As data usage continues to explode, the digital-storage industry is racing to innovate.
Here’s a fun fact for summer beachgoers with a taste for tech: Bytes of data now well exceed grains of sand.1 Thanks to advancements in artificial intelligence (AI), demand for data storage is simply exploding—and the raw numbers are staggering to comprehend.
Data storage is measured in multiples of “bytes,” with one byte representing roughly one character of text. One kilobyte (KB), or 1,000 bytes, might hold three paragraphs, while a 1-terabyte laptop hard drive (with 1 billion KBs of capacity) can store hundreds of thousands of photos and songs, as well as numerous documents, videos and games.2
Twenty years ago, global data generation hit 1 zettabyte (ZB), the equivalent of 1 billion TBs; by 2020, as mobile devices and cloud computing became widely adopted, that figure had swelled to 72 ZBs, and is now expected to reach 181 ZBs this year.3
The AI revolution will likely accelerate data-storage demand. For example, generative-AI models like VideoGPT and Gemini Veo3 employ deep learning algorithms trained on massive datasets to analyze, extrapolate and generate new content, transforming a single photograph into a high-definition video clip at the click of a button.
This ability to remix and enhance content at scale—combined with increasingly stringent corporate data-retention regulations—is driving development of new data-storage solutions, creating potential opportunities for long-term growth investors. Fortune Business Solutions estimates that the data-storage market will grow at 17% a year, to $774 billion, between 2024 and 2032.4
Here are some key areas and market leaders we believe investors should keep an eye on:
Data Center Design
In the past, data centers used “monolithic” or “hyper-converged” systems, where computing and storage were bundled together in a single unit. This setup worked for predictable workloads but made it expensive and inflexible to expand—if more storage was needed, you often had to buy more computing power, too.
Now, the industry is moving toward a “disaggregated” architecture. In this configuration, computing resources and storage are separated and can be scaled independently, increasing flexibility to accommodate more unpredictable AI workloads. One key player, Western Digital, is collaborating with Ingrasys (a subsidiary of Foxconn Technology) to develop “fabric-attached” storage solutions that integrate directly with network interfaces, enhancing the performance of data centers built to handle AI workflows.5
Hard Disk Drives
For many years, hard disk drives (HDDs) used Perpendicular Magnetic Recording (PMR) technology to store information. (In a PMR drive, the poles of the magnetic elements that represent the data are arranged perpendicular to the disk surface, allowing the information to be stored side-by-side without overlapping.) A typical PMR-based drive can store 20 - 30 TBs of data—anything more requires larger or more expensive drives.
To overcome these limits, companies like Seagate and Western Digital are turning to Heat-Assisted Magnetic Recording (HAMR) technology. HAMR drives use a tiny laser to temporarily heat the disk surface, making it more receptive to magnetic effects and allowing data to be more densely packed; the disks, meanwhile, are made of glass substrates (primarily supplied by Japan’s Hoya, among others) which are more rigid and less susceptible to heat, increasing storage space and overall performance. Equivalent-sized HAMR drives have the potential to store 40 - 60 TBs, double the capacity of traditional PMR drives.
Memory Chips
Unlike HDDs, solid-state drives (SSDs) have no moving parts and use “flash” memory chips to store and retrieve data. SSDs tend to be smaller and faster than HDDs, often making them a better fit for AI workloads. Companies at the cutting edge of flash memory innovation, in our view, include SK Hynix, Samsung, Micron and Kioxia.
We believe innovations in data center architecture, hard drives and memory chips are fundamentally reshaping the data-storage landscape—helping organizations keep pace in the AI era and potentially generating attractive returns for well informed, long-term investors.
