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

Date:
Thu, 12 Dec 2024 11:07:59 +0000

Description:
Poor data foundations and a lack of sandboxing when testing is preventing businesses from benefitting from AI.

FULL STORY ======================================================================Companie s 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 whats stopping many UK businesses from adopting artificial intelligence, harming them by preventing them from being able to progress and keep up with rivals, and its 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 isnt 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 plandefined 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. You might also like Ethical AI adoption isn't a priority for new users, and that's a problem Check out our roundup of the best cloud hosting providers Weve listed the best AI writers



======================================================================
Link to news story: https://www.techradar.com/pro/data-management-and-quality-are-falling-short-wh en-it-comes-to-whats-needed-for-ai-adoption


--- Mystic BBS v1.12 A47 (Linux/64)
* Origin: tqwNet Technology News (1337:1/100)