Training content took too long to update
A few months ago, our team realized something frustrating. It’s not like we had a hard time creating training content. We were having trouble keeping it updated. Every time we needed a new onboarding tutorial, process walkthrough, or internal explanation, our workflow became larger than expected.
Create a script Record your screen Edit your clips Modify subtitles Export revisions Submit a draft for feedback
Even a short internal video can easily take several days. And the worst part was that some of the material was already outdated by the time it was completed. For small teams, especially those without a dedicated video editor, this process can quickly become difficult. Initially, we weren’t actively looking for an AI video generator. To be honest, we were just looking for ways to reduce production friction.
Why traditional training videos feel heavy
One thing I’ve noticed is that most in-house learning content follows the same old production logic. That means creating one polished training video and sticking with it for months. However, modern workflows are no longer so slow-moving. Products are constantly updated. Internal tools change. The process evolves. Also, onboarding materials often require small revisions every few weeks.
This means teams spend more time maintaining training content than actually improving the learning experience itself. The larger the organization, the more difficult the cycle becomes.
Started testing short AI video workflows
Our first experiment was actually very simple. We wanted to see if AI-generated videos could help us prototype learning content faster before investing time into full production.
Most tools we tried felt one of the following:
Too much focus on social media Too many templates or difficult to control consistently
That’s why we discovered an AI video tool that allows you to easily and quickly test within your browser without changing your existing workflow too much. What immediately stood out was how quickly I was able to translate rough ideas into visual drafts.
Instead of spending hours editing placeholder videos just to explain a concept in-house, you can quickly create short visual sequences like this:
Onboarding Ideas Workflow Demonstration Internal Process Explainer Customer Education Concepts
This changed our review process more than we expected.
The biggest benefit was not “automation”
Many believe that AI video is primarily aimed at completely replacing production tasks. That wasn’t our experience. In fact, the biggest advantage was repetition speed.
Previously, even small changes caused extra work.
Reopen project Re-edit clip Export again Update subtitles Repeat approval cycle
Once visual prototyping became easier, our team started testing ideas fairly early in the process. And to be honest, the conversation improved because stakeholders responded more to a high-level visual concept than a long document. Sometimes a simple visual draft can provide more information than a few pages of internal memos.
A natural transition to microlearning
Another interesting thing happened a few weeks later. As creating videos became easier, we stopped trying to create long training modules.
Instead, I started building the following.
30-second onboarding clips Short SOP walkthroughs Visual reminders Quick feature descriptions Process-focused mini tutorials
And people actually observed them. Long internal training videos usually feel like homework. I felt the short learning clips were easy to use and easy to reuse later if someone needed immediate help. This change alone probably increased engagement more than any other “AI feature”.
AI still needs human guidance
One thing became immediately clear. That said, AI-generated training content still requires strong human input.
Quality largely depends on:
Contextual structure Learning objectives Clarity Audience understanding
Best results were obtained when:
Instructional designers handled the learning flow, team leaders reviewed accuracy, and AI handled repetitive production tasks.
Attempting to fully automate everything usually results in generic video content that feels disconnected from the actual workflow, but using AI as a production assistant worked surprisingly well. That balance was much more important than trying to remove humans from the process.
Why small teams get the most benefit
Honestly, I think smaller L&D teams are more likely to benefit from these workflows than larger companies. Large companies often already have operational systems in place. Small teams usually don’t. When time is limited, editors are limited, and up-to-date training materials are constantly requested, even small workflow improvements can make a noticeable difference.
This is probably why AI video tools are starting to come in handy for us. Not because AI video tools have completely replaced traditional production, but because they have lowered the barrier to creating visual learning content more consistently.
Especially suitable for:
Onboarding Internal Communication Process Training Distributed Teams Multilingual Learning Support
final thoughts
I don’t believe that AI video tools will magically solve all training problems, but after several months of experimenting with different workflows, I do believe that AI video tools have changed the way my team approaches learning content creation. The biggest change is not that AI will replace training teams. That means teams can iterate on learning content faster without turning every update into a full production project.
And to be honest, that might be a more practical improvement for modern workplace learning anyway.
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