Skillsoft finds gulf between AI adoption & readiness

Skillsoft has published research showing a gap between workplace AI adoption and employee readiness to use the technology effectively. The study surveyed 2,000 workers, managers and executives across North America, the UK and Germany.

The report found that 86% of employees use AI tools at work, yet only 24% feel fully equipped with the skills to use them effectively. It also found that 77% of leaders believe their organisations have set employees up for success, creating what Skillsoft described as a 53-point gap between leadership perceptions and employee experience.

One of the clearest findings was the lack of formal assessment of workforce skills. Only 11% of employees said they receive formal skills assessments or benchmarks, while 69% were only somewhat clear or not very clear about which skills matter in their roles. By contrast, 43% of leaders said they were very clear on which skills matter.

The data also pointed to a mismatch between AI deployment and staff training. Just 16% of employees said they receive training before new AI tools are introduced, compared with 23% of leaders who said the same. This suggests organisations are rolling out tools faster than they are preparing staff to use them.

Time pressures also emerged as a barrier to training. Nearly six in 10 employees cited lack of time as the main obstacle to building new skills. The survey also found that one in five employees remain cautious about or do not trust AI tools.

Governance gaps

Governance was another weak point. Fewer than one in 10 employees said their organisation had comprehensive AI governance in place, while 21% said their employer provided no AI guidance at all. Another 31% said guidance varies by team or manager rather than following a company-wide standard.

The findings suggest many employers have embedded AI into workflows without putting in place consistent rules, training or oversight. As a result, organisations are trying to scale AI use without a clear understanding of workforce capability or agreed standards for how the technology should be used.

Ciara Harrington, Chief People Officer at Skillsoft, said the issue was not whether organisations had introduced AI tools, but whether staff were ready to use them properly.

"Organisations cannot afford to confuse AI adoption with AI readiness," said Ciara Harrington, Chief People Officer at Skillsoft.

"When leaders and employees are operating from fundamentally different views of preparedness, performance becomes inconsistent at best and untrustworthy at worst. Closing that gap starts with treating skills as a business discipline and building the systems to align skill supply with evolving demand across the organisation. Most organisations have established processes for hiring, onboarding and performance management, but our research shows many still struggle to bring that same rigour to understanding what skills they have, building the ones they need and deploying them where demand is greatest."

Changing work

The survey also examined how AI is shaping expectations for entry-level jobs. Twenty-nine per cent of employees said they expect AI to reduce entry-level positions. At the same time, 36% of employees and leaders said they expect work to shift more towards problem-solving and collaboration, and similar shares anticipated faster career progression.

For many respondents, training was seen less as a route to advancement than as a way to keep up with workplace change. Some 45% of employees and 46% of leaders said training is mainly about building confidence in their current role.

The findings point to tension between optimism about AI's role in improving work and concern over how prepared employees are for that shift. They also indicate that managers may have a more positive view of readiness than the workforce itself.

Skillsoft conducted the research through an independent market research firm. It covered full-time individual contributors, managers and executives, and examined AI usage, skills readiness, training practices and governance.

Harrington said stronger systems for understanding and developing workforce skills would be central to narrowing the gap.

"The organisations that pull ahead won't be the ones that adopted AI first. They'll be the ones that redesigned work and built a system to continuously develop the skills required to leverage AI in a way that drives purposeful business outcomes.

"Traditional workforce systems help organisations manage employee records and workforce processes. What's often missing is a continuous view of workforce capability, including what skills exist, what skills are needed, how quickly those gaps can be closed and the impact they have on the business. Without that visibility, leaders are forced to make workforce decisions based on assumptions rather than evidence. That means moving from one-time training to continuous capability development and from ad hoc governance to a company-wide standard."