Right after COVID, we were still working from home. Offices had started reopening, and some colleagues had begun dropping in once a week. One day, our manager—let’s call him UM—booked a slot for the entire team to attend a workshop at the office. The topic was personal growth and networking.
Ironically, I don’t remember much from that workshop.
But one thing stayed with me.
Most of the time, when I say I’m an instructional designer, the conversation stops there. Some pretend to know what it means, some assume it has something to do with art and design, and most are completely clueless.
Thanks to that workshop, I started thinking more carefully about how I describe what I do.
Which of these introductions would make you pause and understand the role better?
“I create courses for corporations.”
Or,
"I design and develop learning experiences that make complex ideas simple."
Or,
“I design learning solutions for organizations to accelerate workforce performance.”
The words are different, but so is the perception. One describes a task. The others describe outcomes. And that was the real takeaway from that workshop: how you introduce yourself matters. But simply rebranding your role with cooler-sounding words does not change much. Not unless the approach changes with it.
Can you create an outcome-oriented curriculum for corporate training? Can you facilitate workshops? Are you good with PowerPoint for creating Instructor-led Trainings (ILTs) and equally adept at churning out e-learning courses using multiple authoring tools? A few years ago, that combination of skills might have made you stand out. Today, it is rapidly becoming the baseline expectation from entry-level instructional designers equipped with AI tools. Why? Because AI tools can already generate course outlines, draft content, create images, produce videos, and speed up production in ways that would have seemed impossible just a few years ago.
As AI keeps improving, the people most at risk are not necessarily the ones with the “wrong” job titles. They are the ones whose value begins and ends with production. The real question is no longer whether you can create a course. It is whether you can identify a business problem, design a learning strategy around it, and influence measurable performance outcomes. The future instructional designer may need to become more “T-shaped.”
Learning strategy remains the vertical core, an Instructional Designer’s deep specialization. But the horizontal layer increasingly includes business acumen, facilitation, analytics, storytelling, AI fluency, UX thinking, and stakeholder management skills. Because in the AI era, value may no longer come from simply producing learning content faster. It may come from understanding business problems deeply enough to design the right learning solution in the first place. AI is not just changing the tools instructional designers use. It is redefining what organizations value in instructional designers in the first place.