Here’s a truth that’s easy to overlook in the excitement of generative AI: the moment you click “generate” is not the moment your learning content is finished. It’s the moment the real work of instructional design begins.

AI tools can now produce draft storyboards, assessment items, job aids, and microlearning modules in minutes rather than weeks. That’s genuinely remarkable. But speed without governance is just a faster way to distribute content that may be inaccurate, biased, off-brand, or androgogically unsound. If your organisation is using AI to develop training — and increasingly, most are — you need a clear, practical process for reviewing what it produces before it reaches learners.

What follows is a governance checklist we’ve been refining in our work with instructional designers and L&D teams. It’s not meant to slow you down. It’s meant to keep your credibility intact.

The Five-Gate Review: What to Check Before AI Content Goes Live

Think of governance not as a single quality pass, but as a series of gates. Each one catches a different category of risk. We recommend running every piece of AI-generated content through these five:

• Gate 1: Factual Accuracy. AI models generate plausible-sounding text, not necessarily true text. Every claim, statistic, regulation reference, and procedural step must be verified against authoritative sources. This is especially critical in compliance training, safety content, and anything involving organisational policy. Assign a subject matter expert (SME) to sign off on factual claims — no exceptions.
• Gate 2: Instructional Integrity. Does the content actually teach? AI tends to produce information dumps rather than well-scaffolded learning experiences. Check that the content follows sound instructional design principles: clear learning objectives, appropriate sequencing, meaningful practice, and aligned assessments. If you’re using a framework like Bloom’s Taxonomy or Merrill’s First Principles of Instruction, confirm the AI output actually maps to it — don’t assume it does.
• Gate 3: Bias and Inclusivity. Generative AI reflects the biases present in its training data. Review content for cultural assumptions, gendered language, ableist framing, and examples that default to a narrow demographic perspective. Pay particular attention to Indigenous considerations, bilingual requirements, and the diversity of your workforce. A second set of eyes — ideally from someone with a different lived experience — is invaluable here.
• Gate 4: Brand Voice and Organisational Alignment. AI doesn’t know your organisation’s tone, values, or internal terminology. It will cheerfully produce content that sounds generic or, worse, contradicts your culture. Review for alignment with your style guide, your organisation’s stated values, and any sector-specific language conventions. If it doesn’t sound like something your team would say, rewrite it until it does.
• Gate 5: Legal and Intellectual Property. Who owns AI-generated content? Does it inadvertently reproduce copyrighted material? Are there privacy implications in the prompts you used to generate it? These questions are still evolving legally, but your organisation should have a position on them. Document the AI tools used, the prompts provided, and any human modifications made — this creates an audit trail that protects you.

Building the Habit: Governance as Workflow, Not Afterthought

The biggest mistake we see teams make is treating AI content review as an ad hoc exercise — something that happens when someone remembers to do it. Governance needs to be embedded in your content development workflow from the start.

Here are three practical steps to make that happen:

• Create a one-page review template. List the five gates above with checkboxes and space for reviewer names and dates. Keep it simple enough that people will actually use it.
• Assign clear roles. Decide who is responsible for each gate. Factual accuracy might sit with an SME, while instructional integrity stays with the instructional designer. Don’t let “everyone reviews everything” become “no one reviews anything.”
• Set a revision cadence. AI-generated content can be updated quickly — which is a strength — but only if you schedule regular reviews. Quarterly audits of high-stakes content (compliance, safety, onboarding) should be the minimum.

The Real Competitive Advantage

Organisations that use AI well in L&D won’t be the ones that generate content fastest. They’ll be the ones whose learners and stakeholders trust that the content is accurate, thoughtful, and worth their time. Trust is built through visible rigour, not invisible automation.

The checklist above isn’t complicated. But applying it consistently is a discipline — and it’s a discipline that separates professional instructional design from content that merely looks professional.

If your team is navigating the shift to AI-assisted content development and wants to sharpen your instructional design and review processes, FKA’s Instructional Design and Performance Consulting programmes can help. We’d love to work through these challenges with you — because the human side of learning design has never mattered more.