Dive Brief:
- Enterprises plan to more than double investments in AI-related data storage and processing power by the end of 2026, according to Hitachi Vantara. The data solutions provider surveyed 1,200 business executives and IT decision-makers across 15 countries in August and September 2024.
- Respondents said they expect data and compute spending to increase 224% in the next two years. AI investments will grow by roughly the same rate — 226% — over the same period, the report found.
- Data governance concerns are escalating, too. More than one-third of respondents expressed a lack of confidence in data quality. Subpar inputs led to poor results: IT leaders said AI outputs were accurate less than half of the time.
Dive Insight:
Large language model technologies cracked open massive caches of previously unprocessed enterprise data. Now, IT leaders are dealing with the fallout as their organizations look to secure returns on growing generative AI investments.
Most companies failed to achieve ROI on their AI investments last year, according to a December IBM report. Less than half of more than 2,400 IT decision-makers surveyed said their AI projects were profitable in 2024.
While immediate gains have yet to materialize, executives see light looming at the end of the AI tunnel, according to Hitachi Vantara. More than two-thirds of organizations are approaching the technology as an R&D expense, with ROI expectations up to two years away.
The scope of data challenges dictates patience.
Three-quarters of respondents to the Hitachi Vantara study said more than half of their organization’s stored data is unstructured. Over one-quarter admitted they have yet to implement comprehensive data quality review processes.
As enterprises tap into massive repositories of blog and social media posts, audio recordings and video files for training and tuning AI models, the cloud storage market is expected to double in size by 2028, according to Omdia research.
Even as companies remain cautious about overall IT spend, executives plan to greenlight AI projects, ISG analysts found.
The level of investments raises the stakes for data operations professionals and the inputs they oversee.
“The adoption of AI depends very heavily on trust of users in the system and in the output,” Simon Ninan, SVP of business strategy at Hitachi Vantara, said in the report. “If your early experiences are tainted, it taints your future capabilities.”
