DevLearn 2024: Did it deliver on the AI Promise from 2023?

At DevLearn 2023 there was a lot of talk on AI revolutionizing the learning technologies landscape. However, much of the promise was focused on what was yet to come rather than the here and now. This year, I was keen to return to DevLearn to assess whether vendors have delivered on their promises.

The short answer? No!

While AI remains the talk of the town, most practical applications still center around content creation. We now have impressive tools that can generate audio, video, images, and entire learning modules in minutes or even seconds. These tools empower L&D practitioners to create high-quality content faster than ever before, when wielded by experienced learning designers.

However, these advancements primarily accelerate existing processes rather than revolutionizing them. I was hoping for transformative learning experiences – solutions that fundamentally redefine how we learn, moving beyond what was available before ChatGPT and other generative AI tools.

Progress and innovations

Some revolutionary offerings were present, including Learning Pool’s AI suite:

• AI Conversations: A role-play tool for practising difficult conversations
• AI Coach: A coaching bot for scaling coaching interventions
• GEM (Gaining and Evidencing Mastery): A generative AI-powered assessment tool for demonstrating and building competency

While these standalone tools are impressive and innovative, they don’t yet deliver the comprehensive learning revolution we anticipated. This observation resonates with Donald H. Taylor and Egle Vinauskaite’s “AI in L&D: From Talk to Action”. Their ‘Immaturity Model’ attempts to explain a paradox we have observed over the past year.  L&D practitioners increasingly use AI in content creation, but this does not necessarily lead on to more complex uses. Why is this?

The missing piece: True personalization

What’s needed is AI that moves beyond single learning interventions to tools that meet learners wherever they are. Tools that can truly personalize the entire learning process for individuals whatever their goals. At Learning Pool, we’re exploring this vision through a research project. Our aim is to develop an AI Tutor that combines deep knowledge about each learner with the comprehensive content housed in our learning platform. This AI would understand who the learner is, their role, skills, goals, and ambitions—while remembering past interactions and progress. Whether it’s in-platform learning or real-life tasks, the AI Tutor would guide learners, helping them set goals, reflect on achievements, and take meaningful next steps.

This kind of feature or bot is possible to create with generative AI but it’s not easy. Firstly you need content that is well structured and indexed for the AI to be able to understand the context of the content and hence be able to know which pieces of content are relevant to the conversation and user and which pieces aren’t. And unfortunately, the more information you feed generative AI the less generative it becomes. It can become easily confused meaning it doesn’t know when to use its innate knowledge and when to use its resource content.

These challenges aren’t insurmountable but they are complex. At Learning Pool, we’ve successfully completed the first stage which is the content indexing and we’re now moving into the second stage: exploring how to create the best user experience for the huge variety of learning aims our users might have. It’s a fascinating journey and we’d love to hear your ideas on how might use such a tool within your organization. Your input will help us incorporate a wide range of use cases as we strive to revolutionize organizational learning. Our goal is to provide every single employee with an AI tutor and coach that supports them every step of the way.