"For years, many L&D teams have been funded and evaluated on visible outputs: courses launched, completions, content libraries, learning journeys, and activity dashboards. That model was already under pressure. Now, generative AI can produce a large portion of those outputs in minutes. When content becomes cheap and fast, L&D faces a credibility test: If we can generate 10x more assets, will the business perform 10x better? If not, the function risks "hallucinating" its own value-mistaking content velocity for capability lift and stewardship."
"Let's be honest about where AI is already strong: If a general-purpose model can draft 70-80% of what many teams publish, content output can no longer be the center of the L&D value proposition. That output will still matter-but it won't be differentiating. And it raises a tougher question: what part of capability building and stewardship is L&D uniquely positioned to own, that AI cannot commoditize?"
Generative AI can rapidly produce much of traditional learning content, making output volume a weak differentiator. Content velocity risks creating the illusion of value if business performance does not improve proportionally. AI increases efficiency and can boost productivity, particularly for less experienced workers, but it does not automatically strengthen judgment, leadership decisions, or ethical and safe execution. Learning functions must refocus on capability stewardship: defining and measuring the skills, decisions, and execution that leaders care about, and owning the parts of capability building that AI cannot commoditize.
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