AI Drives Shift to Object Storage in Hybrid and Private Cloud Solutions

In recent years, the integration of artificial intelligence (AI) and machine learning (ML) into data storage has become a crucial factor for enterprises looking to optimize their infrastructure. According to a survey of over 650 IT leaders, a significant trend is the shift towards object storage, which currently houses 70% of enterprise data, with expectations of reaching 75% in the next two years. MinIO’s latest report highlights the reasons behind this preference: object storage offers superior throughput performance, immutability, and the capability to handle exascale workloads, making it an ideal fit for next-generation AI workloads.

As AI and ML workloads grow more demanding, infrastructure that supports these technologies must evolve. Both public and private cloud environments are predicted to expand their share of AI data over the next 12-24 months. However, despite the dominance of public cloud infrastructure, a considerable number of respondents, 68%, have expressed concerns about the high costs associated with running AI workloads in these environments. Consequently, a hybrid cloud approach has emerged as the most popular solution among IT leaders, balancing cost-effectiveness with performance and scalability.

While the hybrid cloud model offers numerous benefits, it also comes with its set of challenges. Security and privacy concerns, issues related to data governance, and the complexities of managing cloud-native storage systems are significant hurdles. These challenges have prompted some enterprises to migrate data from public clouds to private cloud environments, seeking better control and a higher level of security. This trend highlights the increasing importance of data portability and the need for flexible infrastructure that can adapt to changing organizational requirements.

The ongoing shift towards object storage and hybrid cloud solutions underscores the dynamic nature of enterprise IT strategies. As AI and machine learning continue to shape the demands placed on data storage, enterprises must remain agile, adopting new technologies and approaches that enhance performance while addressing cost and security concerns.

Explore more

How AI Agents Work: Types, Uses, Vendors, and Future

From Scripted Bots to Autonomous Coworkers: Why AI Agents Matter Now Everyday workflows are quietly shifting from predictable point-and-click forms into fluid conversations with software that listens, reasons, and takes action across tools without being micromanaged at every step. The momentum behind this change did not arise overnight; organizations spent years automating tasks inside rigid templates only to find that

AI Coding Agents – Review

A Surge Meets Old Lessons Executives promised dazzling efficiency and cost savings by letting AI write most of the code while humans merely supervise, but the past months told a sharper story about speed without discipline turning routine mistakes into outages, leaks, and public postmortems that no board wants to read. Enthusiasm did not vanish; it matured. The technology accelerated

Open Loop Transit Payments – Review

A Fare Without Friction Millions of riders today expect to tap a bank card or phone at a gate, glide through in under half a second, and trust that the system will sort out the best fare later without standing in line for a special card. That expectation sits at the heart of Mastercard’s enhanced open-loop transit solution, which replaces

OVHcloud Unveils 3-AZ Berlin Region for Sovereign EU Cloud

A Launch That Raised The Stakes Under the TV tower’s gaze, a new cloud region stitched across Berlin quietly went live with three availability zones spaced by dozens of kilometers, each with its own power, cooling, and networking, and it recalibrated how European institutions plan for resilience and control. The design read like a utility blueprint rather than a tech

Can the Energy Transition Keep Pace With the AI Boom?

Introduction Power bills are rising even as cleaner energy gains ground because AI’s electricity hunger is rewriting the grid’s playbook and compressing timelines once thought generous. The collision of surging digital demand, sharpened corporate strategy, and evolving policy has turned the energy transition from a marathon into a series of sprints. Data centers, crypto mines, and electrifying freight now press