If you’re creating online courses – whether you’re an individual course creator, part of an L&D team, or running your own learning business – you’re probably asking: Where does AI actually fit into my workflow? Not “Should I use AI?” but “Which parts of my process should I automate, and choose the right AI-Powered course creation workflow?”
Over the last few years, I’ve incorporated AI into my course development practice and worked with clients on research, proof-of-concept, and live implementation projects. What I’ve discovered is this: AI can dramatically streamline your timeline – but only if you understand where it genuinely adds value and where it can create more work than it saves.
Almost every tool now claims to be “AI-powered”, but the quality of outputs varies wildly. So let’s get practical and walk through the actual stages of course creation – and where AI genuinely helps versus where it falls short.
What You Need to Create and Host an Online Course: The Components of AI-Powered Course Creation Workflow
Before we talk about AI, let’s map the fundamentals. To create and offer an online course, you need three things in place:
1. Curriculum materials – the intellectual scaffolding of your course: module outlines, learning outcomes, content structure, assessment strategies.
2. Tools to produce course content – the authoring layer where you build text, videos, interactive activities, quizzes, assessments, and feedback mechanisms.
3. A platform to host everything – either a traditional learning management system (LMS) or a dedicated online school platform.
Each layer of this AI-powered course creation workflow has its own AI opportunities and limitations.
Aspect 1: Curriculum Development (Where AI Excels)
I’d be genuinely surprised if there are still practitioners not using AI for curriculum research, analysis, idea generation, and drafting module outlines and storyboards. This is where AI delivers real value with minimal friction.
The popular tools – ChatGPT, Gemini, Claude, Perplexity – all work well for this phase. You generate documents you can act on, often including module structures, learning outcomes, and storyboard drafts. There are tools that generate slides and images too, though I’m still not entirely satisfied with visual quality across the board.
The advantage here is speed and iteration. You can generate five different curriculum approaches in an afternoon, refine them based on your learning science knowledge, and use the best version as your foundation. AI handles the heavy drafting; you handle the strategic thinking.
Key takeaway: Use AI generously in this phase. The output quality is high enough to be genuinely useful, and the time savings are substantial.
Aspect 2: Content Authoring (Where Platform Choice Becomes Critical)
This is where things get more complicated – and where your choice of authoring tool matters enormously.
The traditional approach: You design content with AI assistance, then author it using dedicated tools like Articulate Storyline, Adobe Captivate, or similar. You produce interactive courses offline, then upload them to your LMS.
The emerging shift: More platforms now offer AI-assisted authoring that converts your content into interactive courses you can share, embed, and export as presentations, SCORMs, PDFs, and other formats. Examples include Courseu (particularly strong pedagogically) and Midsmith.
The question is: Should you author separately, or look for a platform that combines design, authoring, and hosting? The answer depends entirely on your platform choice and your budget. .
Aspect 3: Learning Platforms – The Real Differentiator
Here’s where I see the biggest variability in what “AI-powered” actually means.
Traditional LMS approach: You approve your curriculum, create your content using external tools, and upload it to your LMS. You combine this with native LMS elements – pages, quizzes, assignments. You’re doing the assembly work yourself.
AI-powered LMS (e.g., Rise Up, Thrive): The platform helps you generate course structure and basic content using AI. You upload a PDF or provide prompts, and the system creates module structure and text blocks. Some generate images and videos. But the authoring is still fairly basic – you’re getting structure and foundational content, not rich interactivity.
AI-superpowered LMS (the rare tier): These platforms go further. They generate structure and interactive content – activities, quizzes, scenarios, assessments, even video avatars. Phases that used to run separately now collapse into one streamlined workflow.
Here’s my honest assessment based on extensive testing:
Sana Learn is my favourite in terms of user experience, learner engagement, and workflow efficiency. It creates courses, lessons, interactive activities, quizzes, scenarios, and instant feedback – all within the platform. It integrates Synthesia, so you don’t create videos externally. The admin and reporting layers are solid, and the learning experience is genuinely polished.
Coursebox AI can generate similar elements, but the learner and admin experience lags behind. It doesn’t feel as robust as an LMS, and the backend options are more limited. The trade-off is affordability – it’s significantly cheaper.
Cyper LMS – really decent structruring and basic content generation with several options including microlearning format.
Rise Up and Thrive are strong for structure and basic content generation, but they don’t author interactive content to the same depth.
Watch this space: Learnupon recently acquired Courseu, which is one of my favourite pedagogically grounded, AI-powered authoring tools. This could be a game-changer.
Three scenarios for building and assembling your courses
Let me map this clearly. In my six-phase course development framework, Phase 4 is the critical branching point. This is where your platform choice determines your entire workflow.
Scenario 1: Traditional LMS + External Authoring
- Manually build the LMS structure.
- Author all content (images, videos, interactive elements) in external tools.
- Upload and assemble everything in the LMS.
- Timeline impact: Sequential. Longer overall timeline. More tool-juggling. Longer Assembly.
Scenario 2: AI-Powered LMS (Basic)
- Use LMS’s AI to generate structure and flow.
- Generate basic elements (text blocks, quizzes, assignments and if you choose, also images and AI video).
- Author multimedia and rich interactivity externally.
- Upload and finalise assembling in the LMS.
- Timeline impact: Faster structure phase, but still external authoring work and assembly time
Scenario 3: AI-Superpowered LMS (Advanced Authoring)
- Generate structure, core content, assessments, and interactive activities within the platform.
- AI handles much of the formatting and media generation, tweaks and corrections us usually needed.
- Everything is authored and assembled in one place.
- Timeline impact: Dramatically compressed. Fewer handoffs. Less file-juggling.
The resource cost and timeline savings of Scenario 3 are genuinely significant. With traditional approaches, you’re managing files across multiple tools, versions, and platforms. With AI-native authoring, the heavy lifting – formatting, structure, basic media – is streamlined. You focus on learning design and quality assurance, not asset management.
The Non-Negotiable Rule: Validation Still Matters
But here’s my firm principle across all scenarios: Always review content quality, navigation, flow, pedagogical value, and accessibility before launch. AI can accelerate production speed, but only if you keep quality gates in place. Without them, fast production can become future rework. You want to catch issues before they cascade across an entire course.
Which Workflow Is Right for You?
If you’re trying to decide which direction to explore:
- Choose Scenario 1 (traditional LMS + external tools) if you need fine-grained control over interactive design and you have the team capacity to manage multiple tools.
- Choose Scenario 2 (AI-powered LMS with basic generation) if you want some AI assistance with structure but plan to author rich content separately.
- Choose Scenario 3 (AI-superpowered authoring) if you want to compress your timeline, reduce tool-switching, and have a budget for the platform that can handle both structure and interactive authoring.
My personal preference? Sana Learn for the combination of pedagogical robustness, learner experience, and workflow efficiency. But that’s a significant investment. Coursebox AI offers similar core authoring capabilities at a lower price point, though the experience isn’t quite as polished for learners and admins.
I’ve detailed all three scenarios, with real examples and templates, in my six-phase course development framework on the blog. It’s the exact map I use with clients.
Final Reflection
The real question isn’t whether AI will transform course creation – it already has. The question is whether you’ll choose a workflow that genuinely serves your team and learners, or just adopt whatever tool has the flashiest marketing.
Platform choice shapes everything: your timeline, your team’s experience, your learners’ experience, and ultimately, the quality of the courses you create. Choose thoughtfully.
Which scenario are you closest to right now? Are you juggling traditional LMS plus external tools, or have you started exploring AI-native authoring platforms? I’d genuinely like to hear what’s working in your practice – and what’s been frustrating.
Drop a comment below or book a meeting with me if you need help.
Note, that this post provides general information about AI-powered course creation.
It is important always to consider the specific context and requirements of your learning projects. If you have any questions or would like to delve deeper into the topic, please email me or book a free online consultation via my contact page.
Make sure to check out my other posts related to planning online courses, designing and developing learning content and delivering training. I share strategies and tools that you can use and many practical tips.
