If you\u2019ve been following the explosion of artificial intelligence, you know that data isn\u2019t just another ingredient\u2014it\u2019s the entire kitchen. Globally, the AI industry is now worth nearly $400 billion, with experts projecting it will soar to an incredible $826 billion by the end of this decade. That kind of growth doesn\u2019t happen in a vacuum; it rides on a tidal wave of data being produced, collected, and put to work in ways that would have sounded like science fiction only a few years ago. (read more<\/a>)<\/p>\n Think about this: in just 2024 alone, organizations across the world generated around 7.2 zettabytes of data. For perspective, if each byte were a drop of water, you\u2019d fill entire oceans. And this is only the beginning. By 2027, the world\u2019s digital footprint is expected to reach a staggering 15.1 zettabytes\u2014more than double today\u2019s volume. Tech companies and IT departments everywhere are scrambling to keep up, searching for smarter, more robust ways to store and manage all of this information because data, in essence, is now their lifeblood. (read more<\/a>)<\/p>\n Yet, more data doesn\u2019t automatically mean better AI. The real secret sauce? Quality. AI systems\u2014from the ones predicting your next online purchase to those diagnosing diseases\u2014need data that\u2019s not only massive in scale, but also accurate and organized. That means cleaning up messy records, filling in gaps, and ensuring the information stays usable as needs evolve. For every bright breakthrough, there\u2019s a whole lot of invisible hard work happening behind the scenes to maintain these vast, ever-changing data reserves.<\/p>\n The pace of growth is dizzying. When OpenAI released GPT-2 in 2019, it was trained on about 3 billion words. Fast forward just four years and GPT-4 was trained on nearly 10 trillion words. That\u2019s a leap so significant you can barely compare the two. But with all this information flying around, an obvious question emerges: How do you safely and affordably store monumental stacks of data, especially when you need to access it instantly\u2014and sometimes after years of storage? (read more<\/a>)<\/p>\n Behind every AI innovation, there\u2019s an unsung hero: data storage. The way organizations save, retrieve, and secure data is fast becoming a decisive factor in who will lead the next wave of digital transformation. As more attacks and ransomware target digital systems, some companies are doubling down on classic yet highly effective solutions, like tape storage. Unlike data stored in always-online clouds, tapes can be kept offline, providing a surprisingly strong barrier against cyber threats. It gets even better: tape systems can safely hold onto petabytes of data for over 30 years and tend to be friendlier on both wallets and the environment when compared to high-powered, always-on server farms.<\/p>\n The truth is, what we\u2019re seeing isn\u2019t just a revolution in artificial intelligence\u2014it\u2019s a revolution in data itself. For organizations dreaming of making their mark with new AI technologies, the first step isn\u2019t simply creating new algorithms. It\u2019s about respecting and investing in the history they\u2019ve already written, ensuring their data is available, organized, and secure for whatever comes next.<\/p>\nIt\u2019s Not Just About Having Data\u2014Quality is King<\/h2>\n
Storage\u2014The Often-Overlooked Foundation of AI Progress<\/h2>\n