Organisations today are investing significantly in learning, leadership development, workforce capability, and AI adoption. Employees have greater access than ever to courses, platforms, content, and intelligent tools. Yet access to knowledge does not automatically translate into improved performance.

Research suggests that as much as 40% of the potential productivity value associated with AI remains unrealised, often due to organisations struggling with adoption, workflow integration, and behavioural change. This exposes a broader challenge facing talent leaders: the persistent gap between what employees know and what they can deliver when confronted with real workplace demands.

This conversation is part of the video interview series, in association with enParadigm, exploring how organisations are closing this practice gap by embedding real-world application into their talent strategies.

In this edition, Jolene Huang, Chief Talent Officer, Singapore and Southeast Asia, Publicis Groupe, joined John Cherian, CEO, enParadigm, to discuss why capability-building investments often fail to move the business needle and what organisations can do to develop talent that is ready to make decisions, navigate ambiguity, and perform under pressure.

A central message emerged from the discussion: capability cannot be developed through content alone. Employees also need the right environment, contextual experiences, leadership support, tools, motivation, and opportunities to practise.

Capability does not operate in isolation

The capability-to-performance gap is often treated as a learning problem. But Jolene argued that the conditions surrounding employees are just as important as the skills they possess.

“I don’t think it’s a wrong approach in terms of building capabilities,” she explained. “That’s definitely the basic foundation that you lay for employees to actually be able to do their job.”

However, building skills alone is insufficient if the organisation does not create an environment in which employees can use them. Jolene identified three enabling conditions that influence whether capability translates into performance.

The first is a conducive working environment. Flexible work arrangements, for example, can determine whether employees are able to manage professional responsibilities alongside their lives outside work. Drawing on her own experience as a mother of three, she explained that flexibility remains one of her most important considerations in evaluating a workplace.

The second is access to the right tools and systems. Organisations may provide employees with an extensive technology stack, but those tools offer limited value if they are outdated, irrelevant, fragmented, or poorly aligned with the work employees perform.

The third is leadership support. Employees need leaders who give them the time and space to explore, experiment, make mistakes, and practise new approaches on the job.

Capability building, therefore, is not simply about equipping people with knowledge. It is about creating an organisational system that enables application.

The real shortage is not content, but contextual relevance

Employees today face no shortage of information. The more important question is whether that information is relevant to the situations they encounter.

“There is no shortage of knowledge, and there’s no shortage of content,” John observed. “The gap is always going to be contextual relevance on one side, and probably intent on the other side.”

For learning to influence performance, organisations must move employees beyond theory and concepts towards application, practice, and outcomes.

This requires clarity about what the organisation expects people to do differently. What decisions should they make? How should they respond to customers? What behaviours should managers demonstrate? What outcomes should a particular role deliver?

John also highlighted the role of intent. Even a well-designed learning intervention may fail if organisational and individual motivations are misaligned.

Low application may not always indicate a learning deficiency. It could reflect weak incentives, unclear expectations, limited motivation, competing priorities, or a lack of perceived relevance.

Organisations must therefore look beyond the learning programme itself and examine the broader factors shaping employee behaviour.

The learning strategy must reflect organisational culture

There is no single learning modality that will work across every organisation, workforce, or role. John argued that organisations must understand both their existing learning culture and the culture they wish to create.

Some workforces operate in demanding, field-based environments where employees have limited time for digital self-learning. In such cases, organisations may need to take people away from the workplace and create structured classroom experiences.

Other organisations may already have a strong culture of self-directed learning, making digital and self-nominated programmes more effective.

In some companies, learning is closely associated with being selected or sponsored for a programme. Moving from this nomination-led model to a self-directed culture can require sustained communication, informal learning experiences, learning weeks, and reinforcement over several years.

“Just because something has been the culture doesn’t mean the organisation will want to continue with that culture in the future,” John said.

The learning strategy must therefore bridge two realities: how employees currently learn and how the organisation expects them to learn in the future.

AI is making practice more contextual and realistic

Simulation-based learning is not new. Organisations have historically used simulations to develop capabilities such as strategic thinking, financial decision-making, feedback, coaching, and people management.

What has changed, according to John, is the ability to create highly contextual experiences on demand.

“In the pre-AI era, you used to have simulations which replicated different organisational competencies,” he explained. “The big change that has happened in the last couple of years is that you can now create things on demand which are very context-tailored.”

Organisations can use their own documents, workplace challenges, customer contexts, decision criteria, and role expectations to generate realistic scenarios.

AI-enabled simulations can recreate customer personalities, employee conversations, stakeholder pressures, business trade-offs, and decision-making environments. Employees can then practise responding to those situations before facing them in the real workplace.

These tools can support more than learning. They can also be used to evaluate role fit, assess growth potential, support internal mobility, and align employees with organisational expectations.

John noted that workplace-situation tools can offer stronger indications of future performance because they assess how individuals respond to scenarios resembling the work itself.

The shift is significant. Instead of only asking whether an employee understands a concept, organisations can examine how that employee applies judgment in a realistic context.

Measure capability through the outcomes it is intended to create

The strongest capability strategies begin with a clear business outcome. Jolene shared the example of training members of her talent team in process automation and the use of AI tools. Rather than measuring only whether employees completed training, she established specific indicators, such as the number of processes automated and the time saved.

The broader business impact is still being evaluated, but the initiative demonstrates how targeted measures can create a clearer connection between learning and performance.

John described a similar outcome-backwards approach.

“We always start with the end in mind,” he said. If a sales organisation wants to increase deal sizes, for example, it must identify the behaviours that are likely to produce that outcome. These could include targeting larger accounts, conducting more consultative conversations, collaborating across teams, thinking strategically, or combining multiple solutions in a client proposal.

The learning solution can then be designed around those behaviours. After implementation, organisations can examine whether employees and managers report behavioural change. Business indicators such as deal size can then be assessed over a longer period.

The measurement timeline will depend on the context. Some changes may become visible within 30 days, while complex B2B outcomes may require six months to a year.

The important principle is that organisations should define the business outcome, identify the required behavioural shift, design practice around it, and then trace the impact back through the same chain.

Building a culture of experimentation

When asked what talent leaders could change immediately, Jolene and John arrived at a similar conclusion: stop overthinking and start experimenting.

“Sometimes you don’t need to overthink. You just need to try,” Jolene advised. In a rapidly changing environment, a strategy may become outdated before it is implemented if organisations spend too long perfecting it.

John similarly encouraged leaders to select a specific problem, run a focused pilot, implement a solution, and examine whether it produces an outcome within a short feedback loop.

This mindset will become increasingly important as AI changes the speed at which organisations can create, test, and adapt capability interventions.

Closing the practice gap does not require organisations to abandon learning. It requires them to redesign how learning connects with work.

Employees need relevant content, but they also need purposeful experiences, supportive leaders, realistic practice, useful tools, protected time, feedback, and clear outcomes.

The organisations that succeed will not necessarily be those that provide the most learning. They will be those that create the strongest conditions for people to practise, adapt, make decisions, and translate capability into performance.

Watch the full video here