UPDATED 14:17 EST / APRIL 25 2024

TheCUBE explores how integrating AI into data storage systems is reshaping modern infrastructure amidst economic challenges. AI

Advancing AI integration in data storage: theCUBE analysis from the ‘Future-Ready Storage’ event

As businesses grapple with the dual challenges of advancing technology and tightening budgets, the conversation around data storage is rapidly evolving.

In today’s enterprise computing ecosystem, integrating artificial intelligence into data management systems plays a critical role in enhancing efficiency and security, despite economic constraints. This shift toward smarter infrastructure is crucial for companies aiming to keep pace with growing data complexity and cybersecurity threats.

TheCUBE explores how integrating AI into data storage systems is reshaping modern infrastructure amidst economic challenges.

TheCUBE explores how integrating AI into data storage systems is reshaping modern infrastructure amidst economic challenges.

“The big trend in storage is … we’ve got to bring AI to the data,” said Dave Vellante (pictured, right), chief analyst of theCUBE Research, pointing out that modern storage solutions must be both innovative and economically viable to meet today’s industry demands.

Vellante and John Furrier (left), theCUBE Research executive analyst, kicked off today’s IBM’s “Future-Ready Storage Redefining Data Center Boundaries” event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the integration of AI into data storage systems is crucial for improving efficiency and security, particularly as economic pressures tighten IT budgets and push for more innovative, cost-effective solutions. (* Disclosure below.)

Navigating economic uncertainty: The push for efficient and scalable IT infrastructure

Organizations are facing shifting economic trends, such as rising interest rates, that impact IT spending and infrastructure decisions. Financial constraints are having immediate effects on technological advancements, according to Vellante.

“Even though you have all this AI tailwind, the reality is IT budgets are not growing,” he said. “Every time the two-year note goes up, IT budgets get tighter and tighter because CFOs are concerned about discretionary spending.”

This economic squeeze forces companies to seek out infrastructure solutions that are not only cost-effective, but also energy-efficient and capable of future-proofing their operations against disruptions. Amid these financial and technological shifts, there is also an ongoing transition from traditional storage methods to more agile and resilient systems. Companies increasingly demand a cloud-like operating model, whether on-premises or in a hybrid environment, to enhance their ability to manage data across various platforms seamlessly, Vellante added.

“What people want is that cloud-like operating model on-prem or in hybrid,” he said. “Or they want the ability to supercloud it to connect across clouds.”

The emphasis is on non-disruptive, scalable solutions that accommodate rapid changes in data management and security landscapes.

Data storage and strengthening infrastructure for AI and data security

Today’s event highlights the critical role of infrastructure in supporting the burgeoning demands of AI and data-centric operations. With AI integration becoming a staple in modern data strategies, the underlying physical and digital infrastructure must be robust enough to support complex data workflows and security measures, such as ransomware and cyberattack protection.

“If you can bring ransomware protection and detection to primary storage, then that just gives you a one-up,” Vellante said. “The adversary is so capable. They’re in, they steal, they wreak havoc and they’re out. So, to the extent that you can identify anomalies in real time or close to real time at the source of the data, that’s a big win for customers.”

As industries evolve, the requirements for storage and data management continue to be redefined. It’s necessary for storage solutions to be “rock solid, lightning fast, and dirt cheap,” Vellante added, albeit the pathways to achieving these attributes are changing with technological advancements.

The convergence of AI and data management not only enhances operational capabilities, but also imposes new challenges in designing infrastructure that can keep pace with innovation without causing disruptions, according to Furrier.

“If you look at the AI demand right now, the developer on the AI side is an all-time high, but it’s all about the data and the data has to run on the infrastructure,” he said. “So, the infrastructure matters. What’s under the hood is super important, and we look at storage and servers. This is where the action is, and this is going to be the pace car that’s going to set the agenda for the industry.”

Organizations such as IBM Corp. are addressing the challenges of modern data storage, particularly through innovations that integrate AI and provide robust infrastructure solutions. Both Furrier and Vellante emphasized that IBM is continually working on these issues in an effort to make storage infrastructure more adaptive, secure and efficient.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of IBM’s “Future-Ready Storage Redefining Data Center Boundaries” event:

(* Disclosure: TheCUBE is a paid media partner for IBM’s “Future-Ready Storage Redefining Data Center Boundaries” event. Neither IBM Corp., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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