Extended reality has spent years hovering on the edge of workforce conversations.
The promise was easy to understand, but many programmes never moved beyond early pilots, often because they were too hard to deploy across sites, too difficult to support, or too tricky to justify with hard outcomes.
What is changing now is the tone of the buying conversation.
The questions are increasingly about operational fit: can it be deployed, managed, sustained, and measured in ways that reduce risk rather than adding to it.
John Iaia, Global Head of Strategic Alliances for XR and Vision AI at Lenovo, sees that shift clearly.
“What I’m hearing these days most is a shift from curiosity to practicality out in the market,” he said.
XR is no longer being treated as an experimental pilot; it is being asked to function as critical workforce infrastructure, requiring the same reliability, security, and measurable ROI as any other enterprise-grade technology category.
Skills Gaps and Role Gaps
Skills gaps are often discussed as if they are purely a training problem, but employers and workforce boards frequently encounter a more basic issue first: role fit.
People apply for roles they do not fully understand or enrol in training programmes without a clear view of what the job requires day to day.
That creates frustration for employers and candidates alike, and it can show up as churn before a worker ever becomes productive.
For Transfr, a company that offers immersive, multi-modal career exploration and training through interactive assessments, VR simulations, and intuitive planning tools this is an ever-present issue.
Bharani Rajakumar, Founder, Transfr, described the pressure as systemic.
Employers are trying to fill high-growth roles while candidates face uncertainty about what the labour market will look like as automation and AI reshape job content.
From Transfr’s perspective, immersive learning helps close the gap between a job title and the lived reality of the work.
Rajakumar said people often commit to pathways without understanding the demands, which can lead to drop-off later.
“People sometimes enrol in training programs without a clear understanding of what the job or the career pathway actually demands, and that leads to attrition.”
This is where workforce boards and employers tend to align.
Better visibility earlier tends to mean better outcomes later, whether that is in reduced course drop-out, fewer mis-hires, or better employee confidence on day one.
Immersive Learning Can Reduce Churn
Immersive learning is often framed as a way to teach skills more effectively, but the workforce value is broader than training delivery alone.
It can also work as a realistic preview that helps people decide whether a pathway is the right fit before they invest months in a programme, or before an employer invests in onboarding.
Iaia described the employer pressure in two themes. The first is persistent gaps in high-growth roles. “A lot of the [requisitions] are seeming to stay open because candidates don’t have the correct pre-exposure or confidence,” he said, adding that this is “not just because they’re lacking any sort of aptitude.”
The second is speed. “Employers, workforce boards, they need productive people,” Iaia said. “People [need] to be productive faster with less churn.”
From that viewpoint, immersive learning becomes a way to move people along the path from initial interest to genuine readiness. It can also help employers avoid the cost of late-stage mismatch.
Put simply, the earlier the misalignment shows up, the cheaper it is to correct.
From Pilot to Program
For most organisations, the biggest barrier to immersive learning is not whether the content is compelling.
It is whether the programme can be run reliably across multiple sites without becoming a headache for IT and operations.
That is where Lenovo positions its value. Iaia said Lenovo’s role is to remove friction by bundling the pieces and supporting deployment at scale, rather than leaving customers to stitch together hardware, software, and support.
In his view, the market has moved beyond the “XR is interesting” phase and into a more demanding stage where leaders want operational answers.
More concretely, Iaia described Lenovo’s strength as operational packaging.
“We bring global reach, trusted enterprise and education industry relationships and the ability to package hardware and best in class software solutions like our Lenovo integrated solution support services (LISS).”
He also emphasised ongoing operational services. While immersive learning can deliver the outcomes, the programme still needs maintenance, lifecycle support, and predictable management.
That layer is often overlooked in early pilots, but it becomes unavoidable at scale.
From the Transfr side, Rajakumar made a similar point about “embedding” in real processes. If adoption depends on heroic effort, it is unlikely to last. If it fits into established procurement and deployment pathways, it can become repeatable.
AI Is Changing Skills Faster
The workforce story is also being reshaped by AI. In many sectors, job content is changing faster than traditional curriculum and training updates can keep pace. That increases the value of adaptability and makes “learning how to learn” a more important outcome. While much of the focus is on displacement, AI is also improving how workers are matched to roles—particularly in skilled trades and technical fields—helping people find positions that better fit their capabilities.
Iaia described adaptability as increasingly central. “Adaptability to a large degree is becoming the meta skill,” he said. Technical skills still matter, but they evolve quickly, particularly with AI tooling becoming embedded in day-to-day work. He also argued that durable advantage is increasingly tied to human capabilities, including “communication, judgment… collaboration and your leadership skills.”
Rajakumar also sees AI as a tool that can support skill development, rather than simply a threat to jobs. He described a concept of an “AI career coach” within immersive experiences, designed to guide learners as they practise tasks and build confidence.
“AI has enabled us to test in an R&D environment an integrated AI Career Coach—essentially providing every learner with a personal mentor who guides them through tasks, providing real-time feedback that simulates a master instructor at a fraction of the cost.”
For workforce programmes, the opportunity is to combine realistic practice with guidance and feedback, then connect that readiness to real pathways.
If AI accelerates change, the workforce response cannot be limited to static training modules. It needs to be practical, contextual, and repeatable.
What Workforce Leaders Should Measure Next
For workforce leaders, the question is no longer whether immersive learning is interesting. It is what they should measure to decide whether it is worth scaling.
Iaia’s view is that success should be judged by evidence that matters to operators: faster readiness, better fit, and broader access.
Rajakumar’s emphasis remains on access and opportunity. He argues that workforce development should give people clarity early and widen access to pathways that deliver stability and upward mobility.
For workforce leaders, the appeal is simple: less guesswork, better fit, and faster readiness, without turning deployment into a science project. In the end, Iaia argues the differentiator will be how quickly people can build real competence in real conditions.
“In an AI economy that we’re all hurtling towards, the winners will be the people who can learn quickly and apply those skills in real context.”
