Top AI Tools Every Instructional Designer Should Know

If you’re an instructional designer (ID) who wants to get started with AI, but you’re not sure which of the thousands of tools are right for you, you’ve come to the right place!

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Below, we’ll explore a selection of AI tools that can be especially helpful for instructional designers, whether you’re researching topics, developing content, or analyzing xAPI data. While the landscape is continually evolving, these tools have shown strong potential to support and streamline the work of L&D professionals. We’ve taken the time to explore and test them, with a focus on practical use cases  that can make your day-to-day work a little easier.

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Getting started with quick wins and scalable AI solutions

One of the things every instructional designer wants to know is which AI tools they should be using. With thousands of AI tools already on the market, and more launching every week, keeping up is a near impossibility. 

However, there are many tools that are beginning to emerge as leaders within the instructional designers field and can be utilized for your own course creation. Everyone needs to start somewhere, and having conducted our own tests, these are some of the top tools we’ve identified for IDs looking to start their AI journeys:

• For AI-powered video creation at scale, try: Synthesia, Vyond, or Pictory
  These tools empower IDs to create polished, professional video content with no video creation or editing skills. From AI avatars of your real SMEs to AI-generated subtitles, and even full video translations for voices and closed captions, these tools give you the power to generate videos from a simple prompt, with easy editing to ensure they meet your standards.
  
  
• For multimedia course components, try: Midjourney, Designs.AI, or Canva
  You don’t need to be a graphic designer or learning designer to create images and courses that meet your exact specifications in minutes. From a simple prompt and your brand guidelines, you can generate an entire suite of on-brand, versatile graphics, ready to use and reuse across your learning program.
  
  
• For analyzing xAPI data, try: XCL Data Explorer or xAPI Reporting Assistant (based on ChatGPT)
  AI means it’s never been easier to analyze activities logged using xAPI. Load the export of your xAPI data in and begin to summarize learning activity, identify patterns, extract quiz responses, filter data, and generate reports on your learning programs.
  
  
• For generating learning objectives, try: Learnt.ai, Semantic Pen, or Objectives Generator
  Generate learning objectives based on your topic, target audience, skills to be acquired, and assessment methods to ensure your learners are working toward the best possible goals.
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Also bear in mind that any AI tools you choose should work well with the rest of your tech stack for the best results. The AI landscape is evolving so quickly that right now, it’s smart to choose the combination of web-based tools that best suits you rather than locking yourself into a specific integration. The dominiknow | ONE Learning Content Management System (LCMS) is the perfect partner for your AI tools, making it easy to create and reuse content with smart authoring, turbocharged with AI-powered research, content, and multimedia assets.

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Top tip: When evaluating AI tools, be sure to check for data privacy, prompt governance, and IT alignment to ensure that each tool fits into your technology ecosystem. In particular, confirm that the tool adheres to your organization’s usage policy, which may prohibit you from using solutions outside your firewall.

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Fast idea generation or content editing

Top AI tools for brainstorming ideas, generating content, or editing content include:

• ChatGPT – The most popular free generative AI tool worldwide, ChatGPT is great for rapid content generation, brainstorming, rewriting, and simulating SME dialogue, making it a versatile companion for the majority of IDs.
  
  Why choose ChatGPT: A great all-rounder for IDs needing a flexible assistant for writing, ideation, and inspiration. ChatGPT also supports a range of custom GPTs made by third parties to carry out more specialist tasks (such as the xAPI GPTs mentioned above), allowing IDs to get more out of ChatGPT beyond simple content creation.
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• Claude – Claude excels at more “thoughtful” tasks, such as handling large course documents, policies, or training manuals, making it a go-to for IDs working on in-depth or regulated content. Claude’s Constitution means it’s trained based on ethical principles, and will be more cautious around clarifying the context and avoiding overconfidence or certainty – especially where difficult, emotional topics are concerned.
  
  Why choose Claude: Useful for long-form reasoning and nuanced dialogue – for instance, unpicking complex topics or constructing balanced arguments. Claude is also a good choice for emotional, ethically centered topics, owing to the way the model is trained, and visibility into its “thought processes.”
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• Gemini – If your organization uses the Google Workspace app suite, Gemini offers  seamless suggestions directly within tools like Slides, Sheets, and Docs, including summarization, reformatting, and switching up the tone.
  
  Why choose Gemini: Convenient for Google-based businesses using Docs/Slides/Sheets to enhance workspace productivity. While Gemini can also be a useful standalone AI assistant for research, coding, and problem solving, it’s at its best when used as part of the Google Workspace suite. When used within Workspace, Gemini operates under Google’s strict privacy and security policies, keeping data secure and contained within your existing tech stack.
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• Microsoft Copilot – Built into tools like Microsoft Word and PowerPoint, Copilot helps IDs generate outlines, reword learning content, and build presentations directly inside their existing workflow with no need to switch platforms.
  
  Why choose Microsoft Copilot: Ideal for Microsoft-based businesses looking for embedded AI support for tasks like content analysis, generation, and streamlining processes. Copilot excels in automating workflows within the Microsoft suite, but for more creative, thoughtful work, consider ChatGPT or Claude, which are much stronger at content creation and refinement.
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• Groq – Designed for speed and cost-efficiency, Groq is ideal for powering real-time experiences on both the ID side of content design and on the learner side (such as powering AI chatbots within the learning platform). It’s up to 20x faster than tools like ChatGPT and Claude, so ideal if you’re short on time – especially for tasks like analyzing or generating long texts, or requesting lots of ideas at once. For example, if you ask both Groq and ChatGPT to generate 50 quiz questions for a course, Groq will give you the answers almost instantly, while ChatGPT may take 10 seconds to generate the full list. For individual tasks, it may not feel like a big difference, but it all adds up over time.
  
  Why choose Groq: Ultra-fast AI tool which generates responses in fractions of a second for speedy back-and-forth conversations and data extraction. It’s best for low-stakes, high-volume tasks, like writing course descriptions, rephrasing questions, or suggesting tags for content assets.

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Research or content summarization 

If you need to research a new topic or dig a little deeper into your focus area, many IDs are switching out traditional search engines, like Google, for AI search tools, including:

• Perplexity – Perplexity cites its sources in real time, making it perfect for IDs who need to quickly fact-check, explore topics, or gather references while ensuring academic or professional credibility. Of course don’t forget to verify those citations, as the AI interpretation may not have been completely accurate!
  
  Why choose Perplexity: Conversational, ChatGPT-style AI search engine which is ideal for IDs needing quick, verifiable insights or topic overviews.
  
  How it works: Ask a question in natural language (via text or voice) and get a concise, AI-generated response with clickable citations from real-time sources. There is also a Pro mode with 3x more sources and more detailed answers.
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• Scite – Scite is a more academic research tool, making it a useful AI companion for IDs working in scientific industries (such as healthcare or pharmaceuticals), so it’s particularly valuable when you’re focused on creating credible, evidence-based learning content.
  
  Why choose Scite: Best for creating fully referenced, scientifically rigorous L&D content with deep citation analysis.
  
  How it works: You search for a topic, and Scite returns research papers with context on how they’ve been cited (supported, disputed, or mentioned), with summaries of complex studies and a focus on trustworthiness and research quality, not just relevance to the search terms.

• Exa – Exa is built for business-grade research, allowing time-poor IDs to cut through the noise and filter out the bland, SEO-driven content to surface only high-quality results. This includes tasks like summarizing recent industry news, finding verified, trusted sources and in-depth research into learning topics.
  
  Why choose Exa: Useful for content creators and IDs sourcing diverse, real-world material with vetted sources. Also a useful time-saver if you don’t want to waste time wading through low-quality resources, as it’s easy to apply filters to your searches to hone in on exactly what you need.
  
  How it works: Search in plain English across the whole internet or specific content types, such as company websites, news sites, or blogs. It uses its own Exa Index to curate a high-quality repository of sources, and it surfaces content based on meaning, not just keywords (so you’re more likely to get relevant results).

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How to make the most of these tools

1. Start with learning objectives: Prompt AI with clear objectives and audience context to keep outputs focused and relevant.

2. Use AI for structure, not just content: Save valuable time by asking AI tools for outlines, learning flows, or assessment logic before writing copy.
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3. Iterate, don’t accept the first draft: At each stage, ask for rewrites in different formats, tones, or for different audiences to refine the design. Breaking up the steps along your ADDIE process and utilizing the revised results at each stage will bring superior results than starting with the end product first. Ironically it’s similar to the same process and steps you currently utilize.

4. Test across tools: Different tools will give different outputs, with one being better suited to your use case. Experiment to see how the tools compare for your specific needs, or try feeding the output from one tool into another to combine the power of two tools.

5. Add your expertise last: Generative AI tools are great for getting a head start, so finish up by weaving in your nuance, tone, and alignment with your real learners. For instance, you can get the AI tool to generate the bulk of a course or script, then apply your own knowledge of your audience to tweak the language to resonate with your business-specific terminology and add examples relevant to your specific circumstances. That’s where the efficiency of AI really gives the skills of the ID space to shine. 
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6. Streamline your workflows: Tools like Copilot and Gemini help automate repetitive tasks, making your instructional design workflow faster and more efficient. For example, Copilot in Microsoft Word can turn a rough topic outline into a structured draft with suggested headings and learning objectives. You can also use AI to generate course templates, summarise learner feedback, or repurpose existing content into new formats, saving hours of manual work.

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How to write an effective AI prompt

Even the most powerful AI won’t deliver useful results without clear, thoughtful prompts. That’s why instructional designers need to sharpen their prompting skills. With the right approach, AI can become a game-changer for efficiency and creativity. 

An effective AI prompt should be:

1. Clear – easy to understand, unambiguous, and avoiding vague language.
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2. Specific – detailed and contextual enough to guide the AI tool in the right direction, including tone, format, audience, purpose etc.
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3. Purposeful – know what you want to get out of the AI tool, whether that’s ideas, information, a solution to a problem or a polished, production-ready resource.

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Example of a good AI prompt:

I am an instructional designer for ABC Corp, a large Canadian electronics retailer. I’m creating a new course to help our store assistants learn about our new product line, the Hex 4D television. These employees are mostly Gen Zs, and do most of their learning on mobile devices. Please help me create a script for a two-minute introductory video that will resonate with these employees, and then suggest how I can break this down into short 10-second clips to promote the course on the LMS.

Example of a bad AI prompt: 

Write me a video script to introduce my new eLearning course about Hex 4D televisions.

You can also specify the type of sources the generative AI tool uses (or doesn’t use) to hone in on the most relevant content. To do this, simply add inclusion or exclusion criteria to your prompt, such as “Only search .gov or .edu websites”, “Prioritize peer-reviewed research papers from North America”, or “Exclude content from competitor websites”. For instance:

"Look for North American research or whitepapers on instructional design, but exclude blog posts, marketing sites, or vendor-driven content."

Revising your AI-generated content

It’s very unlikely that any AI tool will get it 100% right the first time, so knowing how to iterate on AI-generated content is a skill in itself. Always review AI-generated content through your ID lens – check for alignment with learning objectives, tone, and audience needs. For example, if AI suggests a multiple-choice quiz where it’s not suitable, prompt it to rework with scenario-based questions that reinforce application, not recall.

For more about crafting a good AI prompt, read Welbee’s top tips for AI prompt engineering.

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AI at scale: navigating policy, risk, and IT oversight

Naturally, most organizations will have questions before they dive headfirst into an AI implementation. From the IT department, to the senior leadership team, to the marketing team, everyone will want to know how introducing AI into the business will impact their work.

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For L&D, some of the common concerns center around data privacy for learners, quality of the output, and the accuracy of the content. 

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For instance, does it put the organization at risk if you feed confidential company data into an AI tool? What if the AI tool produces “hallucinations” (inaccurate or false information) which make it into the finished learning content? How can you minimize the risk of bias in your AI tools (such as only generating male names for senior roles in learning scenarios)? These are all important questions to consider to ensure the credibility and trustworthiness of your AI tools and outputs.

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IT and policy considerations for rolling out AI tools

Before you jump in at the deep end with any new AI solutions, there are a few things to consider to ensure it goes as smoothly and safely as possible:

• Work with your IT team and senior leaders to ensure everyone is clear about any organizational restrictions (such as using tools that sit outside your company’s firewall, or any infosec policies)
• Choose trusted, established AI vendors who offer onboarding and ongoing support
• Create an AI policy for your L&D team that supplements your organization’s existing IT policy. Here’s a good example of what an AI IT policy might look like
• Create an AI statement for learners so they are aware they may be engaging with AI content
• Make sure you constantly review your AI tools – the AI market is moving quickly, and more suitable solutions could become available in the coming months. It’s also important to stay on top of new AI capabilities so you can constantly revise your AI policy documentation.

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Mitigating risk with an AI pilot

As with any tech implementation, it’s best to start small. Once you’ve verified that your target tool adheres to your organization’s policies, a small-scale pilot project will help your L&D team safely experiment with the AI tools without any risks, and the output can be thoroughly reviewed by all the usual reviewers to make sure it’s up to standard. 

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‍How to set up an AI pilot program

1. ‍Set clear objectives – Define what success looks like for AI in your L&D context.
2. ‍Choose a priority use case – Start small with one practical, high-impact area.
3. ‍Engage stakeholders early – Bring in IT, HR, leadership and end users to build trust and alignment.‍
4. Select and assess AI tools – Focus on usability, data security, and fit with your existing systems.‍
5. Design and launch the pilot – Keep it simple: limited scope, short timeline, clear participants.‍
6. Support and monitor – Provide light training, track engagement and collect feedback throughout.‍
7. Evaluate and decide next steps – Use data and insights to refine, expand or pause your approach.

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Looking for somewhere specific to start? An easy and simple option is Google Chrome’s Help Me Write AI tool.

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A pilot program will allow you to see what works, what doesn’t, and what processes need to be put in place to ensure the quality of your AI outputs, whether that’s graphics, copy, translations, or something else entirely. 

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Allowing your L&D team to experiment in this safe, controlled environment will also give your stakeholders the confidence that the team knows what they’re doing – especially if you can show them samples of your AI-generated content which adhere to your existing quality standards. This will then increase the likelihood that they will give your full AI implementation the green light.

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In other words, treat this like any other technology rollout – just with some extra focus on the ethics and data protection. The new wave of AI tools that most L&D teams are using are still relatively new, so be prepared for any skepticism by highlighting the benefits of using AI from your pilot program and any initial experiments.

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‍A note on ethics: Even in an AI pilot, it’s important to inform your learners that AI is being used, and how it’s being used – for instance, if your inputs are being used to train AI models globally or restricted to use within the company). A good example is if you’re using an AI agent for coaching – ensure that all learners know they’re engaging with an AI coach, and what exactly will be done with their data.

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What’s next: becoming a more strategic ID with AI

AI is the perfect sidekick for any instructional designer looking to become more strategic. AI tools are cleverly designed to remove the time-consuming tasks associated with content creation and free up more time for creativity, strategy, and creating better learning experiences, with more headspace to experiment and find out what works.

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As a result, IDs who are using AI are currently leading the new wave of L&D innovation, whether that means crafting more innovative content, saving significant time on lengthy manual processes, or upscaling content production across the business.

Three of the most important skills for AI instructional design are:

1. AI prompt design – applying critical thinking and evaluation to identify exactly what you need from an AI tool. This includes being specific with your initial prompt, but also having the ability to work with the tool to refine the answer rather than just accepting the first response.
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2. Data literacy – with AI instructional design comes greater access to data, requiring an enhanced understanding of data to make the most of it. This includes understanding the structure of the data, the correct approach to the data, and what is really captured in a data set, alongside basic data hygiene.
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3. Workflow design – until now, most instructional design processes have been manual or semi-automated. AI instructional design empowers IDs to save a lot of time and effort on these processes, as long as you can build smart, AI-enhanced workflows. For instance, instead of requiring hours of stakeholder input and research to create personalized learning paths, AI can generate role-specific recommendations, automatically adapt tone and examples for different audiences, and translate content with minimal manual input.

As you may notice, these three skills embrace AI almost as a new “colleague.” AI isn’t the enemy, and smart IDs are rapidly switching their view of AI from “threatened” to “empowered.” 

After all, you could carry on doing everything yourself from scratch, sinking hours into your familiar manual processes – but why would you, when AI gives you the gift of more time to make your learning more impactful?

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The bottom line

If you’re ready to start exploring the wonderful world of AI instructional design, we recommend starting with one tool, one use case, and one workflow. This will allow you to safely experiment on a small scale to improve one of your current workflows and processes, before tackling the rest.

And speaking of one… dominKnow | ONE is an enterprise-ready content creation, management, and delivery system that is the perfect companion for the various AI instructional design tools on the market today. You can upload and manage your AI-generated text, images, videos, and documents, right within dominKnow | ONE and begin to leverage the content and reuse it across multiple projects and workflows or leverage single source design approaches – no matter how much content you create.

Ready to find out more about how you can build AI instructional design into your current processes? Book your dominKnow | ONE demo today to see how quick and easy it can be to manage, deliver, and update all of your AI learning content.