As enterprises globally adopt artificial intelligence (AI), a recent report from Hitachi Vantara highlights challenges affecting effective AI implementation. The report finds that 58% of organisations in the United States and Canada are not fully realising AI’s potential due to weak data foundations, contributing to an estimated $108 billion in globally unutilised AI investments each year.
The study emphasises ongoing issues in data management, governance, and security that AI makes more apparent. Surveying over 1,200 C-level executives across 15 countries, including 307 from the US and Canada, the report indicates that 84% of these executives face difficulties managing increasingly complex data environments.
With AI investments expected to grow by 76% over the next two years, these challenges are likely to increase. Among US and Canadian business and IT leaders:
- 43% have predictive or automated infrastructure operations.
- 57% report that data complexity makes detecting breaches more difficult.
- Over half consider critical data loss could have significant consequences.
- 50% say their systems are complex enough that executives would be concerned if they fully understood the risks.
AI use is nearly universal, with 98% of organisations currently using, piloting, or exploring AI. A distinction appears between data-mature organisations with structured data management practices and those that have not yet established scalable data environments. Effective AI adoption depends on clear vision, leadership alignment, and data environments capable of supporting growth.
In North America, 42% of organisations are considered data-mature, with managed and optimised practices. The remaining 58% are in emerging or fragmented stages, with less structured data environments that limit AI utilisation. Differences in data maturity are reflected in AI outcomes and return on investment:
- 84% of data-mature organisations report measurable AI ROI, compared with 48% of less mature organisations.
- 59% attribute AI success to high-quality data, rising to 75% among data-mature organisations.
- 59% of mature organisations consider AI essential to business operations, compared with 18% of those with less developed data environments.
Data-mature organisations also report common practices, including strong leadership alignment and prioritisation of data and AI initiatives across the organisation rather than as isolated IT projects. 65% of data-mature firms report automated infrastructure, compared with 27% of less developed organisations, helping reduce operational complexity.
Leadership engagement remains important, with 96% recognising the need for external support in translating data infrastructure into actionable outcomes. Addressing the gap between recognising data challenges and implementing long-term strategies is a continuing focus.
Sheila Rohra, CEO of Hitachi Vantara, noted that as AI becomes central to business operations, organisations need to treat data foundations as a strategic priority. Efforts to simplify management, strengthen governance, and develop sustainable data strategies remain essential for effective AI adoption.
