Rising data complexity undermines UK AI security gains

Hitachi Vantara has published new survey findings linking rising data infrastructure complexity with weaker security and lower returns from artificial intelligence projects across UK organisations.

The company's annual State of Data Infrastructure Report draws on a poll of more than 1,200 C-level executives and IT leaders across 15 countries. The research includes responses from the UK, the US, and Canada.

In the UK, 77% of business and IT leaders said data complexity is rising too fast to manage. Respondents linked the increase to growing data volumes, more platforms and wider AI use. The survey report says the shift has implications for security, resilience and AI return on investment.

The study also points to what it calls an "AI divide" in the UK market. Hitachi Vantara said the UK leads Europe on data maturity, with 58% compared with 38% across Europe. It also said 42% of UK organisations still lack the foundations needed to realise AI value.

Security pressure

Security has emerged as a primary concern for UK respondents as AI programmes continue to expand. According to the survey, 67% of UK leaders cite data security as their top AI-related worry.

The rise of automated threats is also weighing heavily on decision-makers. Nearly half of UK respondents expressed concern that AI-enabled attacks will increase the risk of data breaches. Furthermore, Hitachi Vantara noted that 44% of UK leaders believe AI currently provides more benefits to cybercriminals than to those defending organisational networks.

In the US and Canada sample, 57% said the complexity of their data makes identifying a data breach more difficult. A further 59% said a critical data loss would be catastrophic. Half said their systems are complex enough that executives would lose sleep if they understood the risks.

"AI is raising the bar for how organizations govern and manage their data," said Octavian Tanase, Chief Product Officer, Hitachi Vantara.

Cloud choices

The findings also indicate a significant shift in infrastructure preferences for sensitive AI workloads within the UK. Hitachi Vantara reports that private cloud has emerged as the preferred option, particularly where data sensitivity and governance requirements are the primary drivers.

According to the report, 85% of UK organisations now cite data sovereignty, the requirement that data is subject to the laws of the country in which it is located, as a critical factor. Consequently, private cloud usage has climbed to 73%, while public cloud adoption for sensitive data has fallen sharply.

The survey does not quantify the scale of the decline in public cloud adoption in the UK. It frames the change as part of a wider effort among organisations to address governance and control as AI spreads into more systems and processes.

Investment gap

Hitachi Vantara also highlighted a gap between AI investment intentions and readiness. UK organisations expect AI investment to grow by almost 70% over the next two years, according to the report.

In the US and Canada, leaders expect investment in AI to grow by 76% over the next two years. The report says this trend increases pressure on data governance and security practices as organisations add new tooling and data sources.

Hitachi Vantara estimates a significant global cost for projects that fail to deliver tangible value. The report suggests that weak data foundations prevent 58% of organisations in the United States and Canada from realising the full potential of their AI investments.

This lack of "AI-readiness" is linked to an estimated USD $108 billion in wasted global AI investment annually. The research suggests that without a robust underlying architecture, a majority of capital poured into AI effectively results in "pilot purgatory", where projects never move beyond the testing phase into profitable production.

The report sets out differences between organisations it classes as data-mature and those with weaker practices. In the US and Canada, Hitachi Vantara said 42% are data-mature, defined as having managed or optimised data practices. The remaining 58% fall into defined, emerging or fragmented stages.

Hitachi Vantara said 84% of data-mature organisations report measurable AI ROI, compared with 48% of data laggards. It also said data quality is the most commonly cited driver of AI success. In the survey, 59% of organisations attributed successful AI projects to the use of high-quality data.

Among organisations with mature data practices, 59% said AI is critical to their business. That compares with 18% of organisations with weaker data foundations, according to the report.

The company says leadership and operational practices play a role in readiness. In the US and Canada, 87% of data-mature organisations reported having a strong leadership vision. In the same group, 65% reported automated infrastructure, compared with 27% among organisations with weaker data practices.

Hitachi Vantara said 96% of organisations surveyed said they need outside help with data infrastructure. It said many still struggle to translate that requirement into coordinated action.

"As AI becomes central to how every business operates, leadership has to treat data foundations as a strategic requirement, not just a technical concern," said Sheila Rohra, CEO, Hitachi Vantara.

Hitachi Vantara said UK organisations will face rising complexity and risk if they do not strengthen their data foundations as AI investment increases.