Employers adopt AI tools faster than they can train workers to use them - HR Dive

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Dive Brief:

• While 63% of companies have invested in artificial intelligence training in the last year, 52% of tech professionals say they needed independent training because company programs didn’t keep up with AI changes, according to new research from talent company Randstad Digital.
• The report called this disconnect a “productivity paradox,” and said organizations are building platforms faster than employees can learn to use them. Seventy-four percent of tech workers said they felt they had to upgrade their skills to stay relevant.
• Meanwhile, nearly 1 in 4 workers worldwide have left their jobs because employers didn’t give them structured upskilling opportunities, Randstad Digital said. The study also found that 27% of tech talent thinks their companies aren’t doing enough to develop their skill sets.

Dive Insight:

When companies build AI models without regard for whether their workforce can use them, it creates a capability crisis that Randstad Digital called “acceleration without direction.” This disconnect between what corporations want and what they’re preparing workers for indicates that the factor most likely to impede corporate AI transformation is neither money nor technology, but rather the workers.

“Enterprise AI isn’t failing at the model level; it’s failing at the implementation layer,” Michael Morris, global head of platform and talent at Randstad Digital, said in a statement. “If you increase the velocity of your tools without increasing the capacity of your engineers to govern and optimize them, you get technical debt at scale.”

Specifically in North America, 24% of workers have quit their jobs because there were no development opportunities. Worldwide, engineers, architects and delivery leads are most focused on finding employers that incorporate learning as part of an ongoing commitment to employees, per Randstad Digital.

“The question for leaders is no longer ‘How much are we spending on AI?’ but ‘How fast are our engineering teams learning to work with it?,” Morris said. “Upskilling can no longer be treated as an HR program or professional development perk. It’s business-critical infrastructure, part of your technology stack, not separate from it.”

Against this backdrop, there’s been a significant increase in practice-based AI learning and skills validation. According to a report from AI skills management platform Skillsoft, workers are extremely eager to demonstrate their AI proficiency as companies speed up their AI adoption.