The next learning advantage is better judgment, not more content

Organisations have become remarkably good at giving employees access to learning. Courses, digital platforms, AI tools and development programmes have expanded the amount of knowledge available to the workforce.

But access is no longer the hardest part of capability building.

The more consequential question is what happens after employees learn something. Can they apply it when the situation is ambiguous? Can they exercise judgment under pressure? Can they adapt what they know to a customer, colleague or business problem they have not encountered before?

This conversation is part of the video interview series in association with enParadigm, exploring the practice gap between building workforce capability and translating that capability into performance.

In this edition, Ng CY, AGM Learning & Talent Development at a leading telecommunications provider, joined John Cherian, CEO, enParadigm, in conversation with Jerry Moses, Senior Editor, People Matters, to examine how organisations can move learning closer to real work.

A central idea emerged: as knowledge becomes more abundant, capability building must increasingly focus on application. That means designing for context, creating opportunities to practise, strengthening the role of managers and measuring whether learning actually changes decisions and behaviour.

Learning has to move beyond the programme

For years, organisations have largely approached learning as something employees attend.

Employees identify programmes with their managers, complete courses and accumulate learning hours. CY argued that while organisations have become effective at delivering these interventions, translating them into action remains far harder. “Organisations have been very good in terms of delivering learning programmes,” he explained. “But there’s always this challenge of bringing it into action and translating learning into action.”

Part of the difficulty lies in an older mental model of learning itself. Employees may still associate development with attending a programme at a particular point in the year rather than continuously building capability through work.

That becomes harder to sustain when roles, technology and business priorities are changing continuously.

Closing the practice gap therefore requires more than redesigning content. It requires employees, managers and organisations to rethink where learning happens and what it is ultimately supposed to enable.

In an AI world, context becomes the differentiator

AI is making knowledge easier to access, content faster to create and learning easier to personalise.

But John argued that these advances make one capability increasingly important: knowing how to apply knowledge to the situation in front of you. “Context is king,” he said. “Any learning is effective if it is relevant to the immediate context that we are trying to apply it in.” That changes the starting point for learning design.

Instead of asking primarily what concepts or frameworks an employee needs to know, organisations need to ask what that employee needs to be able to do.

What decision must they make? What conversation must they navigate? What trade-off will they encounter? What does effective performance actually look like in that situation?

It also means recognising that performance is not determined by skill alone.

John described performance through the combination of skill and will. Learning can strengthen capability, but performance is also influenced by motivation, leadership, incentives and the broader organisational environment.

The implication is important: not every performance problem can be solved with another learning intervention.

Managers are where learning either translates or disappears

One of the biggest barriers to learning in the flow of work is usually assumed to be time.

CY reframed the issue around the people manager.

“The key outcome is really to improve the quality of decision making,” he said. “When it comes to post-learning, it is really about the application of what employees have learned.”

That application depends on what happens when the employee returns to work.

Does the manager know what they learned? Is there an opportunity to apply it? Can the employee experiment, or are they immediately pushed back towards the fastest established way of completing the task?

Without those conditions, even a strong learning intervention can quickly become disconnected from work.

John argued that this makes the manager disproportionately important. Managers need to observe what is happening on the ground, understand where individuals are succeeding or struggling and provide coaching, mentoring and feedback in context.

Organisations therefore cannot expect managers merely to approve learning. They need to equip them to become active participants in capability development.

Employees need somewhere to practise before the stakes are real

The abundance of knowledge creates another paradox. Employees today may know significantly more about business concepts, workplace situations and tools before encountering them in practice. But understanding what should happen is very different from experiencing it.

“Many times, we interpret the understanding and the knowledge as the fact that the person is actually ready to do that role,” John explained. “But when they actually face ground reality in the job, the situation is very different.”

The answer is not necessarily more content. Instead, employees need environments where they can rehearse difficult situations before confronting them for real.

John describes this as simulated net practice: recreating situations employees are likely to encounter and allowing them to repeatedly apply judgment in a safe environment.

These situations could involve managing an employee, responding to a customer, solving a business problem or handling a difficult stakeholder conversation.

“The space for simulated net practice has never been higher,” he said.

AI expands what these environments can offer. Scenarios can become more contextual and adaptive, allowing employees to test decisions, experience different reactions and improve through repeated iterations.

As expectations for performance rise, practice becomes not an addition to learning, but part of how organisations prepare people to perform.

Measure what changed, not what was completed

The shift from activity to application also changes how organisations should think about measurement.

CY noted that organisations have historically relied on indicators such as training hours and course participation partly because they are easy to capture.

But those measures say little about whether capability has actually changed.

“How do you link the learning outcomes to the business objectives?” he asked.

John suggested starting with a simpler question: what changed?

“What has a person changed after they went through any learning input?” he asked. “Is there a shift in confidence? Is there a shift in behaviour? Is there a shift in terms of application?”

Technology is making some of those changes easier to observe. Repeated simulations can reveal whether an individual improves at handling a situation over time, while AI-enabled assessment can provide greater visibility into behaviours such as empathy, resilience, consultative selling and problem solving.

The objective is to build a clearer chain between the intervention, the behavioural change it is intended to create and the business outcome that ultimately matters.

Better capability starts with a different lens

Asked to identify one thing leaders could do immediately, both CY and John returned to decision-making.

CY encouraged leaders to examine whether they are approaching new problems with assumptions built for an older environment.

“Take a step back and review how you make decisions every day,” he advised. “If you are still using the same pair of lenses as what you did years ago, it’s time to review.”

John’s recommendation was closely related: approach situations with greater open-mindedness and understand the current context without allowing assumptions from the past to determine the response.

That may ultimately be the deeper practice gap organisations need to close.

As AI makes knowledge increasingly abundant, capability will be defined less by how much employees know and more by whether they can apply that knowledge when the context changes.

The organisations that gain an advantage will not necessarily be those providing the most learning. They will be those giving people the strongest opportunities to practise, improve their judgment and make better decisions when it matters.

Watch the video on YouTube here.