Training Content Was Taking Too Long To Update
A few months ago, our team noticed something disturbing. We didn’t struggle to create training content. We strive to keep you informed. Every time we need a new onboarding tutorial, walkthrough, or internal descriptor, the workflow is bigger than expected:
- Writing documents
- Recording screens
- Editing clips
- Editing subtitles
- Exporting updates
- Submits draft for feedback
Even short indoor videos can easily take days. Too bad some things were out of date by the time we finished them. For small teams, especially teams without dedicated video editors, this process becomes difficult very quickly. At first, we didn’t want AI video generators. Honestly we were just looking for a way to reduce production tension.
What Makes Traditional Training Videos Feel Difficult
One thing I’ve noticed is that most internal training content follows the same production logic: make one polished training video and keep using it for months. But the current workflow isn’t that slow anymore. Products are updated regularly. Internal tools are changing. Processes are flexible. And the rides usually need a little updating every few weeks.
That means teams spend more time maintaining training content than developing the learning experience itself. The larger the organization, the more complex that cycle becomes.
We’ve Started Testing Short AI Video Streams
Our first test was actually pretty simple. We wanted to see if AI-generated video could help us visualize learning content quickly before investing time in full production.
Most of the tools we tried sounded:
- It is very focused on social media
- The template is very heavy
- Although it is difficult to control regularly
Then, we found an AI video tool that was easy to test quickly within the browser without changing the existing workflow too much. What immediately stood out was how quickly we were able to turn bad ideas into a tangible framework.
Instead of spending hours editing placeholder videos just to explain a concept internally, we can quickly create a short visual sequence of:
- Riding ideas
- Workflow displays
- Internal process descriptors
- Client teaching concepts
That changed our review process more than I expected.
The Biggest Benefit Wasn’t “Automation”
Many people think that video AI is about to change the production process completely. It wasn’t that. The biggest advantage was actually the speed of replication.
Before, even small changes made more work:
- Reopening projects
- Rearrange clips
- It also exports
- Updates subtitles
- Repeats approval cycles
When virtual prototyping became easier, our team started testing ideas much earlier in the process. And frankly, the conversations got better because the participants responded better to complex visual concepts than to long written texts. Sometimes a quick visual outline communicates with multiple pages of internal notes.
Naturally We Switched To Microlearning
Another interesting thing happened a few weeks later. As creating videos becomes easier, we stop trying to create long training modules.
Instead, we started building:
- 30-second ride clips
- Short walk of SOP
- Visual reminders
- Quick feature descriptions
- Process-oriented mini-courses
People really looked at them. Long internal training videos often feel like homework. Short learning clips feel easy to use and easy to revisit later when someone needs help quickly. That change alone is likely to improve engagement more than any aspect of “AI.”
AI Still Needs Human Guidance
One thing quickly became clear: AI-generated training content still requires strong human input.
Quality mainly depends on:
- Context
- The structure
- Learning goals
- Clarity
- Understanding the audience
Good results came when:
- Instructional Designers manage the flow of learning,
- Team leaders review accuracy,
- AI has been managing repetitive manufacturing tasks.
Trying to automate everything used to create standard video content feels disconnected from the actual workflow, but using AI as a production assistant has worked surprisingly well. That balance was more important than trying to remove people from the process.
Why Small Groups Can Benefit Big
I honestly think that smaller L&D teams may benefit from this workflow more than larger enterprises. Large organizations often already have production systems in place. Small groups usually don’t do that. When you have limited time, limited planners, and constant requests for updated training materials, even small workflow improvements make a noticeable difference.
Maybe that’s why AI video tools are starting to come in handy for us—not because they’ve completely replaced traditional production, but because they’ve lowered the barrier to creating consistent visual learning content.
In particular:
- Riding
- Internal communication
- Process training
- Groups are distributed
- Multilingual learning support
Final thoughts
I don’t think AI video tools magically solve every training problem, but after a few months of experimenting with different workflows, I think they’re changing the way teams approach learning content creation. The big change isn’t “AI replacing training teams.” It’s like: “Teams can iterate learning content quickly without turning the entire review into a full production project.”
And honestly, in modern workplace learning, that would be a practical improvement anyway.
