Both the development and integration of AI have been skyrocketing lately. Even within the instructional design (ID) field, the use of AI is rapidly expanding.
In any creative work, the process of going from zero to one takes the most time. The struggle of creating something from nothing is such a challenge every ID faces. Before AI became widespread, naturally, everything had to be done by hand.
As an instructional designer, AI is undoubtedly a welcome tool that scratches where it itches. If you say, “I want to create a course like this” or “Draft a module for this target audience,” it can produce content in seconds. It is often described as if it were a magic wand.
You might think, “Woo hoo! Having AI makes things so much easier!” But AI is ultimately just a tool that assists you—it is not a leader meant to drive the project forward. There is no Abracadabra involved.
So, what role does AI actually play in instructional design?
This article explores the role of AI in ID, along with its benefits and challenges.
The Role and Benefits of AI in Instructional Design
1. AI as a “Supporter”
AI handles labour-intensive tasks, such as organizing vast amounts of data and brainstorming initial ideas. For example:
- Drafting learning objectives (LOs): Proposing objectives aligned with learner profiles and specific contexts.
- Suggesting interactive activities: Ideas for effective activities that reinforce learner understanding.
- Content refinement and polishing: Simplifying technical jargon and adjusting tone or style.
This is not cutting corners. It is strategic efficiency used to rapidly build a project’s foundation.
Furthermore, when you are brainstorming so many ideas and can’t narrow them down, AI can act as a sounding board to help you prioritize. Using AI for this “draft creation” phase allows you to tackle development without getting stuck in a vacuum. It’s like having a “buddy” by your side.
2. Reinvesting freed-up time into “what matters”
Course development involves various layers of work. In ID, deciding where to allocate your limited time is crucial. The greatest benefit of AI isn’t just saving time; it’s about what you do with the time you’ve saved.
By streamlining the Develop phase with AI, you can allocate more energy to core ID tasks such as:
- Deeper Analysis: Investigating the root causes of performance gaps on the ground.
- Dialogue with SMEs: Articulating the living wisdom and tacit knowledge that AI simply cannot extract.
- Evaluation: Meticulously measuring and analyzing the actual behavioural changes that occur after training.
Challenges in AI Usage
AI is certainly convenient, but it remains a developing technology. It cannot operate in complete isolation, and human involvement remains essential.
The Indispensability of “Human Verification” and “Professional Judgement”
No matter what excellent suggestions AI provides, they should never be relied upon exclusively. AI does not truly understand the unique culture of an organization, the specific context of the learners, or the ultimate business goals.
This is where professional judgement as an ID becomes necessary:
- Contextual Alignment: Does the content align with the realities of the actual workplace?
- Verification of Learning Transfer: Does the activity genuinely lead to performance, or is it just “fun”?
- Educational Rationale: Do the suggestions align with fundamental instructional design principles?
Furthermore, human verification is essential to confirm the accuracy and sources of AI-provided information. This process is precisely what breathes life into the materials and guarantees results.
Summary: Lead the AI, Don’t Follow It
AI enables faster framework development and a more efficient workflow. However, real humans must always lead the project and make the final decisions. AI should be a “buddy” you work with, not a “dependency” you rely on.
By ensuring the ID professional retains the “lead” and allowing AI to function as the ultimate “supporter,” we can deliver learning experiences of greater value than ever before.
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