Exponential data growth has led to a huge need for enterprise data storage, with major players in the data storage industry eyeing increased adoption of next-generation storage solutions, projected to be valued at over $150 billion by 2023.

Here’s where the “AI-powered hybrid-multi-super cloud” comes into play, as theCUBE industry analyst Dave Vellante put it in a May edition of his Breaking Analysis series.

“Artificial intelligence will now add superpowers to every triggering buzzword, hence the title of this week’s post,” he said. “Look past the buzz, and you’ll find substance somewhere.”

Just a few days after the May Breaking Analysis post, Tony Baer, principal at dbInsight LLC, shared his insights from IBM Corp.’s annual Think event. His overriding takeaway?

“The company showed unusual discipline by confining the focus to a couple of core themes: generative AI and hybrid cloud,” he wrote.

Given the hype around generative AI with the public preview of ChatGPT and the central role of Red Hat’s OpenShift as IBM’s platform modernization strategy, the choice of those themes was not surprising. What was unexpected was that IBM stuck quite close to the script, as a stroll through the expo area reinforced.

There’s no question that the integration of AI into hybrid cloud environments has revolutionized the way organizations leverage data and computational power. Given this new reality, it’s perhaps not too surprising to see the shift in strategy as major players in the industry actively develop solutions to better manage the flow of information through the supply chain.

Global data platforms are becoming increasingly critical and are playing a key role in supporting AI applications that are adaptable and capable of handling the vast amounts of data required.

[This feature is a part of an ongoing series, made possible by IBM, as theCUBE explores the infrastructure angle to artificial intelligence enterprise use cases.]

The future of AI and the future of data

The rise of AI has led to the need for vast amounts of data. That won’t be changing any time soon — data centers are projected to become the world’s largest energy consumers, rising from 3% of total electricity use in 2017 to 4.5% by 2025.

Some food for thought: Much of AI is also about data, which naturally leads to an examination of the future of real-time data and automation as a catalyst for massive productivity growth in the economy, as Vellante noted in an edition of his Breaking Analysis series.

“There will be a major shift in the data infrastructure landscape toward distributed, developer-controlled databases and increased automation,” he wrote. “However, there is a divergence in opinion on how much control developers will have over data management and the extent to which databases will remain an essential tool. The underlying theme is that change is inevitable, and companies will need to adapt to stay relevant.”

With that in mind, it’s worth examining how the data needs of AI are currently putting strain on traditional storage systems.

“We take it for granted, but all the tasks our machines perform are transactions between memory and processors, and each of these transactions requires energy,” said Deep Jariwala, an assistant professor in the Department of Electrical and Systems Engineering at the School of Applied Science and Engineering at the University of Pennsylvania, in a recent interview. “As these tasks become more elaborate and data-intensive, two things begin to scale up exponentially: the need for more memory storage and the need for more energy.”

In 2018, computers consumed roughly 1% to 2% of the global electricity supply, and in 2020, that figure was estimated to be around 4% to 6%, Jariwala noted. By 2030, if things continue at this rate, it’s projected to rise between 8% to 21%, which would further pose challenges amid the current energy crisis.

Given this strain on traditional storage systems, new requirements are emerging for storage to create dynamic information supply chains of data.

Global data platforms

The challenges facing customers today are clear, according to IBM, among them are adopting AI, machine learning and high-performance computing workloads and contending with hyper-data growth. With that storage realignment in mind, IBM has been looking to add new capabilities for data and AI with its Storage Scale System, which was previously known as Spectrum Scale Storage and joined together with parts from Red Hat Storage portfolio.

“The IBM Storage Scale System, with file and object interfaces, meets the full range of data and AI enterprise storage needs with massive scale and extreme performance in a scalable offering,” the company stated.

The company’s integration of its Storage Fusion container-native software with Red Hat OpenShift environments is intended to offer enterprise-grade data storage and protection services, offering customers a way to manage, recover and access mission-critical data as needed.

“To be agile, you need an efficient, secure data platform with easy access that is unified across your containerized environment,” the company said.

Dell Technologies Inc., meanwhile, has been focused on PowerStore, its intelligent all-flash storage portfolio, while Pure Storage Inc. also debuted new flash storage arrays and cybersecurity features.

“Legacy disk solutions, marked by high costs, massive data center space requirements and inefficient energy usage, are ill-equipped to support the evolving needs of today’s modern enterprises,” said Pure Storage Chief Product Officer Ajay Singh at the time.

Public and on-prem cloud

Major storage players, such as Dell, have also been working with organizations on storage scale in the public cloud, as well as on-prem. In May, Dell unveiled upgrades to its Apex as-a-service product portfolio, designed with a “ground-to-cloud” strategy in mind, offering customers a choice of workload deployment on-premises or in the public cloud.

“It’s how we help our customers really unlock that workload flexibility, be able to choose where to deploy your workloads,” said Caitlin Gordon, vice president of product management, cross-platform software and solutions, at Dell, who spoke to theCUBE in May. “Native storage services in the public cloud are great for a lot of things, but mission-critical workloads, scalable workloads are just not something that we’ve been able to solve for. Now with the APEX Block and APEX File for AWS, and Block for Azure, we can help our customers bring those workloads and unleash those workloads in the public cloud.”

In early March, IBM launched Storage Defender in partnership with data security platform provider Cohesity Inc., which in combination with IBM Storage Protect, Storage Fusion and Cohesity’s DataProtect solutions allows users to copy, store and restore data on-prem or in the cloud through a centralized interface.

“People are beginning to realize the importance that storage plays as the data custodian for the organization,” said Scott Baker, chief marketing officer and vice president of IBM infrastructure portfolio, in an April interview with theCUBE.

A reshaping of the industry

It’s obvious that the advent of AI has brought profound changes to the technology landscape, especially given the exponential surge in data.

In the months to come, as demand for sophisticated storage solutions continues to increase, industry leaders such as IBM, Dell and Pure Storage are likely to continue to release solutions geared toward better managing the flow of information through the supply chain.

For IBM, the company announced several updates during the recent Storage Summit event.

“Data is the API by which organizations will program their business in the future,” Vellante said recently. “Moreover, AI is driving unprecedented new demands on storage platforms in terms of scale, performance and always-on global access.”

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