I have spent the last 18 months living in the messy, exciting, and occasionally terrifying world of AI-assisted instructional design. In my decade-plus of experience as an L&D practitioner, I’ve seen teams trade quality for speed more times than I care to admit. When you combine that institutional pressure with generative AI, you get a recipe for "hallucinated compliance training" that could sink a department.
My ‘Gotchas’ doc—a growing list of real mistakes I’ve caught in AI drafts—is now longer than my actual project plans. We’ve seen AI invent corporate policies, misinterpret legal definitions, and use a tone that sounds like a robot trying to win an ‘Employee of the Month’ award. The solution isn't to ban AI; it’s to build a rigorous, targeted sme review template that forces humans to stay in the loop.
What Validation Actually Means in AI-Assisted L&D
Validation in the age of AI isn't just checking for typos. It’s about targeted validation. If you send an AI-generated draft to an SME and ask, "Does this look right?" you’ve failed. You will get back "Looks good to me," and six months later, you’ll be dealing with a messy audit because the AI hallucinated a deadline that doesn’t exist.
Validation means verifying three distinct pillars:
- Source Integrity: Does the AI’s output align with current, approved company documentation? Logical Cohesion: Does the flow make sense, or did the AI create a "Frankenstein" module by stitching together unrelated paragraphs? Tone and Brand: Is the voice appropriate, or does it sound like a sterile, corporate brochure written by a committee of droids?
Risk-Based QA: Not Every Asset Needs a Fine-Tooth Comb
One of the biggest mistakes I see junior IDs make is treating a 30-second microlearning tip the same way they treat a mission-critical safety or compliance module. Stop burning your SMEs out on low-stakes content. Apply a risk-based approach to your review cycle.
Risk Level Content Type QA Strategy High Legal, Safety, Compliance Full SME sign-off, source-check, legal review, and assessment "breaking" testing. Medium Software processes, Soft skills Targeted review of logic flow and technical accuracy by the SME. Low Team culture, Quick tips Internal ID peer review + basic editorial check. No SME needed.The SME Review Template: Targeted Questions
If you want efficient reviews, you have to ask specific, binary, or evidence-based questions. Don’t ask for feedback; ask for verification. Here are the review form questions that I use in my current workflow to ensure my SMEs actually look at the content.
The Core Review Framework
Source Verification: "For every key claim made in this section, please link or cite the internal document that confirms this is accurate." Policy Alignment: "Does this content reflect the most recent version of [Policy Name/Reference Number]?" Assessment Validity: "Are there any 'gotchas' in this assessment? Are there multiple correct answers, or is the correct answer ambiguous?" Efficiency/Conciseness: "Identify one paragraph or sentence that adds no value to the learner's ability to perform the task." Approval Capture: "I confirm this content is accurate, legally compliant, and ready for development. [Electronic Signature]"Notice that these questions are designed to move the SME away from subjective preference ("I don't like this word") and toward objective validation ("Is this factually true?").
The "Show Your Work" Requirement
When I use AI to reduce sme review cycle time generate content, I include a "Source Tracking" field in my project management tool. For every chunk of generated content, I require the AI to list the documents it used to derive the information. During the SME review, I make the SME verify those specific sources.
This does two things:
It forces the SME to check the source, not just the text. It creates a paper trail for future updates. If a policy changes in six months, I know exactly which modules used that source and need to be refreshed.How to Not Annoy Your SMEs (And Still Get Results)
SMEs are busy. If your review process is a bloated 40-page PDF, they will ignore it. Use a digital, modular review form. I use a simple Microsoft Form or a comment-enabled document that tracks every change.
Tips for Efficient Validation:
- Limit the scope: Only ask them to review the content that was AI-generated, not the entire course structure. The 48-Hour Rule: If they don't respond, the content is deemed "Approved for Pilot." This creates a sense of urgency. Contextualize the AI: Tell the SME: "I used AI to draft this based on your previous emails. Please correct the tone, but check the facts against the manual."
The "Breaking the Test" Mindset
Finally, as someone who spent years as an LMS admin, I cannot stress this enough: always test your assessments like a learner trying to break them. AI is notoriously bad at creating "distractors" for multiple-choice questions. It often makes the wrong answers obviously wrong or, worse, makes the "correct" answer defensible for the wrong reasons.
When an SME reviews an assessment, I ask them to purposefully pick the wrong answer to see if the feedback makes sense. If the AI-generated feedback is generic ("Incorrect, try again"), your SME needs to rewrite it to be diagnostic ("Incorrect, because X, try focusing on Y instead").
Final Thoughts
AI is a tool, not an author. The role of the instructional designer has shifted from "content creator" to "content curator and validator." Our job is to manage the flow of information, ensure the integrity of the data, and protect the learner from poorly synthesized AI drivel. Use a template, track your sources, and for the love of everything holy, stop accepting "looks good to me" as a sign-off.
Your ‘Gotchas’ doc is your best friend. Keep it updated, share it with your team, and stay skeptical. In L&D, skepticism isn't a personality flaw—it's a quality control requirement.