As AI is becoming more integrated with business processes, HR leaders need to assess where the boundary to stop lies.

One area that this applies to is how the tool is used to hire and fire employees.

The latest research from Orgvue, an organizational design and planning software platform, found that 39% of business leaders made employees redundant as a result of deploying AI.

Upon reflection, 55% admitted that they were wrong to do so.

In an exclusive conversation with Orgvue CEO, Oliver Shaw, UNLEASH explores what this means for the future of AI and talent retention.

Is AI being stretched too thin?

Orgvue’s research, which surveyed 1,000 global C-suite leaders and senior decision-makers, found that AI is the dominant driver of workforce transformation, with 72% of leaders expecting it to remain in poll position for the next three years.

However, the number of leaders that expect AI to replace employees in their organization has declined over the past 12 months, from 48% to 54% in 2024.

These leaders also feel less responsibility to protect their workers from redundancies (70%), with 34% sharing they’ve had employees resign as a direct result of AI.

This, the report suggests, could be due to confusion around AI, and that employees don’t have the correct skills to use the technology correctly.

In fact, 35% of leaders surveyed found AI expertise to be one of the biggest barriers to successful deployment, with 25% sharing that they’re unaware as to which roles will benefit the most from its use.

Eight in ten (80%) of leaders reported that they wanted to upskill their current workforce, to combat one of their biggest fears – employees using AI without proper controls (47%).

Additionally, over half (51%) felt that introducing policies around AI regulation would help curb this risk, with 41% having increased their L&D budgets to provide employees with the correct training.

“Our research reveals a widening deployment gap with AI and we can’t see much evidence of improved productivity. More than half of leaders who’ve let people go because of AI say they regret it, so the return on investment from AI must also be unclear,” Shaw shares exclusively with UNLEASH.

“Yet the investment is still there, which shows that organizations are committed to making it work. So, the problem is more in the execution.

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