Perspective
Everyone Wants Innovative Learning. Until You Actually Design It.
Why organizations ask learning designers to think differently, then reward them for doing exactly what they've always done.
“We want something innovative.” If you have worked in corporate learning for long, you have probably heard the request. It sounds like permission to challenge convention and make something that might change how people perform. Then come the requirements: use the existing template, match the familiar look, finish in three weeks, work in the current LMS, and satisfy a committee with several definitions of innovation. The opportunity begins to resemble the last twelve courses you built. Welcome to corporate learning innovation. Please remain inside the designated boundaries.
The innovation paradox
Many organizations want creativity and predictability at once: experimentation without failure, difference that feels familiar, and better outcomes without changing the conditions that produced the old ones. These desires are not unreasonable on their own. Standards serve real needs, including brand consistency, accessibility, regulatory requirements, development costs, and operational scale. I have spent years designing learning in complex corporate environments, and I understand why those constraints exist. The difficulty begins when a constraint that should shape the solution starts choosing it for us.
A constraint should influence how we solve a problem; it should not automatically decide the solution. Organizational standards can become design decisions, though they are not always the same thing. A brand requirement may guide how an experience appears. It does not decide whether the experience should be a course, simulation, job aid, or something else. When the familiar form becomes a supposed necessity, innovation means making the old answer look slightly newer.
When creativity becomes a compliance exercise
Consider a common project. A business leader says employees are making mistakes and asks for training. The designer investigates and finds that employees understand the procedure but struggle when circumstances depart from the examples they have seen. Another informational course may not help. They may need practice making decisions under realistic conditions, feedback that explains the consequences, or a tool for navigating uncertainty while doing the work.
The designer proposes a simulation, not a flashy game but a practical experience where employees encounter realistic situations, make decisions, see consequences, and learn from mistakes. The stakeholder likes the idea until the prototype appears. Could it be more straightforward? Are all those choices necessary? Could we explain the correct process and add a quiz? With each sensible-sounding request, the simulation turns back into the course everyone originally asked for. The designer has not necessarily failed; the organization may not have been prepared for the implications of the innovation it requested.
I've experienced the contradiction
I once had a leader call my interactive designs textbook corporate training and say they would not work in our environment. The criticism stayed with me, not because every design I have made is brilliant. I have built things I would happily bury in an unmarked folder. It stayed with me because it raised a useful question: what makes a learning experience appropriate for an organization? Its visual style, delivery platform, familiar interactions, or its ability to help someone perform the work?
Those qualities are not mutually exclusive. An experience can fit an organization and still challenge conventional design. We should distinguish rejecting an idea because it fails to solve the problem from rejecting it because it looks unfamiliar. One judgment asks whether the reasoning holds up; the other lets familiarity stand in for evidence. An unfamiliar proposal can certainly be wrong, but unfamiliarity alone tells us little about whether it will work.
The safest design isn't always the smartest
Traditional learning experiences are often easier to approve. Stakeholders understand them, reviewers know what to look for, project managers can estimate timelines, and teams can reuse established processes. There is real operational value in predictability. Yet when an organization repeatedly chooses the most familiar solution, it gives itself fewer chances to discover a better one.
The question shifts from “What experience would address this performance problem?” to “What is the most acceptable thing we can build inside the existing process?” The first encourages investigation; the second encourages conformity, which has a remarkable talent for presenting itself as efficiency. A familiar course may be the right choice. If it wins by default, before anyone examines the problem, the team has renewed an old subscription rather than made a design decision.
AI could make the problem worse
AI is reducing the effort needed to produce conventional learning content. Objectives, storyboards, quizzes, scenarios, or a version of the same course with slightly different wording can arrive in moments. That is useful, but it preserves the assumption that the requested course is the right answer. Combined with the same approval processes and expectations, faster production may give us more content, faster and cheaper, that is just as ineffective as what came before.
Automating a familiar design process does not improve the thinking behind it. AI can also help designers explore alternatives, prototype unusual ideas, and test different approaches. The technology is not inherently the problem; the question is whether organizations will use it for more than accelerating production. If innovation means delivering an approved template quickly, AI may make us more efficient at avoiding experimentation. The machine can generate options, but someone still has to decide which problem is worth solving.
Innovation doesn't require organizational chaos
We cannot experiment with everything. Compliance matters, resources are limited, and stakeholders need to understand what they are approving. The answer is not to abandon standards or turn every project into an elaborate experiment. Innovation requires room for informed experimentation within existing discipline, and that room can begin with separating what must stay fixed from what has simply become familiar.
1. Separate requirements from preferences
Accessibility, regulatory accuracy, and technical compatibility may be requirements; “we have always used this interaction” is usually a preference. Treating preferences as necessities narrows design. Keep essential safeguards, but ask which conventions serve the work and which persist because no one has revisited them. Naming the difference gives reviewers a better basis for discussion and designers a truer picture of their boundaries.
2. Prototype before asking for full commitment
An unfamiliar idea is hard to evaluate from a slide deck. A working prototype makes it tangible. Instead of asking stakeholders to approve an entire simulation, demonstrate one meaningful decision and let them experience the difference. Then discuss whether it matters to the people doing the work. A small prototype cannot answer every question, but it lets the team examine the experience rather than imagine it.
3. Define success before reviewing the design
Design reviews often focus on presentation: polish, brand fit, and familiar navigation. Those questions matter, but they should not displace the more important one: will this help someone perform better? Without an agreed standard for success, the review can become an exercise in personal preference. Set the performance goal early and use it to judge whether the design does the work it was meant to do.
4. Make experimentation measurable
Innovation should not mean doing something different for its own sake. Start with a hypothesis, test a small version, observe what happens, and compare it with the existing approach. Keep what works and change what does not. Agree in advance on the evidence to look for and the uncertainty acceptable for a small test. That is disciplined design, and even an unsuccessful experiment can teach the team something useful.
5. Let designers question whether training is needed
When a stakeholder requests training, designers should be able to investigate whether training is necessary. That is not rebellion; it is part of doing the job properly. An organization that discourages questions about the original request has already limited how inventive its solution can be. Teams need not turn every request into a debate, but they should test the premise before investing in the wrong answer.
Maybe we need to redefine innovation
Innovation does not always produce something visually impressive. Sometimes the more innovative choice is simpler: a performance support tool instead of a course, realistic practice instead of another presentation, a redesigned workflow instead of an annual refresher, or no training at all. If the goal is better performance, we should consider solutions that do not add another item to the LMS. Designing for performance and producing training are not the same business.
What I'm experimenting with
One reason I built Learning Rewired Lab was to explore these questions without every experiment needing to become a formal corporate project. The Design Lab contains 50 interactive designs exploring approaches to practice, decisions, feedback, and learning experiences. Some are conventional, some experimental, and some may prove less useful than simpler alternatives. That is fine. The goal is not to prove every new interaction is better, but to expand the possibilities we consider before deciding what to build.
I do not believe instructional designers lack creativity. Many work in environments where an idea must survive approvals, expectations, and inherited assumptions before it can be tested. Eventually people learn which proposals are worth making and which will not get past the first review. That is a loss for designers and for the people they are meant to help. If only the safe idea can survive, we should not be surprised when the work stops surprising us.
The real question
Organizations need not approve every unusual idea. But if they genuinely want innovation, they need conditions in which unfamiliar ideas can be explored, tested, and judged on their merits. That means accepting some uncertainty, occasionally questioning established processes, and recognizing that an experience need not look like the last successful project to deserve consideration. You can demand innovation while making familiarity the primary condition for approval. Corporate America has become remarkably talented at it. We should not be surprised when the results look like everything we have already built.
Keep experimenting
This Perspective expands on my latest Learning, Rewired newsletter, The Learning Industry Has a Creativity Problem. And AI Didn't Cause It. If you are interested in exploring different approaches to learning experiences, visit the Learning Rewired Lab Design Lab. At your next design review, ask: Are we rejecting this idea because it will not work, or because it is unfamiliar? The answer may tell you more about your organization's approach to innovation than another strategy presentation ever will.
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The Design Lab is a collection of interactive examples for testing how practice, decisions, and feedback can work beyond the familiar course format.
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