework will not necessarily help.
Even the proposed destination needs a closer look. Curriculum design, performance analysis, and learning science are related areas of expertise, not interchangeable names for whatever remains after content production becomes easier. Organizing a sequence of learning experiences is different from investigating why a workplace process is breaking down. Both differ from judging whether a research finding supports a particular design decision. Asking one practitioner to become proficient across all of them is a substantial development expectation, however casually it appears in a LinkedIn post.
There is also an organizational question hidden beneath the personal one. Will designers be given access to the people doing the work? Can they inspect examples, challenge a stakeholder’s explanation, or recommend something other than the requested course? Will anyone protect the time needed to investigate? A designer cannot compensate indefinitely for the absence of those conditions by becoming more strategic in private.
I am wary of advice that assigns the whole burden of adaptation to the individual. If an organization wants better diagnosis, it has to permit diagnosis. If it wants meaningful evaluation, it has to make room for evidence beyond a completion report. Purchasing a faster production tool does not create either condition. Without them, the promised future could amount to the same constrained assignment at a higher speed, with an additional expectation that the designer should somehow be doing more consequential work.
Still, these constraints do not make the skills question disappear. A designer who has spent years becoming excellent at production may need help approaching an ambiguous request. That help should begin with a manageable piece of work, rather than an instruction to acquire a new professional identity.
What the request leaves out
Consider a hypothetical request from a customer service leader: escalations are taking too long, customers are frustrated, and the team needs a refresher course on the escalation process by the end of the month. The request comes with a slide deck, a subject matter expert, and a deadline. It is entirely possible to begin making something immediately. The material can be reorganized, the language improved, and the process turned into an attractive sequence with a scenario at the end.
But what, exactly, are employees struggling to do? Perhaps they cannot recall which cases qualify for escalation. Perhaps they know the criteria but struggle to distinguish between two plausible categories. Perhaps they can make the decision perfectly well, but approval takes three days and the queue gives them no visibility into what happens next. The same request could conceal any of these problems, and each would call for a different response.
Those distinctions are where analysis starts to become useful to a designer. They influence what to build, how much to build, and what a successful result would look like. If the difficulty is interpreting ambiguous cases, the most interesting creative challenge may be constructing cases that expose that ambiguity. If the difficulty is finding an infrequently used rule, a well-designed reference might serve people better than another explanation they must remember. If the delay sits in an approval process, the designer needs a defensible way to bring that finding back to the requester.
This does not make the creative work smaller. It gives it something specific to accomplish. A scenario about a difficult judgment offers different possibilities from a scenario added because the course needs an interaction. The dialogue, consequences, pacing, and feedback can all grow from a clearer understanding of the difficulty. Analysis can open creative territory that a slide deck alone would never reveal.
That possibility should not become another excuse to dismiss what people may lose. There is satisfaction in shaping a sentence yourself, developing a visual idea through several unsuccessful attempts, or working out how an interaction should behave. A person can appreciate the usefulness of AI and still want to preserve those experiences. The question is whether designers will have the authority to choose where assistance helps and where making the thing is part of how they think.
A practical way into unfamiliar work
This is the problem I want the Decision Workbench to help address. A designer should be able to approach a training request without already feeling fluent in every aspect of performance analysis or curriculum design. They need a way to make the uncertainty visible: questions worth asking, facts that need checking, and a plan they can discuss with the person who brought them the request.
In the escalation example, a useful starting point would be to separate the leader’s explanation from what has actually been established. “Employees need a refresher” is a proposed explanation. “Escalations are taking too long” is a problem that still needs to be understood more precisely. Bringing that distinction into the conversation gives the designer somewhere to begin. They can ask for examples, examine where the delay occurs, and identify what evidence would justify a particular response.
The Workbench’s role is to support that preparation and reasoning. It cannot know the workplace simply because someone describes it convincingly, and a generated suggestion is not evidence that the suggestion is correct. The practitioner still has to investigate, interpret what they find, and decide what is appropriate. A useful tool should make that responsibility easier to exercise, with a plan the designer can explain and revise as the facts become clearer.
There is a learning opportunity in that process, but it deserves a modest claim. Completing an analysis with assistance does not demonstrate that someone can perform the same analysis independently. The opportunity to develop judgment comes when the designer considers why a question matters, tests an assumption, and sees how the answer changes the design. If they accept an output and move straight into production, the underlying gap may remain. Support becomes educational through the thinking it helps someone practice.
I do not think every instructional designer needs to become a learning scientist. I do think designers deserve practical ways to strengthen the decisions that shape their work, along with room to decide which kinds of expertise they want to develop. There should be space for people who love building, people who love investigating, and people whose best work comes from moving between the two.
The future of instructional design will be influenced by what technology makes possible, but also by what employers reward and what practitioners are willing to accept as a satisfying working life. “You can focus on higher-level work” is an incomplete answer to someone asking whether there will still be room for the work they love.
A better answer would give that person a concrete problem, support in understanding it, and meaningful ownership of what they create in response. If we want designers to invest more of themselves in analysis, we should help them experience how it improves a decision they care about. They may discover a part of the profession they want to grow into. They should also be allowed to say that, after doing the thinking, they still want to make something.
Decision Workbench
Bring a clearer plan to your next design conversation.
Start with a training request. Find questions to ask, facts to check, and a plan you can discuss with your stakeholders. Use your expertise to choose useful practice and support.
Practical support for your reasoning. Your judgment stays at the center.
- Clarify what people need to do
- Identify questions and assumptions
- Check the facts behind the request
- Develop recommendations to discuss