Artificial intelligence (AI) infrastructure spending has seen a significant surge in recent years, with hyperscalers, cloud service providers, and enterprises pouring billions of dollars into building out their storage and compute infrastructure to support growing AI workloads.
According to IDC, AI infrastructure investment hit $31.8 billion in the first half of 2024, exceeding $100 billion by 2028. However, reaping the full potential of AI requires more than just financial investment – it demands a robust data management strategy that can handle the increasing complexity and scale of AI workloads.
Traditional storage and data management offerings are struggling to keep up with the crushing demands of AI, with capacity being a major issue. AI models and the data needed to train them continue to grow in size, making traditional solutions inadequate.
Furthermore, AI success depends not just on access to data but also on the “richness of the data that is stored inside the system” and the ability to integrate pipelines and workflows. However, many organizations are currently juggling multiple databases, event systems, and notifications, creating expensive, complex, time-consuming, and latency-prone environments.
To address these challenges, DDN’s Data Intelligence Platform offers a unified view across an organization’s disparate collections of data, combined with a highly scalable file system optimized for high-performance, big data, and AI workloads. The platform provides a massively scalable key value store, allowing users to store metadata combined with unstructured data in the same view.
The result is clear: Multiple TB/second bandwidth systems with sub-millisecond latency, delivering a 100 times performance advance over AWS S3, according to DDN’s comparisons. On-premises solutions also offer significant benefits, including massive density and up to a 75 percent reduction in power, cooling, and datacenter footprint.
As AI technology continues to progress at breakneck pace, it is clear that data management will be the key determinant of whether organizations can realize the promise of AI. By investing in a robust data infrastructure, organizations can unlock the full potential of AI and stay ahead of the competition.
Source: https://www.nextplatform.com/2025/02/20/better-ai-might-depend-on-the-data-infrastructure-getting-better-first