Many organizations are struggling to identify and deploy the skills they already have, creating a growing gap between available talent and how it is used, according to a report from TalentLMS.
Half of employees and managers surveyed said their company hires externally for skills that already exist in-house, pointing to a widespread breakdown in skills visibility. The report, based on responses from more than 1,500 U.S. employees and managers, highlights a shift in workforce challenges.
Rather than a lack of talent, many organizations are dealing with “invisible talent”—skills that exist but are not recognized, tracked or effectively applied. Only a small minority of respondents said their organization does not face issues with skills visibility.
That gap shows up in how managers and employees view workforce capabilities. While 90% of managers said they understand their teams’ skills, only 69% of employees agreed.
A similar disconnect exists around development: 90% of managers said they support skill building, compared with 60% of employees who said they receive that support.
“This is intensified with teams’ restructuring, high hiring rates and priorities shift to new items that may require new skills compared to what the team had been working on,” says Manos Dramitinos, CTO at Epignosis, parent company of TalentLMS.
He explains for engineering teams, that gap creates practical execution problems.
“A team may start hiring externally for a capability that already exists internally or assign work without realizing someone on the team already has relevant experience,” he says.
Over time, projects take longer to staff, technical knowledge stays siloed, and teams become less flexible when priorities shift.
Skills Overviews Outdated
Greg Fuller, vice president of Skillsoft Codecademy Enterprise, says many IT leaders believe they have a clear view of their teams’ capabilities.
“But that view is usually based on job titles, experience, or static profiles, not what people can do today,” he says. “You cannot manage what you cannot see, and in most organizations that gap shows up quickly when work is assigned based on assumptions instead of validated capability.”
He explains that in technical teams, this plays out in project delivery: Work is handed to the wrong people, not because talent is missing, but because it is not aligned to the task.
“AI is making that gap harder to ignore,” Fuller says. “Two engineers can use the same tool and produce very different outcomes depending on how they engage with it.”
Growing Risk Around Internal Mobility
For IT and tech professionals, the findings point to a growing risk around internal mobility. Forty percent of respondents said it is easier to find a new job than to move into a different role within their current organization, suggesting companies may be losing talent they already have.
The lack of visibility is also affecting performance. More than half of managers said underutilized skills are the top consequence of poor visibility, followed closely by declining team performance.
At the same time, skill development is often reactive, with 42% of employees saying gaps are addressed only when performance issues arise.
“In tech teams, a lot of valuable skills develop organically through project work, experimentation, and day-to-day problem-solving,” Dramitinos says.
The issue is that many organizations still evaluate people mainly through their current role or previous experience, not through the capabilities they are actively building.
In practice, this creates friction around internal mobility— an engineer may already have hands-on exposure to AI tools, cloud architecture, or automation work, but without clear visibility into those capabilities, they are less likely to be considered for emerging roles or strategic projects.
“Over time, this can slow down internal mobility and make external hiring feel like the only option, even when relevant skills already exist within the team,” Dramitinos says.
Fuller says lack of skills visibility is one of the biggest barriers to internal mobility.
“Many engineers have adjacent or transferable skills that could move them into roles in AI, cybersecurity, or data, but those capabilities are not visible beyond their current team,” he says.
At the same time, roles themselves are shifting, and job titles are no longer a reliable signal of what someone can do.
Fuller says organizations that move forward are the ones mapping skills dynamically and using that insight to redeploy talent. Instead of thinking about mobility as moving into a predefined role, they focus on assembling the right mix of skills for the work at hand.
“That creates opportunities for employees to expand their impact without formally changing jobs and allows the business to adapt faster as priorities shift,” he says.
More Accurate Skills Assessments
Most organizations currently manage skills through fragmented signals such as performance reviews, manager perception, or disconnected systems; the TalentLMS report found just 18% of companies use a centralized approach to track skills.
Dramitinos says the first step is to create a shared, structured view of skills across the organization, rather than relying on scattered data.
“That means building a living skills inventory supported by assessments, learning activity, and peer validation — not just static role descriptions,” he explains.
The next step is connecting that visibility to operational decisions — project staffing, succession planning, internal mobility, and development planning.
“If skills data doesn’t influence how teams are built or how work is assigned, it has limited value,” Dramitinos says.
He adds visibility also depends on culture and communication, noting the teams adapting fastest are usually the ones treating skills visibility as an ongoing operational process, not a once-a-year exercise.
From Static Snapshots to Continuous Visibility
Fuller says the biggest shift he’s seeing is moving from static snapshots of skills to a continuous, real-time understanding of workforce capability.
“That's critical because AI is changing both the pace and the nature of work,” he says.
He suggests organizations need a more dynamic approach to workforce skills as AI reshapes roles and workflows.
Rather than relying on self-assessments or static certifications, companies are increasingly being pushed to validate employee capabilities through real-world performance and continuously connect skills data to how work itself is evolving under AI-driven processes and decision-making.
“Without that visibility, organizations default to assumptions and incremental improvements,” Fuller says. “With it, they can deploy talent more effectively, reduce unnecessary hiring, and make sure AI drives meaningful outcomes, not just efficiency gains.”
