“We have AI tools that our employees can ask questions from. We don’t need custom e-Learning content for our training.”
This is a common sentiment that most decision-makers may be tempted to think. As most industries are keeping pace with AI technology, quickly moving from simple digitization to automation and AI-orchestrated processes, it is easy to think that e-Learning modules are a thing of the past.
While AI systems solve many business problems, liberate capacity, and accelerate performance– the people behind operationally mature organizations require structure to successfully leverage these technologies. People learn best when everything is highly structured, intentional, and integrated into the task at hand.
Cognitive science supports this. Sweller’s (1994) work on schema acquisition and automation explicitly connects the structuring of information with reducing learning difficulty and facilitating schema acquisition.
There are a lot of technical terms there, we know! But basically, the study found that for people to remember, understand, and truly learn information, we have knowledge structures called “schemas” that allow our brains to process complex information more efficiently. Our brains map connections and build structure. Effective learning, therefore, should facilitate an appropriate structure for organizing information, practice, feedback, social interaction, allowing for a certain level of difficulty for independent thinking. Instruction creates that structure in our minds.
What happens when you remove structure and replace them with AI tools? Anyone who has experienced this from generative AI agents will know: we are simply exposed to information. Information is readily available– and yes, it’s great! We save hours if we were to search information, much less process data or create content. But did your workforce learn? What happens to your workers’ skills acquisition and development?
The question then is not whether e-Learning has become obsolete in an AI-enabled workplace. It is whether we are designing learning with the same intentionality with which we are designing our technology.
Digitization can make knowledge accessible. Automation can make processes faster. AI can make information responsive and increasingly personalized. But none of these, on their own, guarantee learning. Operational excellence still depends on people developing the knowledge, judgment, and skills to use these technologies well. The organizations that will get the most from AI are not necessarily those with the most sophisticated tools, but those that build the strongest structures around how their people learn, practice, apply, and continuously improve.
References
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312. https://doi.org/10.1016/0959-4752(94)90003-5
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