Artificial intelligence is reshaping how organizations approach learning and development, with industries most exposed to AI seeing 3x higher growth in revenue per employee compared to those least exposed. You’ve probably noticed AI tools popping up everywhere, from content creation platforms to personalized learning recommendations. But beyond the buzz, AI is solving real problems for L&D teams: reducing time spent on manual tasks, personalizing learning at scale, and helping close skills gaps faster than traditional methods.
This guide explores what AI means for learning and development, how it’s transforming the field, and five practical use cases you can implement today. You’ll also discover the benefits AI brings to your training programs, the challenges you might face, and how to get started with AI-powered learning solutions.
What is AI in learning and development
AI in learning and development uses artificial intelligence to automate training tasks, personalize learning experiences, and analyze learner data. This technology helps L&D teams create, deliver, and manage training programs more efficiently through machine learning algorithms and natural language processing.
In practical terms, AI enhances L&D through:
Data analysis: Identifies patterns in learner behavior and predicts outcomes
Task automation: Handles content tagging, notifications, and enrollment
Personalization: Creates learning paths based on individual needs and performance
Content generation: Produces and curates learning materials efficiently
Real-time support: Provides assistance through virtual coaches and chatbots
Think of AI as a powerful assistant that handles time-consuming work while helping you deliver more relevant, engaging learning experiences.
How AI is transforming learning and development
AI is fundamentally changing how L&D teams operate, moving from manual, one-size-fits-all approaches to automated, personalized learning at scale.
Traditional L&D programs struggle with personalization. Creating customized learning paths for hundreds or thousands of employees takes significant time and resources.
AI changes this by analyzing learner behavior, performance data, and content interactions to automatically recommend relevant courses. What once took weeks of manual work now happens in real time.
Here’s how AI is transforming key L&D functions:
Content creation: AI-powered authoring tools generate engaging, pedagogically sound content in minutes and translate it into multiple languages.
Proactive support: AI identifies struggling learners early, recommends additional resources, and sends timely reminders about deadlines.
Administrative automation: Tasks like content tagging, learner enrollment, report generation, and compliance tracking run automatically.
This shift from reactive to proactive support improves completion rates and learning outcomes. Your team can focus on strategic initiatives rather than administrative work.
5 use cases of AI in learning and development
Alright, so, there’s a lot of talk about AI. We’ve established that.
But how exactly is it being used today? How do different digital learning solutions incorporate AI features and what do they do?
To answer these questions, here are five use cases of AI in L&D programs.
Use case #1: Virtual coaches
AI-powered virtual coaches are proactive virtual assistants for users on your platform. They can guide learners through learning activities and work within the learning platform to recommend content, monitor progress, answer content-related questions, and send push notifications related to content or deadlines.
Essentially, a virtual learning coach is like a chatbot, similar to the ones used for customer support on various websites and platforms.
Virtual coaches help learners and make the learning process more streamlined. That’s because, unlike human trainers and admins, they’re available 24/7. A virtual coach can answer many basic questions about learning content thus saving time for learners and admins alike.
Docebo comes with a virtual coach that is focused on improving user experience. Your learners can request recommended content, check their progress, and even have the virtual coach ask them multiple-choice questions to test their knowledge. This is a great feature for increasing knowledge retention.
And what’s more, learners don’t have to memorize any special commands thanks to natural language processing.
Use case #2: Deep search and auto-tagging
On an AI-powered learning platform, AI analyzes both formal and informal learning assets and improves their discoverability through search. It’s like the advanced search engines you see on Google or Amazon. When someone shares a new learning asset or creates new training material, the AI synthesizes the information in the asset to produce the most relevant search results.
During this process, AI identifies key phrases and creates tags for assets automatically to make learning content easier to find. Docebo’s Auto-Tagging function identifies key phrases from uploaded learning content and assigns tags automatically, cutting down on the time-consuming task of manual tagging. This helps admins with categorizing content properly and also makes the Deep Search function easier to use for learners.
Furthermore, with Docebo’s Deep Search, if you share an interesting article in your LMS and your coworker needs to reference it a few days later, they can just search for it and find it in seconds. This prevents anyone from needing to dig through a bunch of irrelevant search results.
Use case #3: Personalized learning
Personalization in a corporate environment was once unheard of. Employees were just a drop in the ocean of an organization’s workforce and “one-size-fits-all” was everyone’s mantra.
Now, employee training is a whole new ball game with an emphasis on customization and personalized learning methods. AI can be used to address different learners and different learning styles. A personalized learning experience that adjusts the learning content to individual learners’ needs leads to better learning and engagement.
Among AI’s many functionalities, one crucial one is its ability to provide relevant content suggestions and give recommendations based on an employee’s job title, interests, and the content they’ve already consumed. These AI suggestions are a great way to increase learner autonomy too. Instead of always relying on their trainers to guide them, employees can find interesting and relevant content themselves, thus enabling self-directed learning. Such algorithms create a more personalized experience with a similar feel to Spotify or Netflix.
Use case #4: Content creation
Now, it’s all well and good that AI can enable this kind of adaptive learning but who’s going to create all that content for the algorithm to recommend?
Historically, subject matter experts and company employees have taken countless hours out of their busy schedules and existing workloads to create content for L&D programs. However, although team members may be knowledgeable on a certain subject, creating engaging content that uses the latest in learning and developmental theory is a different kind of expertise altogether. Thanks to AI, organizations can save time and money by using this technology that has been trained to create effective and engaging content based on modern learning techniques.
With Shape by Docebo, you can turn internal or external knowledge into easily digestible microlearning “pills.” You can translate them automatically too, for quick deployment in multiple languages.
Use case #5: Identifying learning gaps
The truth is everyone has knowledge gaps. That’s fine, a single person can’t be expected to know everything.
Sometimes though, these knowledge and skill gaps affect employee performance and companies have to address them.
Without any AI help, closing knowledge gaps can be a drawn-out and tiresome proposition. Identifying individual learning gaps takes time and a lot of effort. Your L&D personnel would have to manually assess the knowledge of every employee to create a learner profile that’ll reveal and fill their learning gaps.
Instead, with AI-powered metrics and data analysis, you can identify skill gaps much faster. Once the AI tool is done with its analysis, your admins and trainers can start working on new learning content to use in upskilling the workforce.
What are the benefits of using AI in L&D?
AI delivers tangible benefits that make your L&D programs more effective and efficient. Here’s what AI-powered LMS features can do for your training programs.
Close skill gaps
AI has the ability to more accurately identify employee skills gaps and suggest the best ways to close them, which is critical in a landscape where the skills sought by employers are changing 66% faster in occupations most exposed to AI. How?
Machine learning algorithms predict outcomes, allowing you to provide specific content based on a learner’s past performance and individual goals.
For example, if a group of learners is unfamiliar with a company’s sales philosophy and format, they can take a “Sales 101” course to fill this gap. While members of the sales department, who are very familiar with the sales philosophy and format, can skip ahead.
The result? All learners can learn new skills and close knowledge gaps without sacrificing engagement or slowing down other learners.
Proactively support learners
One of the major benefits of all AI-based computer features is that they don’t have to wait for you to ask them to do something. AI and automation go hand in hand, and you can use AI proactively.
Invite-to-Watch features, for example, are designed to elevate the social learning experience by making sure that those who’d benefit most from a particular piece of learning content will get their eyes on it. When a user uploads something, the platform can automatically produce a list of people in the organization who may find it interesting. AI (or machine learning in this case) does this by analyzing the content to create a list of users who’ve shown an interest in similar topics in the past.
Interpret advanced analytics
AI can collect and interpret vast amounts of data, meaning you can gather key insights faster than ever. Think of AI as a learner itself: the more data it consumes, the more intelligent it becomes. For example, algorithms can analyze both new content and historic learning patterns, including content preferences and the performance of learners on the platform.
As an AI-powered system is fed more content, it becomes better and better at identifying patterns within the content and learner performance. This gives you a data-driven way to connect learning performance to real-world business results, mirroring findings that show productivity growth has nearly quadrupled in industries most exposed to AI since 2022. Docebo’s Learn Data feature can centralize all your data in one place, letting you access all the learning KPIs and metrics in a format ready for further analysis.
What are the challenges of AI in L&D?
AI isn’t a magic solution. Like any technology, it comes with challenges you need to navigate carefully.
Here are the common obstacles you might face when implementing AI in your L&D programs:
1. Integration
A new AI-powered LMS needs to integrate neatly into your existing tech stack and the tools used in L&D activities. Usually, taking advantage of AI features will require a bit more than just downloading a few plug-ins.
Take into account whether you have the storage and the infrastructure necessary for AI capabilities to work properly. Of course, this need can be lessened somewhat by choosing a cloud-based SaaS LMS.
Even then, you have to set aside some time for your staff to get used to the new system and features. They should know how to use the tools, troubleshoot simple issues, and recognize when AI algorithms are underperforming.
2. Costs
High-tech features usually don’t come cheap. That’s true here as well. Think about which features you need and which you don’t. There’s no need to pay extra for fancy things you won’t use.
Of course, as with any large project, costs are variable. There are many factors that can affect the cost of applying AI to L&D programs, such as:
Whether you are adding AI to a self-hosted LMS or a cloud solution
Whether you need AI experts to update your equipment or provide consultation
Whether you have a lot of L&D team members to train on how to use the LMS
In essence, expect that if your LMS doesn’t already come with AI features, you’ll have to spend some money to get them.
3. Talent
AI, while powerful, is still very new. As such, it can often be hard to find experts to help you realize your AI projects. A lack of internal expertise is one of the main reasons why companies hesitate to pursue artificial intelligence, especially since workers with AI skills can see an average 56% wage premium, indicating a competitive talent market.
There are two main ways to address this:
Work with external experts and companies to provide solutions
Increase internal expertise through training
4. Infrastructure
Features like automated content curation, recommendations, and personalized learning pathways are very tempting and the benefits they can bring are undeniable.
Nevertheless, you need to have the infrastructure to support all this. If your equipment and software are outdated, you won’t be able to properly use the often resource-intensive AI-enabled tools.
Therefore, if you want to use AI in your online learning programs, you first have to take stock of your digital infrastructure. Is it modern and powerful enough? If not, that’s another investment and cost to consider.
5. Overestimation
Artificial intelligence is very useful, but it’s important to remember that it’s an advanced technology, not magic. As such, the results you get from AI are only as good as the data you put in it. Even the best AI-based LMS won’t help you if your learning content is not fit for purpose.
That’s why it’s important not to neglect other parts of your learning and development strategy. You can’t expect AI to be a silver bullet that’ll solve all your learning challenges on its own.
This is yet another reason why training your staff to use AI properly is crucial. They need to be able to recognize the limitations of machine learning and AI when the system is not performing as well as it should.
Transform your learning programs with AI-powered solutions
Artificial intelligence is changing how organizations approach learning and development. From virtual coaches that support learners 24/7 to AI-powered content creation that saves countless hours, the practical applications are already delivering results for forward-thinking L&D teams.
The key is finding the right balance. AI won’t solve every challenge on its own, but when integrated thoughtfully into your learning strategy, it can help you personalize learning at scale, close skills gaps faster, and free your team to focus on strategic initiatives rather than administrative tasks.
At the same time, trying to add AI capabilities to your L&D platforms and tool stack on your own is expensive and extremely time-consuming. So, why not choose a cloud-based SaaS LMS instead? Docebo has AI features that make corporate learning more efficient and effective.
Explore why more than 3,800 companies across the world trust Docebo. Book a demo today.
Frequently asked questions about AI in learning and development
How much does AI-powered learning technology cost?
AI-powered learning platforms typically operate on a subscription model, with costs varying based on organization size, user count, and required features. Most organizations find that time savings and improved outcomes justify the investment.
Will AI replace human L&D professionals?
No, AI augments L&D professionals by automating repetitive tasks, freeing them to focus on strategic work. Research shows that while jobs with low AI exposure grew significantly, growth remained robust (38%) even in occupations with high AI exposure, suggesting a trend of augmentation rather than replacement.
What’s the ROI of implementing AI in learning and development?
AI delivers ROI through time savings from automated tasks, improved learning outcomes from personalization, better completion rates, and faster time-to-competency. Many organizations find AI platforms pay for themselves through administrative time savings alone.
How do I get started with AI in my L&D programs?
Start by identifying your biggest pain points, then look for AI features that specifically address those challenges. Begin with a pilot program to test features with a small group before rolling them out organization-wide.
What data do I need to make AI effective in learning?
Essential data includes learner profiles, learning activity data, content metadata, and performance data. Modern learning platforms automatically collect much of this data as learners interact with the system.
