22nd July 2026
Our recent research shows that employees are embracing AI for learning. But often, it’s not through the tools that their employers expect.
Within companies that offer language training to their employees, 58% of leaders believe company-procured platforms are the primary route to AI adoption, but employees are 20% less likely to confirm that this is the case. Instead, many more reported either using their own choice of AI tools, none at all, or a combination of company and personal tools.
In other words, employees are not reluctant to use AI to learn; some are simply bypassing the organization's learning ecosystem.
The reality of the consumer market today is that AI tools are heavily integrated into everyday work. If, for example, a personal AI assistant helps employees prepare for a meeting, refine their emails, or translate communications, they feel they are already learning, even if that activity never touches the corporate learning platform. Thus, AI-literate employees may take the view that they do not need to actively ‘upskill’ via dedicated programs.
This trend poses a dilemma: if employees are learning elsewhere, organizations may be limiting the success of their AI investments. So, what is prompting employees to seek learning independently and how can leaders assess and remedy unrealized potential in their programs?
Prioritizing organizational guidance
It is hard to understate the importance of active communication. While 54% of leaders believe their organizations actively encourage AI use at work, only 38% of employees feel the same. This is because leaders are more aware of organizational strategies, procurement decisions, and policies, while employees judge support and guidance through their everyday experience. In fact, 62% of employees explicitly report a lack of organizational guidance when it comes to AI in learning.
The motivation data reinforces this point. Asked what would make them more willing to use AI-powered learning, employees did not ask for more sophisticated technology. Their top priority was clear guidance on using AI effectively (51%).
Exemplifying where the greatest need for leader intervention lies, the group who most frequently use AI tools on their own initiative – employees aged 18–29 – placed the most value on guidance for using AI effectively. Older employees, particularly those over 46, were the most likely to use company-provided tools and reported lower concerns around support.
This suggests that employees who use personal AI tools the most may be doing so due to a lack of guidance from their organization. The younger generation may also be more confident with AI assistants (the most common ‘learning’ tools that are embedded ‘in the flow of work’), but unaware that this is not an effective way to learn, or track their progress.
Taken together, the findings suggest a communication and support gap more than a technology gap. Organizations may have invested in AI tools and published guidance, yet many employees either remain unaware of those resources or choose alternatives that feel more accessible or immediate.
Leaders can build a culture of support in AI learning by communicating three vital messages: the value of the company-provided tool for personal growth, guidance on how to get the most out of it, and support for using personal AI tools without disrupting or replacing real learning.
Which AI adoption metrics are more meaningful?
Platform engagement and course completion remain useful indicators, but they no longer tell the whole story. If employees increasingly learn through consumer AI tools alongside formal learning programs, traditional metrics risk underestimating both AI adoption and learning activity.
Instead, organizations need a two-pronged approach, addressing the priorities of the business – ROI – and of the learner – progress.
The learning technology itself partly holds the solution. AI, and particularly agentic AI, is a powerhouse when it comes to gathering and understanding data. On the EF Corporate Learning platform, for example, you can monitor the real-life capabilities of each learner with advanced progress tracking, both proving ROI for managers and offering motivation for learners. This, more than completion metrics, will speak to the value of your investment, regardless of whether additional learning is happening elsewhere.
Beyond that, anecdotal or qualitative evidence of learner behavior is vital for seeing the bigger picture. Leaders will benefit from asking learners about learners’ preferred tools so that they can ensure company-provided solutions match or surpass those tools. For example, workers need to consolidate their learnings, with nearly 80% of learners placing importance on practicing workplace skills using AI. If this is true in your organization, the question is how do you offer practice for the skill you are building.
The value of listening
Ultimately, the data suggests that AI itself is not the obstacle as employees have already demonstrated a willingness to incorporate it into their learning. The real challenge is to guide learners towards technology that does the job more effectively, and with greater motivation on the part of the learner, than anywhere else in the consumer market. Achieving this not only nurtures your employees’ skills but builds your EVP (Employee Value Proposition) as an organization that understands the needs of their people and the future.
Leaders can begin by understanding how their teams already operate, then work backwards to deliver solutions that align with existing workflows while maximizing efficiency and adoption. In other words, it starts with listening to learners, rather than policing learning.
Interested in learning more about how to unlock the power of language learning?
