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Personalised learning has moved from a “nice to have” to a strategic necessity. As organisations navigate AI adoption, digital acceleration, and constant structural change, one uncomfortable reality is becoming increasingly clear: much of the learning we provide to leaders is no longer fit for purpose.
Senior leaders are not disengaged because they dislike learning. They are disengaged because too much of it feels disconnected from their reality.
The growing gap between leadership needs and learning delivery
Across sectors, executives face compressed decision cycles, rising complexity, and accountability that cuts across strategy, people, technology, and regulation. Yet learning systems often still assume leaders have the time, patience, and tolerance for generic content.
This mismatch has consequences. When learning fails to reflect a leader’s role, context, or immediate priorities, it is deprioritised. Worse, it is mentally categorised as “noise”. Over time, this disengagement cascades through the organisation, signalling that learning is something to be completed, not something that drives performance.
Personalisation matters here because leadership learning is not about accumulation of knowledge. It is about relevance, judgement, and behaviour under pressure.
Why scale-driven digital learning underperforms
Digital learning is frequently blamed for disengagement, but the problem is not digital delivery itself. The issue lies in how digital learning has been designed and governed.
Many organisations still rely on static e-learning models: content created once, uploaded to an LMS, and left largely unchanged. These models excel at compliance, standardisation, and reach. They perform far less well when the objective is decision quality, behavioural change, or strategic adaptability.
In practice, digital learning has scaled faster than L&D capability. Tools have advanced, but operating models have not. Without the time, skills, or frameworks to design adaptive learning journeys, organisations default to what is easiest to deploy rather than what is most effective.
Leadership development is not a single category
Another structural issue is how loosely we define “leadership development”. Treating leadership as a single learning domain ignores the realities of modern organisations.
A finance leader navigating capital allocation decisions faces a very different development challenge from a commercial leader driving growth in a regulated market. Even within the same function, two leaders with similar job titles may require entirely different behavioural shifts to improve performance.
Personalised learning recognises this diversity. It accepts that leaders bring different experiences, blind spots, motivations, and constraints—and that development must start from where the individual actually is, not from a predefined curriculum.
From programmes to learning ecosystems
In a volatile environment, leaders cannot afford to complete long programmes that may already be outdated by the time they finish. What they need instead is learning that evolves alongside their role.
Personalised learning ecosystems support this by focusing on small, targeted interventions that combine insight, reflection, and application. Learning becomes iterative rather than linear, continuous rather than episodic.
Crucially, this approach prioritises behaviour change over content consumption. The objective is not to “cover material”, but to support better decisions, stronger leadership habits, and measurable improvements in outcomes.
Making personalisation practical, not theoretical
Personalised learning does not require organisations to discard everything they already have. It requires a shift in emphasis.
First, leaders must develop awareness of their own starting point—strengths, gaps, and priorities. Self-awareness dramatically increases the return on any learning investment.
Second, choice matters. Allowing leaders to navigate pathways aligned to both organisational strategy and personal development goals increases ownership and relevance. Many leaders are already curating their own learning informally; organisations should support this rather than resist it.
Third, adaptive digital tools should be used intentionally. AI can personalise learning in real time, suggest next steps, and retain contextual memory—but only if guided by clear development objectives.
Finally, human support remains essential. Coaching, mentoring, and peer dialogue are what anchor learning into lived experience. Technology should enhance these relationships, not attempt to replace them.
Measuring what actually matters
One of the most persistent weaknesses in learning strategy is measurement. Completion rates and attendance figures are easy to collect, but they say little about impact.
If learning is meant to improve leadership effectiveness, then success should be measured against progress toward specific goals: improved decision-making, stronger team outcomes, or clearer strategic execution. When leaders achieve meaningful goals and then reset new ones, learning becomes a continuous driver of performance rather than a periodic intervention.
A necessary shift, not a trend
In an economy defined by speed and uncertainty, static learning models will always lag reality. Personalised learning is not a fashionable concept—it is a structural response to how work, leadership, and decision-making have changed.
If organisations expect leaders to adapt continuously, then learning must adapt with them. Relevance is no longer an enhancement to learning design; it is the foundation on which credibility and impact now rest.
The question is no longer whether we can personalise learning. The real question is whether we can afford not to.
If this resonates with what you are seeing in your organisation, feel free to comment or send a DM.
Looking to have a chat about this or continue the conversation? Find me on Linkedin here: https://www.linkedin.com/in/stefangauciscicluna/
Stefan Gauci Scicluna