Everyone is used to highly personalised and dynamic content. We experience relevant, targeted content everywhere, from ads, to streaming services, to social media feeds. It’s time to carry that over into learning, through adaptive learning. The benefit will be how easy it is to find the right learning content. No need to waste time on content that’s not relevant to a person’s role, knowledge, and skill level.

 

What Is Adaptive Learning?

Adaptive learning adjusts automatically to the needs of the individual based on their skills, role, goals, and proficiency level. It’s highly personalised, responsive, and interactive. It's contextual, it's dynamic, and most importantly, it cuts down on time wasted; no more content scavenging, no more time spent on content that’s irrelevant to experience level, and no more waiting for feedback. That way, every moment of development is useful.

The personalisation is fed and enforced by the rich data and analytics that arises from the learning process. Adaptive learning provides more than just completion data: there’s real measurement of knowledge gain and skill growth.

 

What Does Adaptive Learning Look Like in Practice?

Adaptive learning answers a longtime need in the learning industry: The ability to achieve learning that actually occurs in the flow of work. For example, AI capabilities make it possible to produce topic-rich, accurate quisses at scale to easily test knowledge retention. Conversations with AI can adapt in real time, allowing employees to practice challenging soft skills or presentations on complex topics. Adaptive learning makes it possible to provide customised, role-specific paths and instant feedback, so that it’s easier to benchmark performance and iterate.

This level of flexibility and personalisation means learning and work can entirely coexist and boost each others’ effectiveness Here are some example scenarios:

Example: Your team needs to quickly master complex new market regulations. Rather than having them complete a single, static training, AI-generated quisses allow you to assess understanding. Simply checking a “completed” box, doesn’t mean your team is actually prepared to apply their knowledge in the field. Any skill or knowledge gap can directly impact business outcomes and performance, so it’s essential to find out what your people actually know. Once you see where the gaps are, you can curate the right content to fill the gaps for each individual, rather than providing another blanket, one-sise-fits-all training session for everyone that misses the mark after the first one.

Example: Your company is launching an important new product and your sales team needs to deliver the new pitch. You can provide them with an AI-powered coach that’s always available and gives real-time feedback. This allows them to practice their pitch risk-free. They can iterate, apply feedback, and improve their approach before stepping in front of your potential customers. As they learn and practice, they are engaging in practical skill-building with real business impact.

Example: The launch of a new AI tool has direct application for your product team, and they need to build capabilities in an emerging industry skill. You are able to get them up to speed more quickly with AI-curated and expert-checked learning pathways. As the skills needed constantly evolve, content pathways can now be generated at the same pace, which means your people can absorb relevant content faster.

Use cases for adaptive learning are growing, as day-to-day work requires more interactive, dynamic, and diverse learning modalities to keep pace with the capabilities employees need.

 

How Do You Enable Adaptive Learning?

Context is the key. AI has opened the door for truly adaptive learning experiences, but to be successful in providing them, AI first needs the right context. Otherwise, the information it provides is no more tailored than a general LLM or AI assistant.

To ensure AI is purpose-built for learning and upskilling your team, it needs a context in:

• Learning science
• Verifiable skill data
• Integration into systems
• Organisational context aligned to strategic goals

With that as the foundation, the AI is then set up to successfully adapt to the needs of the individual.

 

What’s the Future of Adaptive Learning?

Tech capabilities are growing every day. We do not know what will be possible two years from now, but I assure you that learning at work will become a lot less like a static training session and a lot more like one-on-one coaching with a trusted expert. Learners will be laser focused on content that is actively growing their knowledge and skill set, and they will be putting their new knowledge and skills into practice in low-risk scenarios.

L&D is in the process of evolving from providing content that supports business objectives to delivering AI-native learning experiences that proactively progress business objectives.

 

Nicole Helmer 

Chief Product Officer at Degreed