Companies worldwide are allocating an astonishing 93% of their AI budgets to technology, leaving just 7% for workforce development, according to Deloitte’s CTO. The disparity raises questions about how prepared employees are to handle rapidly advancing automation.
Deloitte’s CTO on a stunning AI transformation stat: companies are spending 93% on tech and only 7% on people – Fortune
Key Takeaways:
- Companies spend 93% of AI budgets on technology and only 7% on people
- Deloitte’s CTO highlights a potential risk to long-term AI success
- The data suggests that workforce training may be overlooked
- The piece was published in the business category, focusing on AI transformation
- Date and source context show rising concerns at the end of 2025
The Imbalance in AI Spending
Deloitte’s CTO recently brought attention to a startling number in AI transformation: businesses are channeling 93% of their resources into technology while dedicating a mere 7% to workforce development. This gap underscores a broader approach among organizations to prioritize tools and software over the people who will operate and work alongside these advanced technologies.
Why the Spending Gap Matters
Allocating the bulk of AI budgets to hardware and software can inadvertently sideline employee training. This raises the risk of skilled talent falling behind at a time when AI systems demand ever-increasing human oversight and creativity. Without effective training, the workforce may not fully grasp the potential—and the limitations—of the AI tools they use.
Industry Context
This insight, featured in the business category, reflects a broader conversation on the future of work. While AI holds immense promise for boosting efficiency, the proportionally small investment in people suggests many companies may not be addressing the skills gap that could hinder long-term AI adoption.
Looking Ahead
The significant imbalance in spending on technology versus employees has implications for how AI systems evolve. Businesses may need to rethink their approach and emphasize human input and continuous learning. By balancing investments between AI tools and workforce training, organizations can better prepare for the next wave of innovation in automation and beyond.