Using AI to Enforce Your eLearning Style Guide
Every team has an eLearning style guide, and most teams also have courses that ignore it. That rarely happens on purpose; it's simply difficult to remember forty rules about button labels, capitalization, feedback wording and product names while you're building screen 63 on a deadline. Reviewers catch some of it, but much of it slips through. Can AI help you actually enforce your style guide across every course, without adding hours to every review?
Yes: an AI assistant can check course text against your eLearning style guide quickly and consistently, as long as you turn the guide into clear, checkable rules and give the assistant your course text in a format it can read. Set it up once as a reusable assistant with your rules and glossary built in, export the text from your authoring tool, and ask for a table of issues with their location and a suggested fix. It catches the repetitive problems people miss, like inconsistent terms, wrong button labels and passive feedback. A human still makes the final call on every change, especially on tone and anything that depends on what's on screen.
Why Style Guides Get Ignored
It's rarely laziness. Style guides are long, live in a shared drive nobody opens, and mix broad principles ("friendly, direct voice") with tiny details ("use 'Select,' not 'Click'"). Developers remember the broad principles and forget the details, while reviewers focus on content accuracy and don't have time to check every label.
The result is drift. Course A says "Submit," Course B says "Check Answer," and Course C uses both. Learners notice, even if they can't identify what feels wrong, because consistent wording makes a course catalog feel professional and makes each course easier to use.
Step 1: Turn Your Style Guide into Checkable Rules
AI follows specific rules far better than general advice, so go through your style guide and rewrite each item as something you could verify with a yes or no. For example:
| Vague guidance | Checkable rule |
|---|---|
| Keep it friendly | Address the learner as "you." Use contractions. |
| Be consistent with buttons | Buttons use only: Next, Back, Submit, Continue, Try Again. |
| Write clear feedback | Feedback starts with "Correct" or "Not quite," then explains why in one or two sentences. |
| Use the right product names | Use the glossary spelling and capitals for every product name. |
| Keep it readable | Sentences under 25 words. Spell out acronyms on first use per module. |
If you don't have a style guide yet, borrow structure from a good one. The Microsoft Writing Style Guide is free, clear and full of rules for interface text that translate well to eLearning.
Step 2: Build a Reusable Assistant
Don't paste your rules into a new chat every time, because most major AI tools let you save instructions and reference files so they apply to every conversation. In ChatGPT, that's a custom GPT, and in Claude, it's a Project with instructions and files. Microsoft Copilot and Gemini offer similar options, depending on your organization's setup.
Load the assistant with three things:
- Your checkable rules, numbered, so the assistant can cite them.
- Your glossary of approved terms, product names and acronyms.
- Instructions for the output, such as "Return a table with: screen ID, original text, rule number, suggested fix."
Numbered rules matter. When the assistant says "Rule 7," the developer can look it up, and you can quickly see if it's applying a rule wrongly.
Step 3: Get the Course Text Out of Your Authoring Tool
The AI needs the actual words, and most authoring tools can export course text for translation. Storyline can export text to a Word document, and Rise can export a translation file, which gives you every text string in one place. You can also check storyboards before the build, which is even better, because fixes in a document are cheaper than fixes in a built course.
Include slide or screen identifiers in the export so that every issue the AI finds points to a specific location, which is the difference between a useful review and a vague list of complaints.
Step 4: Run the Check and Review the Results
Upload the export and ask the assistant to check every screen against every rule, listing issues only instead of rewriting the whole course. Then review the table: accept the clear fixes, reject the ones that miss context, and note any rule the assistant keeps misapplying so you can rewrite it more clearly.
A typical first run on an older course finds plenty: inconsistent button labels, product names in three spellings, feedback that just says "Incorrect," and acronyms nobody spelled out. Fixing them is usually quick, while finding them by hand is what used to eat a whole review round.
Where AI still needs you: the assistant only sees text. It can't tell whether a label matches the button on screen, whether an image fits the message, or whether a "rule break" was a deliberate choice. A human reviewer makes the final call on every suggested change.
When Should the Check Run?
Run it at three points, and it gets cheaper each time. First, run it on the storyboard before anything is built, where most fixes take seconds. Second, run it on the alpha build to catch text that changed during development. Third, run a quick final pass before the gold version, mainly to catch anything added during review rounds.
Keep a simple log of what the check finds on each project, because after a few courses, patterns appear. Perhaps one rule is broken constantly, which means the template should enforce it or the rule needs clearer wording. Maybe one rule never fires, which means you can drop it from the check. The log turns the style guide into something that improves over time instead of sitting in a folder.
What Else Can AI Check in an eLearning Style Guide?
Once the basic setup works, you can extend it to other parts of your style guide:
- Alt text. Check that it's present, short and describes purpose, not just appearance.
- Reading level. Flag screens with long sentences or heavy jargon.
- Inclusive language. Flag terms your guide asks you to avoid.
- Quiz items. Check that questions follow your rules for format and feedback.
- Narration scripts. Check for words the narrator should avoid or pronounce a certain way.
Start with the rules that cause the most rework, then add more once the team trusts the process.
Make Your eLearning Style Guide Stick
An eLearning style guide only matters if courses follow it. AI makes that practical by checking every screen against every rule, quickly and without getting tired. Your job is to write clear rules, keep the glossary current and make the final call on each change.
Choose the course that's due for an update anyway. Turn your top ten rules into checkable statements, set up a reusable assistant, export the text and run a check, and once the process works, add it to your standard review steps. The same draft-then-check approach pays off during the build itself, and knowing where AI in Articulate Storyline saves the most clicks helps you decide what to hand it next.