How Course Production Is Evolving With AI
Asking whether AI can save Instructional Designers’ time feels like yesterday’s question. It can, and it already does. In a 2026 survey of 587 Instructional Designers, 73% said they use AI often or daily, and 79% cited time savings as a primary reason. [1]
Although today’s AI stack supports almost every stage of course development, those capabilities often sit in separate tools. In practice, this means that you structure the course in one, create visuals in another, generate narration or translations elsewhere, and then bring the outputs back into the authoring environment where you assemble the course.
That’s the gap some authoring tools are now trying to close by bringing more AI capabilities into a single production workflow and giving course creators a more seamless authoring experience.
What An Integrated AI Authoring Workflow Looks Like
iSpring Suite AI is a useful example of how this more integrated model is taking shape. The tool combines PowerPoint-based desktop authoring with online course creation, supporting slide-based and scrollable courses, assessments, role-plays, and video content.
AI first appeared in iSpring Suite to help with individual authoring tasks. Since then, each new release has brought AI deeper into the authoring process. The latest updates take another step forward, turning individual AI capabilities into a much more connected, AI-assisted workflow. Let’s see how this works in practice.
Less Time Staring At A Blank Page
The “blank page” in corporate course development is rarely actually blank. More often, you have too much to work with: SME decks, policy documents, meeting notes, or an old course.
In both the desktop and cloud authoring environments, you can start with a topic or provide existing source materials and have AI turn them into a working course draft. Rather than simply summarizing the input, it builds out learning objectives, content, and assessments that you can then edit, fact-check, and develop further.
The tool uses Bloom’s Taxonomy to formulate objectives at different cognitive levels, match questions and activities to the kind of thinking learners need to practice, and move the course from basic understanding toward application and analysis.
This certainly doesn’t eliminate the need for an ID to judge whether the sequence actually works for a particular audience or business problem, but you will definitely save a fair amount of the mechanical work involved in converting raw input into something structured.
Custom Visuals That Actually Fit The Content
Stock libraries cover a lot, but the more specific the audience, scenario, or learning context, the more time you can spend searching for something that is merely “close enough.” iSpring Suite AI addresses that by bringing image generation into the authoring workflow.
That’s especially useful for scenario-based training, niche subject matter, or courses that need a consistent visual language across multiple screens. You can iterate on the prompt, style, and format until the image actually fits the learning context, and do so without turning visual sourcing into a separate production task.
Streamlined Narration With Less Recording Overhead
Narration gets expensive surprisingly fast once a course starts changing. A revised paragraph can mean another recording session, another edit, and another round of syncing audio with the module. Multiply that across several modules or languages, and voice-over quickly becomes a big issue.
iSpring has made it possible to generate a narration from the script, review how it sounds, and replace it just as easily when the content is updated. The tool uses ElevenLabs voices, so the result is designed to sound natural rather than like a basic text-to-speech layer.
Presenter Videos That Are Easy To Keep Current
Presenter video has traditionally been one of the least flexible elements in a course. Once it’s filmed, the content is largely locked into the recording.
AI avatars change that model. In iSpring Suite AI, the presenter is generated from the script, with the avatar, voice, and background selected within the tool. That means the video behaves much more like another editable course element than a finished production asset.
For IDs, that opens up more practical uses for presenter-led content: short explainers, course introductions, product updates, or expert-style segments where the effort and expense of organizing a traditional shoot would outweigh the value of the video.
Course Localization That Keeps The Workflow Intact
Creating a version of a course in another language usually involves more than sending the text through a translator. Once the copy leaves the authoring environment, someone still has to put it back in the right places, check that the structure survived, and make sure nothing was lost along the way.
iSpring Suite AI keeps that initial translation within the course itself. The text is translated while the existing structure stays in place, so you start with a complete language version rather than a pile of translated copy that still needs to be rebuilt into the course.
It doesn’t replace localization work that requires cultural adaptation, terminology expertise, or market-specific review. Instead, it can make the translation stage much faster, leaving more time for a higher-value review.
Instant Product Help Inside The Authoring Flow
Course production generates a steady stream of product questions: how a particular interaction behaves, which publishing setting fits the use case, or how to configure a specific element.
iSpring’s AI assistant helps exactly with that. You can ask a question in natural language and get step-by-step guidance based on iSpring’s documentation, along with links to relevant resources when you want to go deeper. It can also translate content from the English-language help center and respond in your native language.
In practice, that means less time spent testing settings, retracing steps, or figuring out which product option does what. You can move from a question to the right action faster and keep the course moving.
Closing
When you choose an AI environment for your ID tasks, don’t judge it only by the quality of the first output. Use a real course project and monitor where your time goes: preparing first drafts, cleaning it up, creating media, handling revisions, translation, and moving content between tools.
If you want to run that kind of test with iSpring Suite AI, you can get a free 14-day trial. Use a real course in progress rather than a demo topic: upload the source material you normally work with, make a few realistic changes after generation, and see how much of the production cycle you can keep concentrated in one place
Reference:
[1] How instructional designers are really using AI
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