Photo by: Horia Ionescu’s Images via Canva
More than ever, instructional designers are being asked to integrate artificial intelligence into our work. AI-generated video has moved rapidly from being an “interesting experiment” to an “expected capability” for learning professionals.
When I was asked to lead the design of our Instructional AI Videos for Beginners workshop, it became clear early on that the core challenge wasn’t simply teaching people how to use AI video tools. The challenge was helping designers make sound instructional decisions about when AI video is appropriate within the broader instructional design process, and when it isn’t.
That distinction became the foundation of the workshop.
The Problem We Set Out to Solve
Many learning professionals are under pressure to adopt AI quickly, often without clear guidance. During early discovery conversations with designers and training professionals, we heard consistent themes:
- “We’ve been told to use AI video, but we’re not sure where it fits.”
- “The tools are impressive, but the outputs don’t always feel right.”
- “We don’t want efficiency to come at the cost of learning quality.”
What emerged was a gap, not in tools, but in decision-making confidence. Designers needed support in evaluating AI video through an instructional lens, not just a technical one.
Rather than building a tool-driven workshop, we focused on instructional intent. AI video became part of the conversation, but not the starting point.
Design Challenges We Encountered
1. Moving Beyond Tool Demonstrations
AI video tools evolve quickly. Designing a workshop around specific platforms would limit the long-term value of the workshop and divert learners from core instructional design principles.
Our approach: Participants learn to assess learning goals, audience needs, and design/delivery constraints to determine whether video is appropriate. And, if it is, whether using AI to create the video is the right fit. We centered the experience on how to think, not what to click.
2. Addressing the “Just Because We Can” Mentality
AI video outputs often look polished at first glance, but even polished outputs can mask weaknesses in instructional quality.
Our approach: We included realistic case studies that require participants to determine whether AI video is the right choice. Some scenarios clearly support AI use; others do not. This helped normalize the idea that choosing not to use AI can be the most effective instructional decision.
3. Balancing Beginner Accessibility with Professional Depth
Many participants are new to AI tools but experienced in instructional design. We had to balance the learning curve of a new interface with the detailed instructional decisions designers make every day, elevating instructional design expertise rather than getting in its way.
Our approach: We see AI-generated video as an instructional tool and approached this workshop like any of our others. Strong design principles still apply, regardless of how content is generated.
Key Insights from the Design Process
As we developed and piloted the workshop, several important insights emerged:
- AI-generated video is most effective when emotional nuance and authenticity are not central to the learning goal.
- Performance support and just-in-time learning are often better methods than high-stakes training.
- Poorly chosen AI video can negatively impact learner trust and engagement.
- Providing a clear decision framework reduces anxiety around AI adoption and empowers designers to explain and justify their choices.
These insights became core learning outcomes, not just design observations.
My Experience During Development
Designing this workshop required a different mindset than previous projects. AI brings strong opinions, uncertainty, and urgency into the learning space. My role wasn’t simply to teach a new tool; it was to help participants slow down and think critically.
Pilot feedback highlighted a clear appetite for deeper exploration of AI video tools. Within the constraints of this workshop, we intentionally focused on instructional decision-making rather than tool mechanics.
Practical Tips for Getting Started with Instructional AI Video
For designers new to AI-generated video, a few best practices stand out:
- Start with the learning objective, not the tool.
- Avoid using AI video when the message depends on building trust, credibility, or personal connection. A real person is usually the better choice in this case.
- Use AI where consistency, speed, and scalability are instructional advantages.
- Evaluate outputs through the learner’s experience, not production efficiency.
- Treat AI as a design decision, not a shortcut.
These principles provide a practical starting point for learning professionals new to AI-generated video.
Final Thoughts
AI-generated video is not a replacement for instructional judgment—it raises the bar for it. The Instructional AI Videos for Beginners workshop is designed to help learning professionals use AI video intentionally, responsibly, and in service of meaningful learning outcomes.