AI isn’t coming to instructional design, it’s already here. From course outlines to voice-overs, artificial intelligence is reshaping how learning teams create instructional materials, streamline the instructional design process, and deliver engaging learning experiences.
To better understand how AI in instructional design is evolving, Clarity Consultants partnered with the Association for Talent Development (ATD) on a comprehensive research report. The findings offer a clear snapshot of how instructional designers are using AI tools today, where they’re adding value across content creation and course design, and what challenges still need to be addressed.
Whether you’re just beginning to explore technology in education or looking to enhance your existing process, this post highlights key insights from the field, and provides a practical starting point for thoughtful integration of AI in your instructional design projects.
Read the full guide: AI in Instructional Design – Transforming Workflows and Content Creation
AI Adoption Is Surging: Here’s What That Means for Designers
AI isn’t a future trend for instructional designers, it’s a current reality. Recent research shows that 80% of professionals in the instructional design field are already using AI tools in their daily work. And for most, that adoption happened fast: 65% began using AI within the past year.
Most rely on generative artificial intelligence, not traditional models. Tools like ChatGPT, Microsoft Copilot, and Grammarly are popular because they streamline the content creation process, improve learning design, and assist with writing effective instructional materials. Only 18% report using AI for more data-heavy tasks like learner analytics or adaptive content recommendations.
Here’s where instructional designers are putting AI to work:
Brainstorming course design concepts and instructional content
Writing and refining learning objectives aligned with Bloom’s Taxonomy
Outlining and storyboarding for elearning courses and online programs
Drafting scripts and narration for audio content and multimedia
Editing or summarizing complex instructional content and source materials
With 64% of organizations reporting that at least half of their design teams use AI, it’s clear that adoption is no longer experimental; it’s becoming part of the standard instructional systems development workflow.
From Idea to Execution: Why AI Is a Game-Changer for Course Design
Instructional designers aren’t just adopting AI, they’re seeing real, measurable results. More than 7 in 10 say that AI tools have improved the quality of their training materials, and over 90% report a reduction in the time it takes to design them.
By automating routine tasks like outlining, drafting, and editing, artificial intelligence allows designers to focus on strategy, learner outcomes, and more engaging learning experiences. It supports the instructional design process as a creative partner, ready whenever ideas strike.
Here’s how professionals across the instructional design industry say AI is making a difference:
Faster course development: AI accelerates storyboarding, scripting, and drafting of instructional content.
Stronger collaboration: AI supports project management by streamlining feedback with subject matter experts.
Better focus on design: Less manual effort means more attention to user experience design, structure, and learning effectiveness.
Enhanced ideation: AI helps quickly generate scenarios, titles, and content variations tailored to the target audience.
As one respondent shared, “I use AI as my collaboration partner so I don’t have to worry about scheduling meetings between deadlines. When I think of something, I can hop on and work it out. It also does so much of the content and scripting for me that took me hours to type out.”
In short, AI is helping instructional design teams do more, without compromising on the quality of their instructional systems design.
Key Risks Instructional Designers Must Navigate
AI may streamline workflows, but it also introduces risks instructional designers can’t afford to overlook.
As adoption grows across the instructional design industry, concerns around content ownership, data privacy, and content reliability are becoming more urgent. To use AI tools effectively, and responsibly, designers must balance innovation with informed oversight grounded in instructional design theory, educational psychology, and ethical best practices.
Here’s where the biggest concerns lie:
Copyright and Intellectual Property
AI-generated instructional content may raise legal questions around ownership and reuse. Designers should understand their tools’ terms of use and align with their organization’s educational communications and IP policies.
Accuracy and Misinformation
AI tools are only as reliable as the data they’re trained on. Without validation from subject matter experts, inaccurate or outdated learning materials can undermine learning objectives and trust.
Data Confidentiality
Some platforms collect inputs to train future models. Entering sensitive company data could pose serious risks for compliance, especially in higher education and regulated industries.
Algorithmic Bias
Like any system based on large datasets, AI can reflect historical biases. If designers don’t stay involved in the creation process, biased or non-inclusive content may be introduced into training programs.
Over-Reliance on Automation
While automation can accelerate instructional systems development, it’s not a substitute for expertise. Skipping key review steps, such as aligning content to Bloom’s Taxonomy or understanding the three domains of learning, can result in ineffective instructional materials.
To manage these risks, experts recommend:
Keeping a human in the loop
Validating outputs with SMEs
Using AI selectively, only where it supports strong instructional outcomes
AI can enhance the instructional design process, but only when paired with sound judgment, thoughtful oversight, and a strong foundation in learning design principles.
How AI Is Redefining Content Creation
From outlining courses to refining learning objectives, AI tools are helping teams develop high-quality learning materials faster and with more consistency. By managing routine tasks, AI enables designers to focus on strategic elements of the instructional systems design process, such as aligning with adult learning theories, supporting personalized learning paths, and enhancing the overall learning experience.
Here’s where AI is delivering the biggest gains:
Outlining and Storyboarding: AI supports the early phases of the ADDIE model by helping designers rapidly structure instructional content, define sequence, and build logical flow based on input prompts.
Writing Learning Objectives: Designers use AI to fine-tune objectives that are aligned with Bloom’s Taxonomy, ensuring they’re measurable, relevant, and mapped to the appropriate level across the three domains of learning.
Drafting Training Materials: From job aids and facilitator guides to slide decks and scripts, AI accelerates the production of training materials that can be reviewed, adapted, and finalized to fit the target audience.
Creating Assessments and Activities: AI can generate quizzes, case scenarios, and interactive elements that deliver instant feedback, enhancing both learner engagement and retention.
Developing Voice-Overs and Narration: Many teams are now using AI-generated audio content from platforms like WellSaid Labs, saving time on voice talent and reducing post-production costs.
Supporting Multimedia Projects: While still emerging, AI tools are increasingly used to create content like avatars, animations, and video-based simulations in multiple languages, though designers remain cautious about quality and accuracy.
While AI won’t replace human creativity or instructional expertise, it’s helping teams scale their instructional design projects with greater efficiency, making the creation process faster, more flexible, and more aligned with the latest trends in education and technology.
A Practical Guide to Using AI in Instructional Design
AI can be a powerful partner in instructional design, but only when guided by clear intent and thoughtful planning. Whether you’re just getting started or looking to optimize your current use, applying a strategic approach ensures AI strengthens your instructional systems development process without compromising quality, ethics, or learner outcomes.
Here’s how to begin:
1. Experiment with Generative AI
Start small. Use tools like ChatGPT or Copilot to draft course outlines, brainstorm content ideas, or transform text-heavy documents into instructional materials. These tasks align well with the early stages of the ADDIE model and allow teams to safely test the value of AI tools in their workflows.
2. Practice Prompting
Great results require well-structured input. Learn how to craft precise prompts that deliver relevant, usable content, whether you’re creating learning objectives, job aids, or multimedia for an online course.
3. Use a Decision Matrix
Not all tasks benefit from automation. Use tools like the decision matrix featured in the report to evaluate whether AI is appropriate based on complexity, judgment needs, and relevance to your instructional design theory or educational psychology goals.
4. Build AI Literacy on Your Team
Help your team stay current with the latest trends in design and technology. Encourage peer learning and consider formal training, such as ATD’s AI for Instructional Design Workshop, to build confidence and skill in content creation and strategic application.
5. Keep Humans in the Loop
Even with high-performing AI, instructional designers remain essential. Review and refine AI-generated instructional content to ensure alignment with learner needs, cognitive science principles, and the unique goals of each instructional design project.
For more guidance and frameworks, download the full report and explore how designers across industries are integrating AI into their learning design practices.
Download the full report and start building a smarter future for your learning team.
Conclusion
AI is changing instructional design, but not by replacing it.
What this research makes clear is that the most successful teams aren’t automating everything. They’re using AI to enhance human creativity, speed up production, and improve the learning experience, all while maintaining a focus on instructional strategy.
As AI tools continue to evolve, the opportunity lies in building a smart partnership: one where automation handles the routine, and designers focus on what matters most, creating learning that drives results.
Clarity Consultants is here to help your team navigate that shift. Whether you’re launching your first AI-enabled course or scaling enterprise-wide innovation, our experts can support your transformation every step of the way.
