Adaptive learning is gaining importance as organizations seek better ways to train employees with diverse roles, backgrounds, and skill levels. Rather than giving everyone the same course in the same order, adaptive learning changes the experience based on what each person already knows and how they perform in training.
There is a clear need for more personalized learning. eLearning Industry's 2026 research shows that 65% of L&D buyers see personalization as one of the most valuable uses of AI in learning. But only 44% of vendors say they are building or planning similar features. The same research found that just 7.5% of buyers have fully integrated AI into their learning environments, while 45% plan to do so in the future.
This gap is important because adaptive learning is more than just an AI feature you can turn on. It is a learning strategy that relies on data, assessments, content structure, technology, and human judgment. When these parts work together, organizations can build more focused learning paths. If they do not, an adaptive learning platform might make things more complicated without helping performance.
Adaptive learning uses data to adjust the learning experience based on what a person knows, how they behave, and how they perform. An adaptive learning system can change several things, such as:
Source: eLearning Industry — Read the full article on the original site ↗