AI Is Becoming an Integral Part of the Instructional Design Process
What I learned from 150 interviews with instructional designers
In the last month, I have run 150 interviews with junior, senior and mid-career instructional designers from the around the world.
The purpose of the exercise was to understand if AI is impacting the day to day work of instructional designers.
Here are the five things I learned.
Let’s go! 🚀
1. AI already plays a central part in the instructional design process
A whopping 95.3% of the instructional designers interviewed said they use AI in their day to day work. Those who don’t use AI cite access or permission issues as the primary reason that they haven’t integrated AI into their process.
2. AI is predominantly used at the design and development stages of the instructional design process
When mapped to the ADDIE process, the breakdown of use cases goes as follows:
Analysis: 5.5% of use cases
Design: 32.1%
Development: 53.2%
Implementation: 1.8%
Evaluation: 7.3%
3. The primary use case of AI in instructional design continues to be content creation
AI tools are being used extensively used to produce multimedia content, draft scripts, and create assessments.
By far the most common use case is AI is video creation, followed by content drafting, and generating quizzes from text. Check out a list of the most popular tools here.
This likely reflects two things:
Traditional content creation methods are painfully slow and expensive, both financially and in terms of time.
The vast majority of AI tools that have emerged onto the market in the last year or so have been “text to content” generative AI tools.
4. Instructional designers are starting to use AI in the design phase more
More and more, instructional designers appear to be using AI as a “thought partner’ in the design part of the process. Specific use cases here include:
Ideation: using AI to generate a range of ideas and suggestions for course topics, learning activities, and content formats based on initial input instructions about learners and goals.
Creative Thinking: using AI to assist in creative thinking and “thinking outside the box” by providing unexpected perspectives or by combining concepts from different domains, leading to the use of innovative instructional strategies and creation of innovative materials.
5. More change is on its way
Several instructional designers are already exploring AI's potential in new areas, indicating a trend towards innovative applications of AI in instructional design. This includes:
Using AI as a tool to get to know the topic / domain, reducing reliance on subject matter experts.
Using AI as a tool to both generate and analyse data about learner needs and the impact of learning experiences on intended outcomes.
The insights from interviewing 150 instructional designers from around the globe have been illuminating, revealing the substantial impact AI is having on their work.
With 95.3% of designers integrating AI into their daily tasks, it’s clear that AI is not just a supplementary tool but an increasingly central component in the instructional design process,
The interviews also suggest that the landscape of instructional design continues to evolve rapidly, powered by a broadening range of AI technologies and increasing confidence among instructional designers to experiment with AI.
One thing is clear: used well and with intention, AI brings a wealth of possibilities for innovation and improvement in the day to day analysis, design, development, iteration and evaluation work of instructional designers.
Happy innovating!
Phil 👋
PS: You can download a copy of the report here.
PPS: If you want to explore the impact of AI on instructional design and hone your AI skills, check out my AI Learning Design Bootcamp.
