GenAI Use Cases for Instructional Designers and L&D Teams

Instructional designers and L&D professionals, welcome to your AI era. Between storyboarding a new micro-course, revamping an onboarding program, or fielding five SME calls all before noon, you’ve probably wondered: “Can AI actually help me?”

This article isn’t a deep dive into some far-off tech future; it’s a hands-on guide for people who care about building clear, useful learning experiences that actually work in the real world.

Here, you’ll find real-world use cases of generative AI for instructional design and learning & development professionals. Things you can actually apply and ideas that don’t require a PhD in prompt engineering. And, because life’s too short for vague tech speak, we’ll connect the dots between AI and what you’re already doing every day.

Three Big Wins for Learning Teams Using GenAI

1. Accelerate Progress

Speed is a beautiful thing, when it doesn’t cut corners. While AI can’t replace your experience or creative instinct, it can cut down the time it takes to go from idea to implementation.

Say you’re building a conflict resolution course for frontline managers and need a realistic scenario to kick things off. You’ve got your core outcomes and a rough outline, but you’re stuck staring at your screen. This is where AI can step in to speed up your brainstorming process and sketch out a rough draft.

Prompt Example:
“Generate a workplace scenario involving a conflict between two team members about missed deadlines. Include dialogue that shows different conflict styles.”

2. Increase Productivity

There’s busy…and then there’s instructional design busy. If your to-do list looks like a multi-tab spreadsheet held together by conditional formatting and a prayer, AI can step in. It’s like hiring a personal assistant who never sleeps, doesn’t mind the grunt work, and won’t judge you for still being in sweats at 2 p.m.

Say you’ve just wrapped a new onboarding course and need to prep a facilitation guide for the trainer. You can try this:

Prompt Examples:
“Draft a trainer’s facilitation guide using this slide deck and speaker notes. Include key talking points, timing suggestions, and tips for audience engagement.”

3. Strengthen Governance + Brand Voice

Good instructional design doesn’t just inform, it reflects your brand. When courses come from ten different contributors, it shows. One module sounds like a legal memo, another reads like a group text. AI can help by checking tone, flagging off-brand language, and making sure content stays clear and accessible.

Say you’re developing compliance training for a healthcare organization. Between tone restrictions, ADA guidelines, and a long list of what not to say, the margin for error is small. Before you finalize course content, cue up a prompt like this:

Prompt Example:
“Review this course script and revise any sections that don’t align with our brand tone. Make it compliant with accessibility standards (e.g., plain language, avoid idioms, use short sentences).”

For Instructional Designers

Instructional design is equal parts creative spark, learning science, and deciphering the SME email that landed in your inbox at 11pm. You’re expected to build experiences that are outcomes-aligned, learner-friendly, media-rich, accessible, inclusive, and oh yeah…done by Friday.

That’s where generative AI can step in. It’s not meant to replace your brain (or your knack for turning chaos into clarity), but to give you back some breathing room, to help you design smarter, think deeper, stress less, and maybe even reclaim your weekends.

Here’s how instructional designers are using AI as their go-to collaborator.

1. Generate Course Outlines Based on Learning Outcomes

Solid learning objectives are the backbone of any good course. Turning those into a full course structure, that’s where the heavy lifting begins. With generative AI, you can prompt a course outline based on your learning goals, audience, and delivery format. Want it mapped to Bloom’s taxonomy? With scaffolding built-in? Aligned to a specific modality? Simply ask.

Prompt Example:
“Create a course outline for [topic] designed for [audience type, e.g., new managers in healthcare]. Align it to [Bloom’s level, e.g., application and analysis], include 5–6 modules, and suggest assessment types and delivery formats (e.g., video, interactive, text-based).”

♦️ Design Tip: Ask for suggested formats for each module (i.e., videos, case studies, interactive quizzes, reflection prompts).

2. Write Scenarios and Branching Dialogues

Building realistic simulations or choose-your-path scenarios takes time. Like, a lot of time. AI can help you script scenario-based dialogues with multiple outcomes, emotional tone variations, and context-specific responses. Let’s say it’s a customer conflict simulation or a leadership dilemma, you can generate branching scripts in minutes and then refine them like the brilliant editor that you are.

Prompt Example:
“Generate a branching scenario for a training module on [topic]. The learner should face a decision with three options, each leading to a different consequence. Include realistic dialogue, emotional cues, and a brief debrief for each outcome.”

♦️ Design Tip: Try building a soft-skills simulation with three learner choices per scene and built-in feedback tied to each decision path.

3. Summarize SME Transcripts

We love our SMEs, but their 60-minute lecture recordings…not so much. Instead of replaying the same audio five times to catch that one quote about compliance training, AI can transcribe, summarize, and highlight key moments for you. In minutes, you’ll have the major talking points, action items, potential learning objectives, and even quotes to use in your content.

Prompt Example:
“Summarize this transcript into 5 key points, highlight any action items or course-relevant examples, and identify content that could be used for quiz questions or discussion prompts.”

♦️ Design Tip: Ask AI to extract quiz-worthy content or suggest potential module titles based on the transcript.

4. Repurpose Existing Content

You know that one PDF the instructor swears “has everything you need?” Cool. Except it is long, text-heavy, and not exactly ready for the modern learner. AI can help you break it into something a lot more learner-friendly. Upload it, prompt AI to chunk it, and watch as it transforms into Rise micro-modules, quiz questions, visual slide prompts, or text for a video explainer.

Prompt Example:
“Break this PDF content into short learning segments suitable for Rise 360. For each segment, write a brief intro, 2–3 key takeaways, and a knowledge check question. Keep tone conversational and learner-friendly.”

♦️ Design Tip: Try turning a dense policy doc into a compliance eLearning course with a quiz, a scenario, and a knowledge check all in one session.

5. Generate Assessments at Bloom’s Levels

Writing solid multiple-choice questions is its own kind of art. Writing them at the right level of Bloom’s is another story. AI can help you build both formative and summative assessments aligned to specific cognitive levels, without spending your whole afternoon in analysis paralysis.

Whether you need application-level questions with targeted feedback or evaluation prompts for a discussion board, you don’t need to start from scratch anymore.

Prompt Example:
“Write 5 multiple-choice questions for [topic], targeting the ‘analyze’ level of Bloom’s taxonomy. Include four answer options per question, explain the correct answer, and provide brief feedback for each option.”

♦️ Design Tip: Use AI to rewrite questions for accessibility, reword for plain language, or tailor content for specific learner audiences. That way, your assessments meet more learners where they are.

6. Draft Rubrics or Align with Learning Standards

Rubrics: essential, but time-consuming especially when you’re aligning to UDL, Quality Matters, or your institution’s internal review checklist. AI can help you draft rubrics, polish criteria language, and ensure consistency across your deliverables.

Just feed it your learning outcomes and assignment type, and watch it create scoring levels, criteria descriptions, and alignment suggestions. Use it as a starting point, then layer in the nuance that only youcan bring.

Prompt Example:
“Create a 3-level rubric (Developing, Proficient, Advanced) for a multimedia assignment on [topic]. Each row should evaluate criteria such as content accuracy, creativity, technical quality, and learner engagement. Align this rubric with Universal Design for Learning (UDL) and check for inclusive language.”

♦️ Design Tip: Ask AI to check your rubric language for potential bias or vague phrasing because clarity and inclusivity are not just nice-to-haves, they are essential for fair evaluation.

Case Study: From Content Chaos to Cohesion

The Challenge

A university instructional design team is knee-deep in over 20 simultaneous online course builds. Each course had its own instructor, tone, pacing, and (let’s be honest) wildly different definitions of “done.” One week they were reworking a course written like a TED Talk, and the next they were deciphering PowerPoint slides that looked like they were exported from 2003.

Consistency is elusive, deadlines are looming, and you’re getting non-stop slack messages asking, “Is this the final version?”

The Solution

The team uses ChatGPT to streamline their design workflows and create a scalable, repeatable system that cuts down on chaos and levels up quality. With ChatGPT, they are able to:

• Draft initial course outlines directly from syllabi and learning outcomes.
• Standardize tone and formatting across modules (no more mood swings between ultra-formal and emoji-filled).
• Suggest visuals and interactions that aligned with learning goals.
• Flag duplicate or outdated content hiding in reused templates.

In other words, they don’t just build courses…they built a smarter, faster process and workflows. Instructional designers get to spend less time chasing inconsistencies and more time doing what they do best: designing impactful, engaging learning experiences.

For Learning & Development Professionals

If instructional designers are the architects, L&D professionals are the urban planners of learning, connecting people to the right opportunities at the right time with the right message. You’re designing experiences that don’t just check a box, they shape culture, support growth, and (ideally) keep people from nodding off during compliance training.

With generative AI, you’re working faster and smarter. Whether you’re onboarding 500 new hires or launching a leadership accelerator, here’s how AI can become your behind-the-scenes MVP.

1. Draft and Refine Training Content

Let’s be real: some onboarding manuals were never meant to see the light of day. We’ve all inherited dusty PDFs, word-for-word transcripts, or Frankenstein docs stitched together over the years.

AI won’t turn chaos into curriculum overnight, but it can help you get there faster. With the right prompts, you can transform raw materials like outlines, transcripts, slide decks, and policy documents into clear, structured, and engaging content. Think clean flow, conversational tone, and learner-centered outcomes, all without starting from scratch.

Prompt Example:
“Convert this onboarding manual into a 5-part training series for new hires in [industry]. Include clear learning objectives, interactive elements, and a brief knowledge check for each module. Keep the tone warm and professional.”

♦️ Design Tip: Need versions for self-paced and instructor-led formats? Ask for both. AI will split the difference and save you hours.

2. Create Tailored Microlearning

Bite-sized learning doesn’t have to mean simplified content. AI can support the development of short, focused lessons that are adapted to specific roles, locations, or performance goals. This approach works well for onboarding refreshers, just-in-time learning, or delivering consistent training across distributed teams. By helping you break down longer materials and adjust tone or context for different audiences, AI makes it easier to deliver relevant, accessible learning without starting from scratch each time.

Prompt Example:
“Create a 5-minute mobile-friendly microlearning module on [topic] for frontline employees in [region]. Include a short real-world scenario, 2 key takeaways, and a quick knowledge check.”

♦️ Design Tip: Follow up with: “Now rewrite this for mid-level managers in North America, adjusting tone, examples, and learning objectives.”

3. Analyze Employee Feedback & Survey Data

You’ve got 300 open-text responses. Do you really want to read every single one? AI can summarize feedback themes, detect sentiment, and even suggest next steps so you spend less time combing through data and more time acting on it.

Prompt Example:
“Summarize the top trends from this employee engagement survey. Highlight concerns about leadership, workload, or culture. Suggest 3 action items for HR and managers.”

♦️ Design Tip: Need a slide deck for leadership? Ask AI to turn the summary into a 5-slide executive report with talking points.

4. Update Policy Training

HR policies don’t sit still, neither should your training. When guidelines shift, AI can help you rewrite materials across formats quickly and consistently, ensuring everything from LMS modules to email templates stays compliant and aligned.

Prompt Example:
“Rewrite this compliance training module to reflect the updated [policy name]. Use plain language, keep the tone respectful and clear, and ensure all required legal statements are included.”

♦️ Design Tip: Ask AI to flag any outdated terms or legacy references. It’s a great way to clean house while you’re at it.

5. Build Coaching Guides and Leadership Toolkits

Scaling your top talent doesn’t mean cloning them, it means capturing what they do best and turning it into actionable resources. AI can transform interview notes, 1:1 insights, or feedback sessions into toolkits, playbooks, and coaching guides that help every manager lead with confidence.

Prompt Example:
“Turn these manager interview notes into a leadership coaching guide for new team leads. Include 3 weekly topics, reflection questions, and conversation starters.”

♦️ Design Tip: Want to level it up? Ask AI to draft a 4-week leadership development journey based on the guide.

6. Ensure Inclusive & On-Brand Language

You’ve got the values. You’ve got the tone. Now you need every piece of content to reflect that, without manually checking every word. AI can help flag exclusionary language, rewrite for clarity, and keep things consistent with your brand and DEI principles.

Prompt Example:
“Review this training content for inclusive language and accessibility. Flag any jargon or biased phrasing and suggest improvements. Keep tone aligned with our internal voice: clear, kind, and action-oriented.”

♦️ Design Tip: Ask AI to turn your brand voice into a style guide it can follow, then let it apply those rules to everything you create.

Case Study: Personalizing Leadership Training at Scale

The Challenge

An L&D team was tasked with creating leadership training for three distinct audiences: new supervisors, mid-level managers, and senior leaders. The goal was to personalized tone, relevant examples, and tailored reflection prompts for each group.

The catch was they didn’t have the bandwidth to build three separate programs from the ground up. They needed scale without sacrificing personalization.

The Solution

Instead of developing separate tracks manually, the team used ChatGPT to:

• Build a modular leadership curriculum that served as a shared foundation
• Adapt tone and scenario examples to fit each leadership level
• Rewrite learning prompts and exercises to reflect different departmental contexts

By prompting ChatGPT with variations in role, experience, and learning goals, the team was able to create targeted content that still felt cohesive across the board.

The Result

• Higher engagement from learners who felt the training “spoke their language”
• Streamlined development with less duplicate work
• A clearer leadership pipeline built on content that scaled with intention, not duplication

The best part was that the team finally had a repeatable process to personalize learning at scale, without burning out in the process.

How to Get Started with Generative AI in L&D and ID

The idea of bringing AI into your workflow might feel like adding one more tool to an already crowded tech stack. But here’s the secret: it’s not about learning everything, it’s about starting somewhere.

Whether you’re an instructional designer juggling 10 course builds or an L&D leader supporting thousands of learners across teams, the real win comes from using AI to remove friction, not add it. Here’s how to get started with intention:

1. Pinpoint the Time-Sinks

Where’s your workweek going to die a slow, repetitive death? That’s your starting line. Maybe it’s rewriting the same policy module every quarter. Maybe it’s summarizing a dozen SME transcripts. If you find yourself copy-pasting, duplicating effort, or reinventing the wheel, you’ve found your first AI use case.

Look for:

• Repetitive drafting tasks
• Content repurposing
• Assessment writing
• Survey analysis
• Formatting and clean-up

2. Start Small, Stay Smart

Don’t try to automate your entire program overnight. Choose one piece of content (like a slide deck, a video script, or a job aid ) and test how AI can support the process. Can it give you a strong first draft, suggest a visual, or rework the tone for a different audience? That’s the magic of starting small: the wins are quick and the momentum builds fast.

Starter projects:

• Rewrite a slide intro with better flow
• Draft quiz questions from an outline
• Repurpose a long webinar into microlearning
• Create two versions of the same lesson (e.g., manager vs. entry-level)

3. Teach It Your Style

Your brand has a tone. Your content has a rhythm. Your team has values. AI can learn all of that if you show it. Upload writing samples. Share your course templates. Define accessibility rules, inclusion principles, and preferred terminology. The more context you give, the more aligned (and useful) your AI partner becomes.

What to feed it:

• Style guides
• Learning frameworks
• Rubric language
• Common learner personas
• Voice and tone samples from existing content

4. Choose the Right Platform

Not all AI is created equal. Some are chatbots. Some are productivity tools. And some are built specifically for enterprise learning use cases. Look for platforms that are secure (hello, learner data), customizable, and flexible enough to grow with your team. If you’re working across multiple teams or departments, integration and permissions matter too.

Good signs:

• SOC 2, HIPAA, or GDPR compliance
• Easy content customization
• Enterprise-ready features
• The ability to ingest your internal content or data

5. Measure the Magic

If you’re not tracking your wins, you’re leaving value on the table. The real power of AI isn’t just in what it can do , but what it did. Whether it cut your content creation time in half or helped you scale a personalized learning path in a fraction of the effort, those outcomes matter. Document them. Share them. Use them to build buy-in and guide future investments.

Keep an eye on:

• Time saved
• Revisions reduced
• Learner engagement or completion rates
• Quality or consistency improvements
• SME or stakeholder satisfaction

♦️ Pro Tip: Create a “Before vs. After AI” snapshot to show stakeholders how this isn’t just shiny tech, it’s operational gold.

Final Thoughts

The best AI tools don’t replace your work, they reveal the parts that were weighing you down and free you up to create something better. So don’t overthink the jump. Pick a task. Write a prompt. Start small. And if you mess up the first try, that’s part of the fun.

The future of learning isn’t about robots. It’s about humans working smarter, with a little help from generative AI.

Please note: you can also read this article on Medium.