Instructional designers are no longer questioning whether to use AI in video creation; the challenge has shifted to ensuring that faster production does not come at the expense of instructional quality. As AI tools make it easier to generate scripts, visuals, narration, and edits, learning professionals must decide which parts of the video process can be responsibly automated and where human judgment remains essential.

This session presents a practical approach to integrating AI into instructional video workflows using a familiar model: pre-production, production, post-production, and publishing. You will examine how AI can support common creation and revision tasks while maintaining instructional intent and learner clarity. Using an Automate, Augment, or Keep Human decision lens, we will explore where AI meaningfully improves efficiency and where hands-on expertise continues to produce better learning outcomes. You will apply these decisions to realistic video creation scenarios and experiment with structured prompting approaches designed to move AI-generated results beyond predictable outputs. Our focus is on sustainable adoption rather than tool demonstrations or future speculation. You will leave with a practical decision framework that you can immediately apply to updating existing content, creating new instructional videos, and experimenting with AI responsibly within your own workflows.

In this session, you will learn to:

• Determine where AI can provide meaningful and impactful support across the stages of instructional video creation
• Decide which video creation tasks should be automated, augmented, or remain human-led
• Apply structured prompting and evaluation approaches to move AI-generated content beyond average results

This session is designed as a safe entry point for learning professionals exploring how AI can support instructional video creation. No prior experience with AI tools is required.