A research survey from Hitachi Vantara indicates that weak data foundations are preventing organizations from getting the best return on AI investments, leading to enormous levels in wasted spending annually.
The findings reveal a structural issue rather than temporary growing pains. As AI adoption accelerates, legacy data environments are struggling to keep up with rising volumes and increasing complexity. Across North America, 84% of organizations report that their data environments are becoming too complex to manage effectively.
The report surveyed over 1,200 C-level executives and IT leaders across 15 countries, including 307 respondents in the U.S. and Canada.
The Challenge of Increasing Complexity
The growing complexity in enterprise IT directly affects security and the ability to scale AI initiatives. More than half of respondents say complex data environments make it harder to detect breaches. These risks are compounded as enterprises increase AI investment, with spending expected to rise sharply over the next two years.
The survey indicates that 57% of business and IT leaders say that complex data environments make it more difficult to identify breaches. Half of respondents state that their systems are so complex that executives would lose sleep if they fully understood the risks.
Despite these constraints, AI investment keeps climbing. Organizations expect AI spending to increase by a remarkable 76% over the next two years. This widening gap between investment and readiness is pushing many initiatives into what the report characterizes as stalled or underperforming deployments.
The survey indicates that 42% of organizations are classified as data-mature, while 58 percent fall into emerging or fragmented categories. The distinction has direct implications for AI outcomes.
Among data-mature organizations, 84% report measurable return on investment from AI. That figure drops to 48% among organizations with weaker data practices. Data quality is a primary driver of success, cited by 59% of respondents overall, rising to 75% among mature organizations compared with 47% among less mature peers.
The Role of AI
The role of AI within the business also varies sharply. Fifty-nine percent of data-mature organizations consider AI critical to operations, compared with just 18% of those with weaker data foundations. In other words, infrastructure readiness, rather than adoption itself, determines the strategic impact of AI.
Only 43% of organizations report having predictive or automated infrastructure, limiting their ability to manage complexity. Among data-mature firms, 65% have implemented automation, compared with 27 percent of less mature organizations. Similarly, 82 percent of mature organizations report resilient and sustainable infrastructure, versus just 19 percent among laggards.
Even as executives note these challenges, execution remains uneven. Ninety-six percent of organizations report needing external support for data infrastructure, yet as the survey makes clear, many have not translated that need into coordinated strategy.
