Training Smarter In 2026

"What is changing, quickly, is the operating logic behind effective L&D. For years, many organizations were able to "get by" with a solution-first approach: pick a course, roll it out, hope adoption follows. AI is making that pattern expensive because it scales whatever logic sits upstream. If the logic is weak, AI amplifies the waste. If the logic is strong, AI multiplies impact."

"This is the real shift: L&D is moving from content delivery to decision quality to make training smarter. 1) Personalization Is Becoming The Default, Not The Differentiator Adaptive pathways and recommendation engines are increasingly common. The market is racing toward individualized learning experiences based on role, behavior, and performance signals. The hidden implication: once personalization becomes standard, it stops being a competitive advantage. The advantage moves to what you personalize toward."

"If an organization has not defined target behaviors, conditions of performance, and clear proficiency expectations, personalization simply optimizes consumption. You get more "relevant" learning activity, not better outcomes. What to do instead: Define "good performance" in observable terms before configuring adaptive pathways. Treat "content engagement" as a weak proxy unless it connects to behavior and results. Standardize role-based proficiency signals so personalization has a real target."

AI is embedded across the learning stack and is changing the operating logic behind effective L&D. Legacy solution-first models that prioritize course rollout over defined outcomes become costly because AI scales upstream decisions. Personalization is becoming the default; without defined target behaviors, proficiency expectations, and performance conditions, personalization optimizes consumption rather than outcomes. Predictive analytics can surface capability gaps earlier, but only when organizations have defined which capabilities matter, how they appear on the job, and which signals indicate drift. Organizations must define observable performance, treat content engagement as a weak proxy, and standardize role-based proficiency signals.

Read at eLearning Industry