As artificial intelligence becomes the hottest investment across global industries, a crucial question remains unanswered: are employees ready for it? According to the Forbes Research 2025 CxO Growth Survey, the AI boom is not a futuristic prediction — it’s already here. Ninety-three percent of global C-suite leaders reported they plan to increase AI investments over the next two years, with over half committing to budget jumps of 16% or more. From customer support to financial forecasting, AI is quickly weaving itself into every facet of business operations. But while the technology is advancing at breakneck speed, people may not be.
Tech Arrives Before the Team
It’s a familiar story in innovation cycles: shiny tools are deployed, but the people expected to use them are left playing catch-up. This time, the stakes are higher. The survey reveals that only 49% of Chief Human Resources Officers are prioritizing AI and data analysis training. Even among companies investing heavily in AI, only 57% are doing so. In the tech sector — arguably the most AI-savvy — the number drops to a worrying 38%.
These figures expose a growing disconnect: while companies are racing to automate and innovate, their workforce isn’t being equipped to keep up. That gap doesn’t just slow down adoption — it threatens to derail it.
The Hidden Cost of Not Training
This skills shortfall can result in a cascade of problems. Underutilized tools, inefficient workflows, low employee confidence, and failed implementations could all become common side effects. And the blame often falls on the technology, not the lack of training.
For many organizations, the rush to “do something with AI” overshadows the quieter, less glamorous task of teaching teams how to use it meaningfully. This gap in workforce readiness could ultimately cost more than the AI investments themselves.
From Awareness to Action
The survey also shows that AI upskilling is technically on HR’s radar — it's the second-highest talent development focus, just behind expanding data-driven employee insights. But “focus” doesn’t always translate into comprehensive training programs or cultural adaptation.
As AI systems increasingly define how decisions are made, workflows are optimized, and customer service is delivered, ensuring that humans are fluent in how these tools work — and where their limitations lie — becomes critical.
Without a parallel investment in people, companies may find their AI revolution stumbling not because the tech failed, but because they forgot to bring their workforce along for the ride.
Tech Arrives Before the Team
It’s a familiar story in innovation cycles: shiny tools are deployed, but the people expected to use them are left playing catch-up. This time, the stakes are higher. The survey reveals that only 49% of Chief Human Resources Officers are prioritizing AI and data analysis training. Even among companies investing heavily in AI, only 57% are doing so. In the tech sector — arguably the most AI-savvy — the number drops to a worrying 38%.
These figures expose a growing disconnect: while companies are racing to automate and innovate, their workforce isn’t being equipped to keep up. That gap doesn’t just slow down adoption — it threatens to derail it.
The Hidden Cost of Not Training
This skills shortfall can result in a cascade of problems. Underutilized tools, inefficient workflows, low employee confidence, and failed implementations could all become common side effects. And the blame often falls on the technology, not the lack of training.
For many organizations, the rush to “do something with AI” overshadows the quieter, less glamorous task of teaching teams how to use it meaningfully. This gap in workforce readiness could ultimately cost more than the AI investments themselves.
From Awareness to Action
The survey also shows that AI upskilling is technically on HR’s radar — it's the second-highest talent development focus, just behind expanding data-driven employee insights. But “focus” doesn’t always translate into comprehensive training programs or cultural adaptation.
As AI systems increasingly define how decisions are made, workflows are optimized, and customer service is delivered, ensuring that humans are fluent in how these tools work — and where their limitations lie — becomes critical.
Without a parallel investment in people, companies may find their AI revolution stumbling not because the tech failed, but because they forgot to bring their workforce along for the ride.
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