The 7 Artificial Intelligence Use Cases for  Learning & Development

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Hi, and welcome to the Training Impact podcast.

 

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I’m your host, Jeff Walter, founder and CEO of Latitude Learning.

 

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And today I want to talk to you about artificial intelligence and its impact on the learning and development industry.

 

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Artificial intelligence is the

 

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Next major technological revolution that’s occurring, we’ve had a number of technological revolutions since the beginning of the Industrial Revolution, for steam power and then gas power, electrical power, media, mainframe computers, personal computers.

 

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One most of us remember is the internet back in the late 90s into the mid 2000s, a big thing there.

 

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And now we’ve got artificial intelligence and artificial intelligence, like all those other

 

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technological revolutions will eventually change everything.

 

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So the opponents are 100% correct.

 

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It will change everything.

 

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It will change all aspects of life, much the way the internet did, much the way electricity did, gas-powered cars, steam-powered locomotives.

 

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But I want to take a little grain of salt here.

 

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In every one of these technological revolutions, they follow a certain pattern.

 

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And the first pattern is the new technology is going to solve everything in the world and to be better.

 

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And you hear that now.

 

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It says, should we fear AI?

 

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It’s going to take over the world.

 

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It changes everything.

 

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And if past is prolonged to the future, what we know is that people are going to overpromise on what AI can do.

 

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And there’ll be some

 

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very, very public disasters or disappointments.

 

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But in the end, it will change everything.

 

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And you can just look back at the internet.

 

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Back in the late 90s, when the dot com boom was going on, people were wondering, will people use their credit cards online?

 

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lot of things that we were thinking about, nobody, nobody thought about social media.

 

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It wasn’t even a glimmer in the eye.

 

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And so here we are 20, 30 years later and things like credit card transactions and buying things online, all these things we just take as commonplace and part of the infrastructure.

 

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But then there’s social media and it creates some new challenges for us.

 

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So nobody would have anticipated that.

 

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So we’re kind of in the same phase.

 

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with AI, where there’s some really good use cases out there, especially for learning and development, that can help us be more productive and more effective at what we do.

 

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And we’re going to have to basically let AI play out over the next 10 years to see what the ultimate impact is.

 

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But what I want to talk about is the seven use cases that we can apply today to learning and development so that we can do our jobs better.

 

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And so the first thing I wanted to talk about was chat support.

 

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So we’re all familiar with chat support, and as consumers now, we’re starting to see where AI is coming into chat support.

 

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And a lot of it is chatbots that are doing the actual chat support.

 

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In learning development, that has the potential to create the ultimate job aid for our learners and employees.

 

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And the thing to remember about the chatbot, or the way you set up a chatbot, I should say,

 

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is you have to create a body of knowledge and then you take the chatbot technology and you have it learn on that body of knowledge.

 

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So it’s really important to remember that body of knowledge because you don’t want the chatbot just kind of going out to the general internet to find information.

 

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You want to control what type of information you have curated and you want to put that into a body of knowledge and then train the chatbot on that.

 

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body of knowledge.

 

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So now that chatbots, again, as consumers, we’re seeing it all over the place now.

 

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From a learning and development standpoint, we want to take our learning environments and start to include chatbot support for the jobs that are going on, the way we provide additional resources or currently provide job aids for our learners.

 

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So for example, Latitude, with our Latitude Learning LMS,

 

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We have a body of knowledge that’s all our support documentation, and administrators can now get onto a chatbot for support on how to use the LMS.

 

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We’re in the process of taking that and extending it to our clients so they can create chatbots to support their learner population.

 

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And what they would do is they would identify the resources and the courses that they want to be part of the body of knowledge, and then that’s

 

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where the information in the chatbot would.

 

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And you take that and you combine it with the large language models, which is what allows AI to interact with people in a natural language.

 

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That can become a really powerful job aid, like I said.

 

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So, you know, and as I said, you know, from an LMS standpoint, from a house provider or learning environment,

 

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provider, great, great fit.

 

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And we’re working on bringing that to our clients in the near future.

 

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So that’s the first use case, is chatbot support.

 

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The second is in content creation.

 

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Now, we as training industry folks, we’re in the business of creating training content, courseware, resources, et cetera.

 

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Now, a lot of training content

 

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that you see in employee training can be relatively horizontal.

 

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Things like how to do good customer service, how to be a good manager, how to diffuse a difficult situation with an employee.

 

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There are great vendors out there like BizLibrary that have…

 

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libraries of thousands of courses that are really horizontal, whether it’s the type of things that we’re talking about or how to use Microsoft Word, how to use these different tools, really great stuff out there.

 

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The second use case of content creation is you’re starting to see all the authoring tools include AI capabilities into the authoring tools to make the authoring of courseware and the authoring of resources

 

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much more productive, like a 5 to 10x increase in productivity.

 

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Now, where that’s really going to play out really well and really important is especially folks with training programs where the information that they have to be trained on is very idiosyncratic to the company.

 

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So you take things like customer service is very idiosyncratic to a particular company.

 

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Or if you have an extended enterprise training program where you’re training resellers, you’re training suppliers, you’re training your customers, that’s usually all centered around your product.

 

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And that information is very idiosyncratic.

 

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You’re not going to go be able to find courseware about that in the large publishers.

 

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So you have to create your own courseware.

 

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And that’s where the second use case of creating courses and creating resources and other content, all the authoring tools are starting to embed AI capabilities into them.

 

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And even if you’re not using that, you can go to ChatGPT and open it and some of the other tools, and you can just say, here’s a bunch of information.

 

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Here’s a body of knowledge.

 

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Write me a thousand word article on X.

 

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And so we’re just seeing huge, huge productivity improvements in content creation.

 

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Now, the good thing about that is you, as the author, still have complete control over everything that’s going on.

 

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With chat support, you control the body of knowledge, but you don’t really control the answers that the chatbot comes up with.

 

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When it comes to using AI for course generation and resource generation,

 

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you still see the finished product.

 

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You still are editing the finished product and have complete control over what the finished product is.

 

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So it’s really, you can look at it as a tremendous productivity tool and AI is just, you know, fabulous there.

 

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So, and we’re seeing a lot of different things, not only from writing, not only from generating written word,

 

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but also using tools like Synthesia to create AI generated videos.

 

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You’re seeing artwork and pictures.

 

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So some really great things coming down the line there.

 

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And I would suggest that if you’re in the bit, if you’re creating content, that you start using those tools.

 

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And if there’s courseware that you thought was too expensive to produce,

 

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because it was too niche of a need, these tools will really start to increase productivity and open up that opportunity to create courseware for those more niche opportunities.

 

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All right.

 

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The third use case is an assessment creation.

 

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And now this is going to become really important when you’re trying to do a knowledge acquisition type training program.

 

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Creating good assessments is actually really, really difficult and people do struggle with it.

 

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And as a result, we as an industry, we tend to be really good on the content creation, creating the courseware that kind of explains everything.

 

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But then we kind of take a more pejorative approach to assessing a learner’s knowledge.

 

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You know, we’ll put a little 10 question quiz at the end of a course or something like that.

 

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And it’s really just checking to make sure they learn something, but we’re not really doing in-depth assessment of their knowledge.

 

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And that’s because doing an in-depth assessment is well, pretty difficult.

 

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It takes a lot of time and energy.

 

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And unless you’ve got really a high stakes training program going on, like, you know, that’s for surgery, you know, it’s a lot of effort and a lot of energy.

 

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So here’s another place where we’re seeing generative AI being able to

 

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create assessments with really good distractors and thoroughly test for the knowledge that’s in a certain body of information.

 

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And so we’re starting to see that.

 

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And again, as a LMS provider with an assessment engine built into our tool, it’s one of the things that we’re researching now.

 

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is how can we point an AI at a body of knowledge, at some courseware, let’s say, and then generate, automatically generate an assessment.

 

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Now, good news here is you can generate that assessment just like other generative AI.

 

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The AI doesn’t have the final word.

 

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You, as the assessment author, you’re really using it as a productivity improvement tool

 

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And so you don’t have to worry about odd assessments going out there to ask various questions, because again, you’re in control of the final product, as it were.

 

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But I think as that technology gets better, we’re going to start to see programs start to flip.

 

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And instead of training and then assessing knowledge, they’ll flip it around and do the assessment first and kind of

 

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understand what knowledges the learner already has, and then just do the training on the knowledges that they are coming up short on.

 

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And I think that’ll get us some productivity improvements, not just in the creation of all this content, but also in the training program itself, where learners won’t have to sit through an entire course just to learn the 25% of the course that they didn’t know.

 

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So, but

 

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You know, that’s a little further away.

 

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You’re starting to see that come out in some of the assessment tools that are out there.

 

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It’s a little bit more of a difficult use of AI, but you are starting to see it.

 

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And we are looking at embedding it into our product for our assessment engine.

 

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So that has, again, placed some great promise.

 

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The fourth use case

 

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is, and this is very exciting to me, is in role-playing.

 

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And so one of the things we do really, really well as an industry is we’re really good at creating programs that are all about knowledge acquisition, and we struggle as an industry to create programs that help students do skill development.

 

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And the main reason is, and the way I define it too, is if you think of your thriving test, passing the written test, that’s all about knowledge acquisition, where you have to know what the red light means, you have to know what the signs on the side of the road mean, and you have to study that, and then you get assessed to see if you know what all that means.

 

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And then you take the road test, and the road test is

 

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all about skill.

 

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You have to actually have the skill to parallel park, to pull into traffic, to merge onto a highway.

 

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These are all skills, not just knowledge.

 

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And again, as an industry, we’ve done a really good job on the knowledge acquisition side, you know, using technologies, using e-learning and using assessments to make sure that, you know, to convey a body of knowledge into somebody and assess that they have that body of knowledge.

 

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We’ve struggled as an industry on skill development, primarily because skill development has traditionally been very manually intensive.

 

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Because really, in order to do skill development, you need practice and you need coaching.

 

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And that’s very human intensive.

 

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And so that’s been a difficult thing to scale, and a lot of skill development has really happened on the job.

 

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as people talk to their colleagues and their boss, and they develop those skills that way.

 

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So here, coming out with role-playing.

 

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So what role-playing is is you get an avatar in a particular situation, and you interact with the AI avatar to try and reach some type of end.

 

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So it could be helping you develop your interview skills, and the avatar is the candidate.

 

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It could be helping you develop your sales skills and the avatar is a prospective customer.

 

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It could be helping you develop your supervisory skills and the avatar is an employee that’s having some difficulty with something.

 

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And it’s really interesting.

 

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I’ve seen a number of these simulations and some of these avatars, you can get into a really in-depth conversation with them and it really is

 

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excellent and has excellent potential to help develop soft skills.

 

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And the technology is there, but it’s getting honed quickly and it’ll become more commonplace as we go on.

 

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And it will really allow us to create programs that allow for

 

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soft skill development, where you’re interacting with this avatar.

 

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Because not only, you know, when I talk to a number of the companies that are developing this technology, it’s not just that you’re, it’s not just that you’re interacting with this avatar, but at the same time, the, you know, the avatar has

 

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some type of rubric that it’s grading you on.

 

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It’s trying to see, did you approach me this way?

 

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Did you try this?

 

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Did you try that?

 

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And the avatar can be dialed into a specific type of interaction.

 

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So if we take sales, for example, you can have an avatar that’s just interested in information, and they’re not going to sell anything, or they’re not going to buy anything.

 

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you can have another avatar that’s ready to buy, but maybe has some objections that have to be overcome.

 

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And so each of those different avatars would have a rubric that would be unknown to the…

 

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learner that the learner can get graded on and coached on as they interact with the avatar.

 

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So, you know, you’ve got the opportunity to practice your skill and then you also have that coaching feedback through the rubrics that are coming in.

 

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So it’s very, very exciting and we’re really looking forward to seeing that develop as a technology because I think it can really help us as an industry develop soft skills within our learner population.

 

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The fifth use case is similar to role-playing, but it takes it to the next level, and that’s simulation.

 

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And to me, the difference is simulation is something like airline simulation or flight simulator.

 

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And the thing about simulation is the technology exists today to do simulation, but creating a simulation is just really, really, really expensive.

 

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And that’s why you only see simulations in high volume, high stakes environments like flight simulators.

 

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And you don’t see it down at lower volume and lower stakes type of situations like repairing a truck, because it’s just very, very expensive to create this simulation.

 

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So just like the generative AI

 

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was is a game changer on content creation where it reduces the cost of creating content by an order of magnitude.

 

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I’ve talked to a number of simulation companies that are bringing AI into their tools.

 

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And it’s so exciting because again, it has the potential to drop the cost of creating a simulation by an order of magnitude or tenfold.

 

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And when you do that, it opens up now simulation becomes economically viable for a whole new world of applications and environments like truck repair or surgery.

 

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And it’s very, very exciting.

 

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So, you know, it’s a little further down the line.

 

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These other things have been more immediate, but it’s very, very exciting.

 

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It’s coming and that’s going to allow us not, you know, the role plan will allow us

 

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to create training programs to develop soft skills.

 

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The simulation will allow us to create training programs that cost effectively develop hard skills, technical skills.

 

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And so that’s, again, something that we as an industry, it’s been very difficult because it’s been very expensive to do that.

 

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And we’re seeing that expense going way, way, way down.

 

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So very exciting there, very exciting there.

 

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Moving on to the sixth use case is analytics.

 

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Now, you know,

 

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One of the big challenges we’ve always had as an industry is demonstrating that the training has an impact on the business.

 

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And if you really wanna prove that, you gotta use Bayesian analysis and really nobody has had to do that.

 

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You know, it’s a very niche thing.

 

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Even research scientists don’t use Bayesian analysis.

 

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They use multivariant analysis, which is another tool

 

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you could use to try and prove that A causes B.

 

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This training causes improvement in performance.

 

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And even when you’re doing multivariate regression analysis, you have to pick which variants you’re going to do.

 

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And again, it will require a significant amount of

 

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statistical knowledge and then you can only, you know, you’re limited to just how many multi regressions you can do.

 

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And so when we look at AI and using analytical AI, a lot of those limitations go away and we’re starting to see some tools.

 

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I’ll be able to do this, but at least from my standpoint, it’s still ways out.

 

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But getting tools where you can really

 

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bring all that in, have it do not just a couple of, a dozen or so multivariant analyses, but do thousands of multivariant analyses, take everything and just put it into a big analytical AI tool and have it tell you, oh, these courses have an impact on these performance metrics.

 

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So, you know, analytical AI coming down the pipe, very exciting.

 

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It’s going to, I think, finally help us as an industry be

 

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be able to demonstrate return on investment and as we’ll get all that information.

 

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And like I said, doing the stats in the past, it’s just hard.

 

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And it’s a skill set that not a lot of folks have, that detailed statistical analysis.

 

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Usually, top research scientists do that.

 

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And it’s just not a commonplace skill set.

 

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So we’ll see that baked into the AI and we’ll be able to basically say, hey, look, we’ve done this, this training regimen causes

 

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This type of improvement in sales, or this type of improvement in customer satisfaction, and so it’s gonna be really exciting, really, really exciting, and then kind of a variant of that, taking the analytics and breaking it right down to the individual.

 

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is our seventh use case, and that’s individualized learning plans, where the AI, the analytical AI would look at everything it knows about the learner, from their demographic information, their compensation, reviews that have occurred, any type of assessments that have occurred, any type of performance information that you can get on the individual learner, and you take all that down

 

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And then based on the type of job that they have and where they want to go with their career, the AI would generate an individualized learning plan.

 

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And I’ve seen a couple of Fortune 500 companies start to do this.

 

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I think it’s still in its infancy, and it takes that analytical AI really down to the individual level and say, okay, you, Jeff Walter, this is the training you need to take.

 

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And so that’s pretty

 

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exciting there.

 

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And so that’d be the seventh.

 

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And so those are it in a nutshell, at least our first pass of the seven use cases, the seven AI use cases that are applicable to learning and development.

 

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Kind of tried to do in order of the things that are available now versus the things that are coming down the pipe.

 

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I would say, I’ve had a number of clients ask me this,

 

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This, like every other technological revolution, it will eventually change everything.

 

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But it’s okay to walk before you run and to test these things out and not jump on the bandwagon immediately, especially depending on the type of training program you have and if it’s high stakes.

 

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You know, we are still in that early stage where we’re all trying to figure out what this stuff does and where it can be applicable.

 

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And so, you know, the higher the stake training program you have, the more conservative I would be to just, yeah, as you introduce AI, especially when the AI, the final product of the AI is not under the control of a human.

 

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So like when you’re talking about content creation or assessment creation,

 

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and to some degree, the analytics, you can have a person interpret the outcome before it actually goes out into the learning community.

 

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the chat support and the role-playing, the AI is interacting directly and you don’t really control that.

 

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But with those, with the role-playing, with simulations, with the chat support, remember you need that body of knowledge.

 

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You have to curate that body of knowledge and make sure that the AI is just focused on that, not getting information from across the internet because that information may not be valid.

 

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So that’s in a quick nutshell.

 

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You know, those are the seven AI use cases for learning and development.

 

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Thought I’d get that out there because it’s a big topic right now.

 

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Everybody’s talking about it and going through your, you know, some guidelines of how to approach that as you’re looking at bringing AI into your training program.

 

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So thanks again for listening.

 

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Appreciate your time and look forward to talk to you again soon.

 

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Have a great day.