Data management and quality are falling short when it comes to what's needed for AI adoption

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Companies don’t have a clear strategy

Racks of servers inside a data center.
(Image credit: Future)
  • Companies are set to be faced with 150% more data, large organizations will see double by 2026
  • More than half of organizations test new AI systems in real-time without sandboxing
  • Businesses should select trusted partners for hardware, software and data

New research has revealed exactly what’s stopping many UK businesses from adopting artificial intelligence, harming them by preventing them from being able to progress and keep up with rivals, and it’s not cost.

The report from Hitachi Vantara claims insufficient data management and quality standards are threatening the success of AI initiatives, with two in five (42%) UK companies identifying data quality as the top concern for successful AI adoption.

Despite acknowledging the hurdle, many organizations are failing to establish the robust data infrastructure needed for effective AI implementation.

Data is the main AI hurdle

Addressing the challenge tomorrow simply isn’t good enough, says Hitachi Vantara, which claims the volume of data businesses need to manage will increase by 150% by 2026. The average large organization globally is now said to be managing 150 petabytes of data, with this set to rise to 300 PB by 2026.

Nearly half (45%) of UK companies report significant challenges with data storage, with even more (56%) admitting that more than half their data is untapped and unanalyzed – what Hitachi Vantara is calling ‘dark data.’

Even worse is that companies’ attitudes to artificial intelligence is just as chaotic – more than half (56%) admit to testing and iterating on AI in real-time without controlled environments, which could be putting them at risk of major vulnerabilities. On the flip side, only 12% report using sandboxes.

"A lot of companies are diving into AI without a solid strategy or proper training simply to keep up, but this can backfire. Successful AI projects start with a clear plan—defined use cases, desired outcomes, and infrastructure built to handle massive data responsibly," noted Hitachi Vantara Global Business Lead for AI and High-Performance Data Platforms, Sasan Moaveni.

Looking ahead, the company calls for the development of a network of trusted partners. By bringing together reliable hardware, software, data storage and processing solutions and skilled staff, companies can tackle AI more effectively.

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Craig Hale
Craig Hale

With several years’ experience freelancing in tech and automotive circles, Craig’s specific interests lie in technology that is designed to better our lives, including AI and ML, productivity aids, and smart fitness. He is also passionate about cars and the decarbonisation of personal transportation. As an avid bargain-hunter, you can be sure that any deal Craig finds is top value!