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10 Immediate Uses for AI in Learning and Development
ATD Blog

10 Immediate Uses for AI in Learning and Development

Thursday, September 9, 2021
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L&D professionals are watching with excitement and apprehension as artificial intelligence (AI) reaches new levels of sophistication. Meanwhile, marketers have been experimenting with AI for creative work for quite some time. In my 2017 talk What L&D Can Learn from Marketing’s Use of AI, I shared how Saatchi and Saatchi used AI to generate a new creative ad. However, the arrival of ChatGPT-3 and 4 has the L&D industry accelerating efforts to adopt the generative AI underpinning it.

L&D Use Cases for AIAs an L&D industry, we can learn from what marketers are doing with AI. Automating time-consuming tasks can free up more time to create engaging and effective training materials. Additionally, AI can help us create new experiences for our learners. I’ve put together ten use cases to consider, many of which can be tried and tested for free with various AI chatbots relying on natural language processing tools:

1. Quickly produce many ideas.Program creators can use generative AI to quickly develop ideas for training programs or content for e-learning. For example, ask ChatGPT for suggestions on training topics based on the pre-identified needs of a particular department or role.

2. Support data analysis.AI can provide significant support by assisting in tasks such as data analysis, evaluating feedback from learners to gain insight into the effectiveness of training materials, and identifying areas that require improvement. Furthermore, AI can generate reports based on this feedback, providing valuable awareness to shape future training initiatives.

3. Assimilate content from meetings.Compiling meeting transcripts from subject matter experts (SMEs) and extracting relevant notes can be time-consuming and labor-intensive. A myriad of new AI tools can analyze audio, transcriptions, and video recordings to ascertain the most important parts, making it easier to identify key takeaways and improve overall training and development initiatives.

4. Synthesize and summarize.AI chatbots can digest information from subject matter experts, textbooks, or manuals. Instead of reading pages, use AI-powered text summarization tools to extract the most relevant information quickly and efficiently. Note: If you’re using a public tool, make sure the data you have it analyze is non-confidential and non-proprietary.

5. Improve storytelling.Leverage the power of AI to enhance storytelling and create more engaging training experiences. For example, by feeding the AI chatbot relevant phrases, you can obtain a range of objection-handling situations to develop and adapt to suit your specific training needs. This allows you to visualize and experiment with various concepts more swiftly to see which works best. And you can easily refine different components, like changing the background or characters to be more appropriate to the learning objectives, without restarting the creation process from the beginning. This has application when creating scenario-based quiz questions, story arcs, and other creative content.

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6. Create role-play scenarios.Let AI generate plausible yet generic responses to role-play scenarios using machine learning algorithms. This would be particularly useful for developing scenarios requiring employees to handle difficult or sensitive situations, such as customer complaints or navigating workplace conflicts. For instance, you could use ChatGPT to generate different client responses based on your customer personas.

7. Generate quiz questions at varying levels of difficulty.AI can generate a unique and relevant set of questions for a specific training topic through machine learning algorithms. And it can be programmed to adjust the difficulty level of the questions based on the learner’s progress and performance with tools such as Obrizum or Area9 Lyceum. AI may already be integrated into the training creation process with some tools. For instance, Obrizum employs advanced AI to define content related to each piece of information when auto-creating training materials.

At a more basic level, instructional designers can use AI chatbots to generate quiz questions using clear prompts based on non-confidential, non-proprietary content. Just be sure to verify the accuracy of the answers by checking them with credible sources (which you can also ask your AI tool to do for you).

For example, we used ChatGPT to generate two quizzes based on this article using the prompt “Create one multiple choice quiz question and one open-ended higher level thinking quiz question. Indicate which answer is correct and identify where in the article the question came from.” We could also prompt it to rewrite the quiz questions to be more difficult.

8. Create rapid training videos.AI video creation tools can create training videos in just a few minutes. Instead of relying on the traditional workflow of scriptwriting, finding a filming location, filming an actor, and post-production editing, these tools use AI-generated avatars or text-to-animation features to bring videos to life. This process is faster and more cost-effective, eliminating the need for expensive equipment and software. The resulting videos are engaging and visually appealing, making it easier for learners to retain information.

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Advertisement9. Generate unique images.AI-generated images suitable for L&D allow for unique visual content for courses. These AI tools, such as Midjourney or DALL-E, can quickly create images customized to specific learning objectives. But don’t forget to adhere to company policies on attribution and follow branding guidelines to maintain consistency in visual representation. Thoughtfully used, AI-generated images can make courses more visually appealing and engaging for learners.

10. Practice conversations.Finally, there are direct benefits to learners interfacing with AI coaches. For example, ChatGPT can be a valuable tool for language training due to its advanced natural language processing capabilities. It can engage learners in conversation, assess their grammar and vocabulary, and provide real-time feedback. The model can simulate scenarios—ranging from basic conversation to more complex business interactions—allowing learners to practice their language skills in a safe and controlled environment.

For example, an AI chatbot could be used to refine a learner’s French spelling, sentence structure, and basic conversation skills, providing tailored and specific feedback on precise issues. Because many AI tools adapt to the learner’s proficiency level, it’s possible to customize the learning experience to individual needs to promote confidence before communicating in real-world situations.

Effective Application of AI to L&DA few aspects particular to L&D to remember when adding an AI chatbot to your toolbox.·


  • Manage the data sources. Savvy marketers are cautious about using AI for customer-facing work; L&D professionals should be, too. It’s essential to closely vet the data sources that train generative AI models and monitor the accuracy of their output. Stay in touch with news about the rapidly evolving technology to identify any legal or ethical issues before they arise. And remember, a public AI chatbot is not secure and should not be used for typical corporate training. Stick to general topics in nature and not connected to an organization’s people, processes, systems, and proprietary data.
  • Create a defined space for taking the AI gamble. According to a recent article, many marketing firms are setting aside a portion of their budgets for AI test and learn initiatives. For instance, Mint Mobile dedicates 10 percent of its marketing budget to experimentation with early-stage technologies like generative AI. Other companies have created a center of excellence or an AI steering committee to explore what’s possible with automation and generative AI while considering legal and ethical implications. By setting aside money and fostering a risk-embracing culture, these organizations can test new technologies and approaches that can potentially improve their business outcomes.

Typically, L&D has an approximate eight-year lag behind the marketing industry. This gap can be seen in adopting tools from blended learning and multi-channel approaches to augmented and virtual reality (AR/VR) to data-fueled profiling. Let’s commit to adapt more quickly given the pace of change within AI itself. As an industry, we cannot afford to lag.
While AI can be incredibly helpful, it doesn’t replace the unique perspectives and skills that humans bring. AI is a tool to augment our work rather than replace it. As an industry, now is our moment to explore and embrace this technology to harness its power allowing us to benefit more learners.

While marketers are leading the charge in using generative AI, L&D professionals can monitor how marketing uses the technology and subsequently adopt an effective AI for them. By experimenting with the ten use cases above, we can create better learning solutions, streamline processes, and ultimately enhance the learning experience.

About the Author

Danielle Wallace is the chief learning strategist at Beyond the Sky, a provider of custom learning solutions. She combines proven marketing techniques with adult learning principles to create learning that sticks. Previously, as a marketing executive with Procter & Gamble and PepsiCo, she learned strategic marketing and advertising principles, which she applies to learning and development to create compelling breakthrough solutions. Danielle is also a certified training and development professional (CTDP).

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Love the scorecard! Thanks for the templates.
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