72% of HR leaders believe AI is the dominant driver of workforce transformation, Orgvue finds
39% of global leaders have made employees redundant because of AI, with 55% regretting it later, according to data from Orgvue. CEO Oliver Shaw spoke exclusively to UNLEASH to share his thoughts.
New research from Orgvue found that more than half of leaders made employees redundant because of AI, only to then regret the decision.
The businesses, which generated $52.5 million in revenue in 2024, highlights why this is a problem and what the catalyst behind it could be.
CEO Oliver Shaw spoke exclusively with UNLEASH to share his insights on the data.
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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.
Leaders need to understand the workforce impact of deploying AI in detail before they begin, and then work with the teams being affected to move proof of concept into production effectively. Holding a finger in the air based on potential cost savings is not the way to go about this.”
As Shaw mentioned, AI is expected to see continued investment growth in 2025, with 80% of those that invested in 2024 sharing that they plan to do so again.
As a result, 76% of business leaders expect that their organization will be taking full advantage of AI before the end of the year.
Concluding, he explained: “As in 2024, businesses remain confident that AI will solve their biggest business challenges and will define how they structure their organization and workforce in the future. But our research suggests this confidence could be misplaced.
“While it’s encouraging to see investment in AI continue to grow, businesses need a better understanding of how the technology will change their workforce in the coming months and years.
“Questions remain unanswered over whether AI will yield enough return on investment in the near term to justify the costs associated with lost talent and downturn in productivity.”
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