AI Hype Hits a Wall of Messy Data, Costing Firms Billions: Hitachi Vantara Report

A new Hitachi Vantara report found that enterprises are wasting an estimated $108 billion on AI annually, as more than half of businesses fail to get a return on their investment because their underlying data infrastructure is a mess.

• A tale of two data sets: The performance gap is stark. While 84% of "data-mature" companies see measurable results from their AI initiatives, less than half of "data laggards" can say the same, according to a survey of over 1,200 IT leaders. The findings suggest the problem isn't the AI, but the quality of the data it's fed.

• Throwing good money after bad: But instead of tapping the brakes, executives plan to boost AI spending by 76% over the next two years—doubling down on a strategy that's already failing for most. The spending spree extends to the infrastructure backbone, with cloud providers also planning to pour nearly 40% more into their own capital investments this year just to keep up.

• Garbage in, garbage out: "AI is raising the bar for how organizations govern and manage their data," said Octavian Tanase, chief product officer at Hitachi Vantara. The race to adopt AI is simply exposing long-standing data management problems, with more than four in five organizations admitting their sprawling data is spiraling out of control.

The enterprise AI push is forcing a reckoning, proving that without a solid data foundation, even the most advanced technology is just an expensive experiment. Meanwhile an AI spending blitz is fueling a massive infrastructure boom for cloud providers, while experts warn that the same data complexity wasting company dollars is also creating major cybersecurity headaches for businesses adopting generative AI.