As workers’ roles change faster than they can be trained, many are relying on artificial intelligence tools to cover their skills gaps, with potentially detrimental consequences, according to a July 15 report from employee training platform TalentLMS.
“AI is blurring the line between learning and doing,” shifting how employees build skills, Dimitris Tsignos, CEO of TalentLMS’s parent company Epignosis, noted in a press release. While AI helps employees complete work they aren’t trained to do, employees are getting the work done without developing skills they need to grow with their roles, the research found.
A June survey of 1,200 employees in the U.S. ages 25-64 revealed that 41% said their role has evolved faster than their company’s ability to train them. Almost 6 in 10 reported using AI tools at least sometimes to complete tasks they weren’t trained to do, and 29% said they’ve delivered work they couldn’t fully explain if asked how they did it.
Of concern, nearly half (47%) said they keep quiet about not knowing how to do something, most often because they were expected to figure things out on their own (50%) or didn’t want to appear incompetent (49%), according to the report.
“The result is a workplace where performance doesn’t reflect capability,” and where organizations build up “learning debt” — the growing backlog of learning that accumulates when work evolves faster than employee training and learning can happen, TalentLMS explained.
About two-thirds (62%) of employees said they use tactics to get around not having the skills, knowledge or training needed to complete a task, although not all of these “workarounds” are problematic, the report emphasized. “Asking a colleague, searching for information or learning through experimentation are effective ways to build knowledge,” it said.
The issue arises “when shortcuts become a substitute for learning, rather than a path to it,” the report pointed out. Over time, if not properly addressed, this shows up in preventable mistakes, lower-quality work and weaker performance.
To break the cycle, researchers recommended taking a few practical steps. First, learning should be embedded into the workflow. This means delivering learning closer to the moment of need, such as introducing training when new tools and processes are introduced.
Learning should also be shorter, more targeted and easier to access during the workday, the researchers added.
Second, managers must sharpen their “skills visibility.” Managers play a critical role in identifying learning debt early, but they can only act on what they see, the report explained. To capture problems as they unfold, managers can hold weekly one-on-one conversations about building skills, and share the data with employees to identify and track emerging capability gaps, the researchers suggested.
Importantly, gaps that surface should be treated as valuable intelligence, not poor performance, and mistakes should be viewed as learning opportunities, rather than reasons to assign blame, the report emphasized.
Also, instead of placing undue value on the appearance of having all the answers, employees should be encouraged to feel safe about asking questions and requesting feedback as well as be rewarded for being open.
Recent studies confirm the skills gap has become more pronounced over the past year. The gap is particularly noticeable among Generation Z and millennials, who have been found to be below average in three of the most essential skills in the AI era — critical thinking, attention to detail and creative problem solving, according to research from AI candidate screening platform Cangrade.