“So…what are you doing in AI?” A refresher in AI terminology for Learning and Development professionals.

As we kick off the year, it may have been some time since that last “So, what are you doing in AI?” conversation. AI in learning continues to be a hot topic (or the hot topic) in our industry in 2025. So, whether you’re preparing for the inevitable chat with an old colleague at your next conference, or just curious and need a refresher, here’s a friendly rundown of key AI terms in learning and development with relatable analogies.

These are in no particular order but let’s start with Machine Learning. Think of an eager new starter that has learnt mainly by observing and practicing tasks from other colleagues. Initially, they might make mistakes, but over time, with feedback and practice, they become proficient, or even experts.

In AI, machine learning (ML) is the same as a new starter when it first comes in. It’s a subset of AI where algorithms learn from data. The more data (experience) they have, the better they become at predicting outcomes or identifying patterns.

In an L&D context, an ML algorithm can analyse a business area’s performance data to identify common threads with skill gaps, and recommend personalised training programs.

Deep learning is a subset of machine learning that involves neural networks with many layers (hence ‘deep’). These networks are capable of understanding complex patterns in data. In L&D, deep learning can be used to develop advanced simulations and immersive learning experiences, providing learners with a hands-on, interactive way to grasp difficult concepts. Yeah, it’s deep. 

Large Languages Models (LLMs) 

The “Ask Jeeves” of the AI world. Think of LLMs as encyclopedias with the ability to understand and generate human-like text. These models are trained on vast amounts of text data and can perform a variety of language-related tasks. In L&D, LLMs can be used to create automated content generation, summarise lengthy documents or storyboards, or even act as a coach using conversational agents to assist learners with their queries. They have zillions of use-cases and we’re bound to hear more in 2025.

Natural Language Processing (NLP)

NLP is a seasoned translator who not only translates languages but also understands the context and sentiment behind the words. In L&D, NLP can be used to analyse feedback from learners, summarise long texts, or even create chatbots that provide instant support to learners.

Reinforcement learning

Anyone find a new puppy under the Christmas tree in December? Imagine training your new best friend. You reward it when it performs the command and withhold the reward when it doesn’t. Over time, it learns to associate certain behaviours with positive outcomes. In L&D, reinforcement learning can be used to create adaptive learning systems that provide rewards or incentives for learners as they achieve specific milestones.  So maybe comparing learners to canines isn’t the best analogy however….AI-backed systems are making it much easier to create, support, and report on the effectiveness of learning environments.

Chatbots

Knowledgeable assistants who are always available to answer questions, provide guidance, and offer support. In L&D, chatbots can be integrated into learning platforms to assist learners in real-time, answer their queries, and offer personalised recommendations.  Chatbots continue to expand from the early ‘Clippy’ versions that often took a lot of programming efforts to create and maintain.  AI is now helping to automate, curate, and even triage the way chatbots function. 

Personalisation engines

Like the way a personal trainer might craft a workout plan tailored to your fitness goals, personalisation engines use AI to create customised learning pathways for each individual, ensuring that the content is relevant and engaging for them. It’s a big leap for some large complex organisations that may feel more comfortable with more traditional set-and-forget pathways.

AI-Powered Analytics (Power BI)
Imagine a detective who meticulously analyses data to uncover hidden patterns and insights. AI-powered analytics in L&D can provide valuable insights into learner behaviour, engagement levels, and the effectiveness of training programs, helping organisations make data-driven decisions. For example, Power BI, a powerful analytics tool, can be used to visualise and interpret data from various learning platforms, identifying trends and areas for improvement. By leveraging AI algorithms, Power BI can help pinpoint which training modules are most effective and highlight learners who may need additional support, ensuring that resources are allocated efficiently and effectively.

Let us support you with your next learning project

We have only scratched the surface of the common AI terms currently circulating in the world of learning and development. There are bound to be more that will emerge throughout the year. Hopefully, this has served as a helpful refresher. At Lucid, we’re experienced in supporting ethical AI solutions, particularly when it comes to all things L&D. 

We’re all on this learning journey together, so reach out if you’d like to chat about your next requirement.

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