AI just made eLearning much easier to create
That doesn’t make good learning easier to design.
A membership organisation published new professional guidance. Its experts have worked through the detail, and the document gives members advice they need. However, it’s long. Finding time to read it properly is difficult, and knowing which parts affect your own work takes even more effort.
Members can have the guidance in front of them and still be unsure what to do. A course seems a sensible next step, especially if it helps them work through the decisions behind the advice.
Until recently, that could mean a sizeable production job. A team would need to decide what learners needed, develop the explanations and activities, produce and test the course. For a charity or membership organisation with a small team, the cost alone could put it out of reach.
This is exactly the sort of problem AI should help us solve.
Recent developments in tools such as Articulate are making it much easier to turn existing organisational knowledge into courses, scenarios, and interactive resources. More of an organisation’s knowledge can reach the people who need it, without every project requiring the same production effort.
For charities and membership organisations, that creates an exciting opportunity. Valuable knowledge that might previously have been too expensive to turn into learning can now become accessible to a much wider audience. Organisations can develop resources that strengthen member value, support professional development and potentially create new sources of income.
But uploading a document and producing something that looks like a course isn’t the same as designing useful learning. The opportunity isn’t simply to produce more content at lower cost. It’s to make genuinely effective learning more accessible and affordable.
Information with extra steps
Upload a guidance document to an AI tool and ask it to create a course, and the result will often follow the document’s structure. Sections become screens, some paragraphs become interactions, and a quiz checks whether the learner remembers what they have read.
The result can look polished, but it can also leave learners wondering why they couldn’t simply read the document. The document tells AI what the subject is, but usually tells it very little about the people who actually need to learn it.
For our membership organisation, suppose the guidance concerns a change in professional regulation. A course explaining the revised requirements sounds straightforward enough, but an experienced member and someone new to the profession may arrive with quite different problems.
The experienced member knows the framework; they want to understand what has changed and how it affects their practice. Asking them to work through the whole background again is likely to feel like a poor use of their time.
A newer member may need that background before the change makes sense. An update which assumes they understand the existing requirements could be accurate throughout and still leave them struggling to follow it.
Put both groups into the same course and you can quickly end up compromising for both. By that point, if the content has already been built, fixing it means reworking the course.
The problem starts when the source document becomes the brief. Learning designers and subject experts need to establish who the learning is for, and what it needs to achieve.
Your experts can describe the audiences, what they already know, and the misunderstandings they commonly encounter. Our learning designers use that insight to shape an early outline. AI can then help examine the outline for explanations that assume too much, or material experienced members may find repetitive.
These findings still need expert review. A simulated learner’s response isn’t evidence that a real member has understood the course, but it can help identify questions worth investigating before development progresses.
That review may reveal that one course doesn’t make sense at all. Experienced members might need a short piece of microlearning focused on the change and its practical implications, whilst newer members may need a fuller course which explains the underlying requirements and gives them practice applying them.
Used properly, AI makes it much easier to test ideas before you’ve built half the course. Subject experts can focus their review on whether the proposed learning reflects what members need, while the design is still easy to change. For the organisation commissioning it, that can mean less avoidable reworking and fewer demands on experts’ time later.
Expertise is still the advantage
An organisation’s experts know things that rarely make it into the guidance itself. They may have spent years answering questions about an exception members keep overlooking or seen how advice that seems clear on paper becomes difficult to apply in practice.
That’s the kind of knowledge AI doesn’t have unless you give it. A request to “create a realistic scenario” leaves the model to guess what realistic means, whereas an expert can describe situations members regularly face, explain why a tempting response causes problems, and identify what a good decision needs to consider.
Our learning designers shape that input into meaningful practice, with AI helping to develop activities and draft feedback for review.
The difference becomes obvious when you look at the scenarios. If the right response is obviously sensible, and the alternatives are plainly foolish, there isn’t much of a decision. Expert input helps make the alternatives credible and the feedback useful.
That’s where good learning design adds value. A well-designed course doesn’t simply make information easier to consume. It gives learners opportunities to apply what they’ve learned, practise making decisions, explore consequences and receive meaningful feedback. It helps them develop confidence before facing those situations in their work.
For charities, the expertise behind that learning may come from frontline work or listening to the people they support. For professional bodies, it may come from advice services and years of working with members. Feed that knowledge into the design, and the course starts to feel like the world learners actually work in.
Your subject experts shouldn’t need to become instructional designers, or learn how to build AI workflows, just to get a good course made. Their time should go into the judgements only they can make.
At GetSavi, our approach brings together three things: your specialist knowledge, our learning design expertise, and the production advantages of AI. Our job is to use your experts’ input well, take responsibility for designing and producing the learning, and use AI to make the process more efficient.
Remember, your name is on the course
A member who trusts your guidance will expect a course carrying your name to reflect the same care.
AI can now produce fluent narration and professional-looking content very easily. That can make a course look authoritative long before anyone has checked whether it actually is.
An important qualification may have disappeared when the guidance was simplified, or an example may suggest a response that your experts would advise against. The course can look finished and leave someone confident in the wrong decision.
The learner may have no idea how the course was made, but they know whose logo is on it.
For an organisation whose value rests on trusted expertise, that’s important. Expert review needs to establish that the learning preserves the meaning and limits of your guidance, whilst testing with members needs to show whether they can actually use it.
AI should save organisations time and money, but those savings disappear quickly if the course needs extensive reworking or simply isn’t good enough to put your name on it.
The real opportunity is to combine the efficiency of AI with the expertise that makes learning valuable in the first place.
For charities and membership organisations, this could change what’s commercially possible. Knowledge that was previously too expensive to turn into learning can become practical, engaging resources that help more people develop their skills and make better decisions. Existing learning can be updated more readily, and new programmes can become viable at a cost that would previously have been prohibitive.
At GetSavi, we create AI-accelerated eLearning for charities, membership organisations and other purpose-led organisations. By combining your specialist knowledge with our learning design expertise and the production advantages of AI, we help turn that opportunity into learning that’s practical, credible and worth people’s time.
Could AI help you create better eLearning within your budget?
If you have valuable knowledge you’d like to turn into engaging, effective learning, we’d love to explore what’s possible.
Contact Allen Reid at allen.reid@getsavi.co.uk to start a conversation.
