Streamlining Instructional Video Production with AI

The demand for high-quality instructional videos has never been greater. Everybody needs them. Whether you are onboarding new users or rolling out complex technical products, there is always a lot of pressure to deliver awesome and accurate videos. But let’s be realistic—the resources and deadlines are always tight.

Here comes the part where the advances in artificial intelligence (AI) are completely transforming the waycontent is created and consumed these days. AI tools are now making it possible to restructure time-consuming production steps for creators. They can reduce human error to significantly improve the overall learning experience for learners. For Information Developers and Instructional Designers, this shift denotesan exceptional opportunity. We can now ditch the tedious stuff and focus on what really matters—that is helping people actually grasp technology with ease.

AI is becoming a must-have in the world of eLearning and technical documentation. By 2025, more and more companies have been using generative AI (Gen AI) to personalize learning and show real, measurable results. There has been a quantum shift in the quality and speed of delivering eLearning assets. For Information Developers like me, it is not just about drafting and editing content anymore; AI helps us to scale up content creation by giving us more time to focus on creative and high-value work.

In this blog, I will discuss how integrating AI into the instructional video production process can help Information Development teams overcome traditional hurdles and deliver professional-quality videos faster than ever before.

Why Traditional Video Production Falls Short

As an Information Developer, creating instructional content is trial by fire—you have to make sure everything is technically accurate, while also keeping your audience interested and prioritizing efficiency. One of the toughest parts? Taking long, unstructured walkthroughs and turning them into short, polished videos that are both useful and engaging.

And why? Because short, customer-facing technical videos just work better. They fit modern attention spans, making it easier for people to watch the whole thing without zoning out. Quick videos are also easier to share and revisit when someone needs a refresher. Plus, breaking up longer content into focused, bite-sized clips helps viewers actually remember what they have learned. And from a creator’s perspective, shorter videos are much faster to produce and repurpose, so you can keep your content fresh and relevant without a huge investment in time.

The traditional way of making user-assistance videos, especially for technical topics, can be a real challenge. It is slow and full of snares. You have to carefully script everything, record voiceovers, edit and sync the audio with visuals. All of these steps take a lot of time and effort, and it is easy for little mistakes to slip in. Filler words such as “umm”, awkward pauses, repetitions or uneven pacing of the video can act like a grinch and ruin the whole learning experience.

Moreover, studies in cognitive psychology, such as Cognitive Load Theory by John Sweller, show that unimportant information like filler words increases cognitive load, making it harder for viewers to retain core content. Fixing these issues later means even more editing and cleanup.

The conventional process of customer-facing video production typically includes the following steps:

• Information Developer draws a script outline and makes it as detailed as possible.
• Once the script is approved, either an Information Developer or a subject matter expert (SME) records the voiceover. Or sometimes, the SME records the entire video, including the feature or tool demonstration and conceptual knowledge, and shares it with the Information Developer. This step may require multiple iterations due to filler words, human tics, faulty microphones or unclear phrasing.
• SME or an Information Developer records the visuals.
• Syncing voiceovers with visuals often requires multiple iterations.
• SME and other stakeholders review the finished video.

This process often poses difficulty in estimating final video duration due to lack of content organization. Also, there is not much wiggle room to shorten the video duration for better end-user consumption. There can also be limited flexibility in repurposing raw recordings to fit diverse personas.

For example, I had to work on a 30-minute walkthrough for a soon-to-be-released OpenEdge tool, which needed to be condensed into a 10-12-minute customer-facing video. Achieving this manually would have required extensive editing, potential re-recordings by SME and multiple rounds of review. In breakneck development cycles and release deadlines, this level of effort is rarely feasible.

The AI-Driven Approach: Restructuring Script and Voiceover Production

So, here is how I tackled the AI-assisted workflow for shortening video length while still maintaining high quality of the finished asset. The goal was simple: to get a script that was super clean, with no weird quirks and ready to roll into the video-editing process without a hitch. I can now say with experience that some of the most effective solutions and creative breakthroughs happen simply because you were pushed to find a better way.

Here is the step-by-step workflow:

1. Transcript generation: Process raw video content, such as the video script, using an AI tool (e.g., Microsoft Copilot) to generate a clean, logically segmented transcript. Let Copilot do all the heavy lifting by intelligently organizing the content into sections, such as agenda, use case, solution and demo walkthrough, eliminating filler language and superfluous phrasing.
   

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Sample prompt

Process the following raw video script to generate a clean, logically segmented transcript for a customer-facing video. Organize content into meaningful sections. Eliminate filler language, redundant phrasing and any superfluous commentary. Ensure the final transcript is clear, concise and structured for easy consumption. Prioritize logical flow and readability.

2. Voiceover optimization: Import the AI-generated script into an AI audio editor, such as TechSmith Audiate. This tool automatically splits the narration into smart scenes, which eliminates the need for manual scene breaks and facilitates consistent pacing and tone. You can apply minor edits in the script for clarity and completeness wherever required. Using an AI-assisted voiceover can be good for maintaining consistency in your instructional videos, especially when you have a loyal following.

3. Duration estimation: Use AI tools to provide accurate narration time estimates. Then ensure that planned durations closely match the actual video length. Doing so enables better planning and tighter control over your video’s timing.

Sample prompt

Analyze the following video script and provide accurate narration time estimates. Assume natural pacing and conversational delivery speed to calculate how long each section will take to narrate. Break down the timing by segment, such as introduction, use case, solution or demo, and provide a total estimated video duration.

4. Visual structuring: Use AI-generated titles and transitions to create smooth segues between sections. This makes it easier for viewers to follow along and keeps the video flowing nicely. For a better viewing experience, you can use these segue screens as a guide when creating chapters for your YouTube posts.

5. Export and integration: Exporting the final audio files to the video editing platform, such as Camtasia, allows manual synchronization with visuals, while maintaining the freedom to make necessary adjustments.

Outcomes and Benefits

The AI-enhanced workflow delivers measurable improvements, including:

• Time efficiency: Significant reduction in editing time, especially in trimming and syncing.

• Script quality: Filler words and repetitions are eliminated resulting in a polished, professional voiceover.

• User engagement: Structured narration and transitions improve understanding and retention of the viewer.

• Important information: Ask AI to list important information as notes within the transcript. By adding callouts for crucial details in your videos, you can help the viewers easily spot important concepts and not miss any caveats or disclaimers.

Sample prompt

Process the following transcript and identify information that should be highlighted as notes. Add clear markers for crucial details, such as important concepts, caveats, disclaimers and action items. Make sure that no critical information is overlooked.

• Scalability: Faster turnaround for multiple video assets without compromising quality.

• Creative focus: More free time to dedicate to visual design, storytelling and overall user experience.

Additional Insights

Beyond the main features and workflow, here are some helpful advanced capabilities I discovered while working with AI tools:

• Smart scene segmentation: AI-powered scene breaks make it easier to edit and organize content, which is especially useful for longer recordings.

• Voice customization: You can change the tone and speed of AI-generated voiceovers to fit different audiences.

• Reinforced messaging: Using outro screens and verbally mentioning links to the Progress content portal makes the calls to action more effective. This method shows viewers what to do next and makes it clear where to get more help or resources, making it less likely for them to miss important information and more likely to interact with the content.

• Content summarization: Copilot can generate slides from raw transcripts that can help distill main takeaways in the form of bullet points. This information is a great way to repurpose content into microlearning modules.

Sample prompt

Process the following transcript and generate a slide deck that distills the main takeaways into concise bullet points. Organize the content into logical sections. Make each slide focus on one core idea, suitable for microlearning modules.

• Human touch: Real people can make the content resonate with the masses. If you are a seasoned Information Developer and prefer keeping it classic, you can record the AI-assisted clean and organized transcript in your own voice to foster loyalty and engagement for your content.

For my use case, I was finally able to reduce the 30-minute walkthrough for a soon-to-be-released OpenEdge tool that I mentioned earlier into a 12-minute customer-facing video. This is a significant reduction, especially when we are talking about content where everything feels essential and information bias takes over. Filtering the information to get rid of unwanted noise is an accomplishment. Plus, there are so many derivatives you get to learn and enjoy in the process.

Potential Pitfalls and Mitigations

Despite their advantages, AI tools are not perfect. They may misinterpret technical terms and create voiceovers that sound a bit too robotic. Sometimes, they also introduce small errors if left unchecked. If you rely too much on automation, there is also a risk of losing the personal touch that makes instructional content feel relatable.

To mitigate these issues, you can maintain a hybrid workflow that combines AI automation with human oversight. Some of the best practices include:

• Having SMEs review the scripts
• Using iterative feedback loops to refine the content
• Regularly updating AI tools with the latest, domain-specific terminology
• Applying human judgment before publishing

Future Directions

The field of AI in instructional content is ever-changing. New capabilities, such as generative video creation and adaptive learning paths, are making it possible to further personalize the learning experience to fit multiple personas. As these tools continue to mature, they will unlock even more opportunities for delivering premium content.

To remain at the forefront, it is important to adopt a culture of perpetual experimentation and constant feedback. Regularly evaluating new AI features can help you maximize its benefits.

Conclusion

Bringing AI into instructional video production has completely changed the game. What used to be a manual and error-prone process is now structured and streamlined. By letting AI handle the difficult parts like cleaning up scripts and removing common human slip-ups, Information Developers can now focus on delivering professional content faster and with less stress.

For Information Development teams dealing with complex technical topics, this transition does not just improve efficiency, it genuinely elevates the user experience. While it is clear that thoughtful integration of AI with a human touch is the key for endless possibilities, let’s acknowledge that even the most technical content benefits from warmth and relatability.

It’s exciting to see how AI is helping us overcome yesterday’s limitations and unlock new creative possibilities that once felt out of reach.