Dec 23, 2025 (VMBlog) – Industry executives and experts share their predictions for 2026.  Read them in this 18th annual VMblog.com series exclusive. 

By Matt Swalley, Senior Director, VDURA

Over the past 12 months, increasingly demanding workloads (AI chief among them) have put technology infrastructure under immense pressure, with storage performance and efficiency a major part of the challenge. While the biggest international service providers are content to throw billions at the problem, for everyone else, the priority is to extract more value from existing resources through smarter storage architectures rather than ever-increasing spend.

But looking ahead to 2026, what will this look like in practice? What options are there, and how will businesses refine their storage strategies to deliver the performance levels they need without breaking the bank?

1.  AI workloads will demand balanced storage performance, not just raw speed 

At present, AI workloads apply uneven, shifting pressure across key processes, making static storage performance provisioning inefficient. As datasets and model sizes continue to grow, the cost gap between peak storage performance and average utilization becomes increasingly difficult to justify.

For instance, systems that cannot adapt their performance in real time increase the scope for delay and operational risk. Instead, organizations need sustained throughput over time more than peak benchmarks, particularly as AI environments scale.

In 2026, storage investment decisions will be determined not only by raw performance levels but also by the ability of solutions to intelligently balance workloads across flash and hybrid tiers. Why? Enterprises will expect platforms that can dynamically optimize cost while sustaining high-speed throughput, ensuring that AI models scale without bottlenecks. The winners will be those who deliver parallel performance that adapts in real time to shifting demands.

2.  2026 will see the beginning of the end for fragmented storage 

Currently, many organizations utilize fragmented storage systems and tiers, making data difficult to access and use consistently, particularly for high-performance workloads. In these environments, storage silos can also force them to manage performance, protection, and recovery separately for each system, increasing complexity and cost.

This approach increasingly determines whether data can be used at all, rather than which would deliver the most value. Teams often spend disproportionate time managing storage boundaries and data movement rather than focusing on how it is consumed by AI workflows.

However, the situation is now changing, and during 2026, enterprises will demand a single namespace across flash and capacity tiers, eliminating inefficiencies caused by siloed systems. Intelligent orchestration will automatically move data to where it’s needed most, whether for analytics, compliance or AI training, creating a seamless data fabric that accelerates innovation while reducing operational overhead.

3.  Operational simplicity will become non-negotiable 

As storage environments expand to support AI and data-intensive workloads, operational complexity increases faster than teams and processes can realistically keep up. Manual configuration and intervention do not scale cleanly, increasing the risk of misconfiguration and slower recovery. Over time, the operational overhead of managing complexity becomes a constraint in its own right, absorbing time and expertise that would otherwise be focused on delivering outcomes from data.

In the year ahead, complexity will no longer be tolerated at scale because infrastructure must deploy in hours, expand in minutes and self-optimize without manual tuning. Instead, operational simplicity will be the baseline expectation, not a differentiator. Organizations will gravitate toward platforms that abstract away complexity, enabling IT teams to focus on outcomes and proving that simplicity is the ultimate measure of resilience.

4.  Software-defined durability will unlock supercomputer-class throughput 

Next year, organizations will also try to balance storage efficiency and performance at scale by achieving breakthrough throughput on commodity hardware. These architectures will redefine durability as a software capability, enabling supercomputer-class performance without recourse to proprietary systems. This shift will prove that innovation lies not in expensive hardware, but in the intelligence of software-defined resilience and scale.

These changes will take place against a backdrop of continuing high levels of technology investment and innovation. Organizations everywhere will be looking closely at the best ways to balance performance with cost, and those who succeed will be ideally positioned to thrive in the long term.