Hitachi, the Japanese conglomerate that employs nearly 290,000 people worldwide, has not rolled out a single, company-wide AI tool for all its workers. This decision comes more than three-and-a-half years after OpenAI's ChatGPT first sparked widespread corporate interest in generative AI. Instead, the company is taking a different path.
Bala Krishnapillai, the senior vice president and chief information officer of Hitachi's Americas division, says the company's enterprise AI strategy is not one-size-fits-all. His comments highlight a deliberate shift away from the idea that one big AI tool can serve every employee in a massive organization.
Why Hitachi Avoids a Single Enterprise-Wide AI Tool
The cautious approach appears to be a calculated move. Research shows that a high number of enterprise AI pilots fail, and there is an intensified debate about the cost of AI. These factors have pushed most large employers, including Hitachi, to closely track workplace AI usage as expenses rise.
According to CIO, the strategy that outlasts any single model is one that does not tie the company's future to one specific AI tool. This aligns with Krishnapillai's view that a tailored approach makes more sense for a company of Hitachi's scale and diversity.
Krishnapillai notes that there are plenty of AI tools that have been widely embraced. The point is not to reject AI, but to choose tools that fit specific needs rather than forcing a single solution across the entire organization.
Enterprise AI Strategy Focuses on Practical Use
For Hitachi, the focus is on practical application. Instead of deploying one massive tool, the company appears to be letting different divisions and teams find what works best for them. This approach acknowledges that a tool useful for one part of the business may be useless for another.
According to Hitachi Vantara, AI is not new, and apart from generative AI, other technologies are creating substantial value. This broader view of AI — beyond just the latest generative models — seems to guide Hitachi's thinking.
The company's strategy also reflects a growing awareness that AI investments can go wrong. A Hitachi Vantara report found that enterprises are wasting an estimated $108 billion annually on AI because poor data infrastructure undermines their return on investment. This finding reinforces why Hitachi is being careful about how it rolls out AI tools.
What This Means for Large Employers
Hitachi's approach offers a lesson for other large organizations. The idea that one AI tool will solve every problem is appealing but often unrealistic. A more measured strategy — one that tracks usage, measures costs, and lets teams choose what works — may be more sustainable.
Krishnapillai's comments suggest that the future of enterprise AI is not about the biggest tool, but about the right tool for the right job. For a company with nearly 290,000 employees, that distinction matters.
"There are plenty of AI tools that have been widely embraced." — Bala Krishnapillai, CIO of Hitachi Americas
Our Take: A Smart, Measured Approach to AI
In our view, Hitachi's strategy is refreshingly sensible. Too many companies rush to deploy AI because it feels urgent, only to find that the tools do not fit their actual needs. The result is wasted money and frustrated employees.
Hitachi is choosing the harder path: understanding what each part of the business needs before rolling out tools. This takes more time and effort, but it is far more likely to succeed. The $108 billion waste figure from the Hitachi Vantara report shows what happens when companies ignore this reality.
For readers, the takeaway is clear. Whether you run a small team or a global company, do not assume one AI tool will fix everything. Look at your specific problems, measure what works, and be honest about costs. That is the approach Hitachi is taking — and it is one more companies should consider.
