As artificial intelligence (AI) drives IT usage and resources, many organisations have fallen behind in their data storage capabilities.
This is among the findings from DataCore Software’s annual 2024 State of Storage Survey, conducted by independent research company, DirectResearch.
The survey, which collected insights from over 540 data professionals across the globe, uncovered key trends shaping the future of data storage and the use of artificial intelligence (AI).
“This year’s findings highlight the growing pressure on organisations to modernise their storage infrastructures in response to rapid advancements in AI and increasingly complex data management needs,” says Abhi Dey, chief product officer at DataCore. “A significant gap exists between current storage capabilities and what is needed to stay competitive.”
Data storage capability gaps and management hurdles
More than half (54%) of respondents cited that they prefer to keep the data of their organisation central in local data centers and/or decentralized across distributed facilities. In particular they cited the below concerns:
- Lack of essential storage capabilities: 90% of respondents indicated that their current storage infrastructure is missing critical features, and then went on to elaborate that the most pressing gaps being high availability (26%), sufficient storage performance (25%), and tamperproof data protection (23%). These top three concerns are followed by two further challenges which over a fifth of respondents deemed as critical. The fourth challenge is expanding storage capacity/hardware refreshes without disruption (22%); followed by intelligent storage operations that leverage AI (21%).
- Simplifying management and cost reduction: Respondents indicated that simplifying storage management was the most desired improvement (37% requesting simplified management for different types of storage), but at the same time wishing to avoid vendor lock-in to keep costs in line and competitive, with 31% desiring to have the option to lower storage costs by flexibly switching hardware suppliers as needed.
Impacts of AI usage within organisations
AI is currently being used internally by 57% of the interviewed organisations (with a far higher number of 69%, being recorded in the US). Key internal departments using AI are IT (60%); Marketing (37%) and Customer Service (30%).
Yet only 27% of total responses stated they were ‘Extremely Confident’ that their present data management and storage could handle AI workloads, with the remaining 73% citing their confidence levels on a sliding scale between ‘Moderately Confident and Not at All Confident.’
- AI usage grows amid uncertainty: More than half of respondents reported using AI within their organisations, yet nearly 73% are unsure if their infrastructure can handle AI’s current impact, let alone future impacts, as increased AI adoption is expected by 58% of respondents in the future. Many however continue to express concerns about managing AI’s future impact with only 19% citing that they were ‘Extremely Confident’ they could handle AI usage within their present infrastructure. 86% expect challenges for their storage infrastructure in supporting current and future AI workloads. Topping the list of primary future concerns about AI data are: data security (54%), data privacy (47%) and data integrity and compliance (32%).
AI capabilities within data storage management
At the same time, the audience was questioned on their intent (current and future) to deploy AI directly within their storage infrastructure, 69% of whom were interested in doing so, with AI looking to take an increasingly important role in shaping storage efficiency and performance.
Multiple drivers for implementing AI capabilities in data storage were cited: Most mentioned the automation of repetitive storage tasks (43%), intelligence storage operations (43%), more efficient space management (39%) and identifying cost saving potential (38%).
AI in storage is expected to streamline complex operations, optimise resource use, and enable organisations to tackle performance demands with greater agility and precision.