Overview
Corporate learning failed to deliver impact despite personalised content recommendations. This article explains why personalised learning in the workplace must focus on behaviour and practice, not courses. It shows how contextual prompts, real-time practice, and on-the-job reinforcement outperform Netflix-style content personalisation for lasting skill development and measurable performance change.
Introduction
The L&D industry rushed to copy Netflix. Adaptive learning platforms promised to deliver “the right content at the right time.” AI engines analysed learner preferences, recommended relevant courses, and curated personalised playlists. If Netflix could keep people watching by personalising content, surely L&D could improve learning by personalising training content.
Yet companies investing $98 billion annually in corporate training saw the stubborn reality remain: only 25% experienced measurable performance increases (McKinsey). Skills didn’t transfer to the workplace. Business outcomes barely budged.
Here’s what the industry missed. Netflix optimises for consumption. Learning requires practice.
We personalised what people watch, when the real challenge is personalising what people do.
The Netflix Rush Made Perfect Sense—At First
LinkedIn Learning is the pinnacle of Netflix-style training. Massive content libraries with AI-powered recommendations based on your role, skills gaps, career interests, and what similar professionals are watching. Personalised course suggestions, curated learning paths, “you might also like” recommendations. It’s sophisticated content matching at scale.
The technology delivered what it promised. These platforms do sophisticated work analysing role requirements, career aspirations, skill assessments, and learning history. They surface content that matches individual needs. By every measure of content relevance, they succeed.
But research on training transfer from the Journal of Management tells a different story. Only 10-30% of training content transfers to workplace behaviour in the best conditions.
The content was more relevant, more engaging, more personalised—and still not creating lasting behaviour change.
Why Content Personalisation Misses the Point
Netflix succeeds by keeping you engaged with its content library. More viewing hours mean success. But learning doesn’t work that way.
Consider how people actually develop skills. A chef doesn’t become proficient by watching cooking videos, no matter how perfectly those videos match their cuisine preferences. A surgeon doesn’t master procedures by completing personalised e-learning modules. Skills develop through repeated practice in authentic contexts.
The forgetting curve doesn’t care how relevant your content is. Without reinforcement, people retain only 56% of new information after one hour, 36% after nine hours, and just 21% after 31 days.
Personalising which content someone forgets doesn’t solve the forgetting problem.
Some organisations recognised this limitation and moved toward experiential learning—bringing employees together for simulations, team-building exercises, or hands-on workshops. The results are promising, with some suggesting retention rates for experiential learning can reach as much as 90%. This points to a hands-on approach leading to better retention.
But here’s the catch: most experiential learning still pulls employees out of their work. Whether it’s a two-day offsite or a half-day simulation, it remains episodic. Employees experience something once, learn from it, then return to their desks where the insights gradually fade without reinforcement. It’s a strong starting point. It’s better than watching videos, certainly—but it needs to be complemented with opportunities for repeated practice in authentic work contexts that actually builds habits.
Personalising Practice, Not Content
Think about brief prompts matched to specific practice opportunities in actual work. A manager learning feedback skills doesn’t get a personalised video library or attend a quarterly workshop—they get a context-specific prompt right before their next one-on-one: “In today’s conversation with Sarah, practice asking one open-ended question about her career goals, then listen for 30 seconds before responding.
The prompt takes seconds to understand. The value comes from practising it in context, during work that’s already happening.
Real personalisation considers where someone is in their skill development. A manager who’s mastered basic feedback might practice navigating difficult performance conversations. Or team leads and supervisors in manufacturing settings need to ensure their teams are following SOPs, so they can carry out the activities as they do their safety walks or shift briefings. Someone earlier in development practices simpler behaviours first—perhaps just noticing when team members do something worth recognising.
The progression is personalised to capability, not just matched to role.
The most sophisticated personalisation accounts for when someone is ready to practice. Not “you should complete this module” or “attend this workshop” but “you have a team meeting in twenty minutes—here’s one specific behaviour to try during it.” The prompt arrives at the moment when practice is possible, when the context is right, when application can happen immediately.
This approach requires different infrastructure than content recommendation engines. Not platforms optimised for delivering videos, but systems designed to deliver contextual prompts. Not algorithms matching people to courses, but systems matching people to practice opportunities in their actual work.
The 70-20-10 model reminds us that 70% of learning happens on the job, not in classrooms or simulation centres. The challenge is to create better practice opportunities where work and learning become indistinguishable.
Where This Leads
Content libraries will remain useful for building foundational knowledge. Experiential workshops will continue to create memorable learning moments. But competitive advantage won’t come from better content recommendations or more engaging off-sites.
It will come from better practice personalisation—matching people to the right behaviours to develop next, delivered at the right moments in their actual work, progressing in difficulty as capability grows. Learning that happens so seamlessly within work that employees barely notice they’re being trained.
The technology to deliver personalised practice at scale exists now. The measurement methods to track behaviour change rather than content consumption are proven. The only question is how quickly L&D organisations will recognise that they’ve been personalising the wrong thing—and start building infrastructure around what actually creates lasting skill development.
