Generative artificial intelligence (AI) — think tools like ChatGPT or Google Bard — has been making waves ever since ChatGPT’s rollout to the public in November last year. While AI is not new, the technology has become the focus of a media firestorm over the past few months, equal parts fearmongering and naively optimistic. The world of learning and development (L&D) doesn’t exist in a bubble, so of course we’ve been wading through the same extremes of information. At the same time, we’ve been seeing an industry-wide shift from one-size-fits-all training to more personalized offerings — a shift that AI may be uniquely equipped to help us make.

Like any technology, generative AI has its uses, as well as its limitations. Let’s explore some of the ways that AI can be used to lighten the load on L&D professionals, as well as impact the company’s bottom line by engaging and retaining top talent with more personalized learning solutions.

Generative AI: What It Is

Before we get into how it can be used, it would be helpful to define the technology: “Generative AI” simply refers to algorithms that can be used to generate content. Despite the name, generative AI chatbots aren’t intelligent. They rely on machine learning (ML) to generate convincing language (or images, audio, video, etc.) based on the vast amount of input it’s been fed with.

“AI is not a subject matter expert,” says Tom Whelan, Ph.D., director of corporate research at Training Industry. “It’s been shown to hallucinate incorrect information and parrot biases that it picks up on the internet.” AI doesn’t review sources or carefully consider the output it gives you; rather, it scours the internet and pulls together a plausible-sounding quote based on the massive amount of written language at its disposal — or other forms of content based on all the written language, images, voice clips and video that have been posted on the internet.

Challenges of AI in Learning Design

AI-generated materials should always be regarded with a healthy dose of skepticism. Anyone who’s had to fact-check ChatGPT knows that it can be wrong, and it’s often confidently wrong. Another thing to keep in mind is that, since AI’s output is based on input from millions of human beings, it’s just as capable of being biased or bigoted as a human. AI will fail to grasp the nuances of complex situations — which can become a big problem if you’re using it to generate soft skills or diversity, equity and inclusion training materials, for example.

Advantages of AI in Learning Design

That’s not to say that AI is inherently dangerous, or that it shouldn’t be used. In fact, generative AI can be used pretty much everywhere in the context of L&D, says Ken Taylor, CEO at Training Industry. “From advanced course creation tools to automating the repetitive tasks required to deploy and maintain a learning management system (LMS), AI can simplify routines, improve the quality of training and improve learner experiences,” Taylor says.

It’s important to keep in mind that you, the user, will always be an essential part of the process. Whatever AI generates for you, you’re still the final say in what gets used, deleted, regenerated, etc. With all that in mind, let’s take a closer look at some areas of training design that can benefit from the use of AI:


AI tools now allow for the creation of realistic and immersive simulations that mirror real-life scenarios. “It’s one thing to know about something,” says Gwen Baker, chief learning officer of Mursion, “it’s another to learn how to do something by direct experience.” With AI, learners can engage in hands-on practice, designed according to their unique skill levels and career path choices, which allows them to hone their skills and decision-making abilities in a safe and controlled environment. For example, cybersecurity professionals might engage in simulated cyber-attack scenarios within a controlled environment, where AI algorithms create realistic simulations to help them develop their incident response and decision-making skills without compromising real systems.

Content Creation

AI algorithms can produce outlines for a wide range of learning materials, from interactive modules to custom-tailored assessments. Learning leaders still need to carefully review everything to make sure the information is factual and that it serves the interests of the organization, but these tools can certainly lessen the lift. Without devoting as much time and resources to designing and producing presentations/learning materials, you’ll be freed up to focus on bigger-picture concerns, like your training strategy.

Adaptive Learning

AI can meet your learners where they are by continuously analyzing their progress and needs. Adaptive learning experiences ensure that training interventions and content are personalized in real-time, optimizing learning outcomes fast so that your team can stay in the flow of work.

For example, AI-based natural language processing (NLP) tools enable learners to interact with educational content using voice commands or text input. They can ask questions, seek clarification and receive instant feedback, creating a conversational and personalized learning experience.

Enhanced Data Analytics

Modern adaptive learning platforms utilize AI to give L&D leaders the ability to capture and analyze more data than was previously possible. They can dynamically adjust the difficulty level, pacing and content based on learner performance. Additionally, virtual learning assistants, in the form of AI-powered chatbots or intelligent tutoring systems, can engage learners in conversation, answer questions, provide feedback and offer personalized recommendations. This is all made possible through recent advancements in NLP and ML algorithms to better understand queries and deliver relevant information.

The Human Touch

It’s important to remember that human oversight will always be necessary. No matter how advanced a large language model becomes, it’s still just combining words and phrases in a way that it has determined is probably correct, based on all the data it’s been exposed to thus far.

“Human experts are the heart and soul of the simulated learning experience,” says Mark Atkinson, co-founder and CEO of Mursion. Models like ChatGPT have been known to confidently state things that are patently false. In other words, if there’s not a human person there to double-check every piece of information that comes out of an AI model, you will run the risk of exposing your learners to misinformation.

This is why generative AI is best used as an ideation tool, something to quickly produce a rough draft.

The Future of Personalization

As the L&D landscape continues to evolve, generative AI can offer an exciting avenue to personalize training and optimize learning outcomes. With careful consideration of its limitations and the importance of human oversight, AI can become a valuable tool in the arsenal of L&D leaders, supporting their efforts to engage learners, enhance training content and drive organizational success.


Want to learn more about AI and its uses in L&D? Check out this Training Industry webinar for more information.