StorageNewsletter Vendors’ Predictions 2026

As mentioned a few days ago, here are the vendors’ predictions for 2026.

StorageNewsletter recently invited vendors from across the industry to share their outlook for 2026, resulting in 54 submissions. Each participating company contributed three key predictions, all of which are presented below.

These companies are by alpha order: 9livesdata, Akave cloud, Arcitecta, Astera Labs, Backblaze, Cerabyte, Cohesity, CTERA, Databahn, Datadobi, DDN, ExaGrid, Grau Data, Hammerspace, Hitachi Vantara, HYCU, HyperBunker, Infinidat, Komprise, Leil Storage, Lightbits Labs, Lucidity, N2W, Nakivo, NetApp, Nexsan, Object First, Oxibox, Parallel Works, Peer Software, Phison, Plakar, PoINT Software & Systems, Pure Storage, QStar Technologies, Savartus, ScaleFlux, Scality, SIOS Technology, Solidigm, Starfish Storage, StorMagic, StorONE, StorPool Storage, Swissbit, Toshiba Electronics, TrueNAS, Tuxera, Vdura, Versity Software, Wasabi Technologies, Western Digital, XenData and Xinnor.

We also provide below a synthesis of this impressive vendors’ contribution and the 10 top ideas.

Here is synthesis:

1. AI agents will fundamentally change storage access patterns
   Storage systems will need to adapt from human-driven I/O to massively parallel, autonomous AI-agent behavior

2. AI-native workloads will pressure existing storage architectures
   Traditional file, block, and object systems will struggle to meet the latency, concurrency, and scale demands of AI pipelines

3. Data gravity will intensify due to AI and sovereignty requirements
   Organizations will increasingly keep data close to where it’s generated and regulated, limiting free movement across regions

4. Geopolitical data localization (“geopatriation”) will accelerate
   Regional regulations (especially in Europe and Asia) will force enterprises to redesign storage and data placement strategies

5. Storage will become policy-driven, not capacity-driven
   Decisions about where and how data is stored will be governed by compliance, sovereignty, and risk policies rather than cost alone

6. Data governance will shift from compliance to operational necessity
   Governance frameworks will be required to enable AI trust, lineage, and explainability – not just to satisfy auditors

7. Hybrid and distributed storage will become the default model
   Pure cloud or pure on-prem strategies will decline in favor of tightly integrated, location-aware hybrid environments

8. Observability and metadata will be as critical as raw storage capacity
   Understanding data context, usage, and movement will be essential for managing AI-driven workloads

9. Security models will evolve to assume continuous access by machines
   Zero-trust and identity-based access controls will need to account for non-human actors operating at scale

10. Storage vendors will reposition as data infrastructure platforms
    Vendors will move beyond selling capacity and performance to offering integrated data services for AI readiness

We provide all vendor’s inputs in a table via this pdf file available here.