The Value of Data

Data has often been called the “new oil” or “new gold.” But in today’s world of artificial intelligence (AI), those comparisons fall short.

Data is integrated into every part of our lives. It flows through our phones, streams from countless sensors around us, and hums across global servers. It grows richer with every interaction, every insight, and every fragment of experience. It creates insight and innovation not yet imagined.

Every byte is unique and holds infinite potential—a record of history, a discovery, a creative venture, or a memory—waiting for the right model and the right moment to unlock it.

In the age of AI, data is capital that compounds in value over time. The more data we save today, the more we can learn and discover, and the more significant progress we make tomorrow.

Data’s value can be realized in four ways:

1. Reusable data = limitless leverage
2. More data = better results
3. Your data = competitive advantage
4. Trusted data = trustworthy AI

Reusable Data = Limitless Leverage

Data is a powerful and inexhaustible resource that can be used, but never used up. As billions of connected devices and systems generate massive amounts of it every second, models learn from it continually, growing in intuition, understanding, and reach.

Historically, a lot of this data has been underutilized. Seagate research from 2020 showed that companies weren’t using 68% of the data available to them. Since then, as tools, technologies, and compute power have advanced, organizations are now ready to take advantage. Not using data—current or historical—is a missed opportunity to tap into your organization’s most valuable resource.

More Data = Better Results

AI needs vast amounts of data to work well. Large language models (LLMs) learn by training on high volumes of text, image, and video files. Larger, more diverse datasets increase model accuracy, particularly in unstructured domains like customer service, cybersecurity, or predictive maintenance.

Your Data = Competitive Advantage

Storing all the data that can be stored is a smart investment, but owning that data is a true economic differentiator. Proprietary datasets are irreplicable capital that build domain-specific competitive advantage. Model providers risk a degree of commoditization, while data is what drives smarter, more valuable AI—especially as agentic systems emerge.

Markets recognize this reality. Companies that treat data as a true asset—managing it well and building AI around large proprietary datasets—tend to be valued more highly by investors because the market sees their data and AI capabilities as powerful drivers of future growth.

Trusted Data = Trustworthy AI

Trusted data means trustworthy AI—and, ultimately, trustworthy organizations. Clean, ethically sourced data improves AI outcomes while reducing compliance and reputational risk.

Transparent and traceable data with clear provenance is critical to making AI models auditable and accountable. Verifiable data lineage and model explainability helps mitigate compliance and reputational risks, which are especially vital in regulated industries.

Storage: the force multiplier of data value

When data’s value as capital is understood, it is stored. And when it is stored, it can be put to work.

In the AI era, data has become heavy—denser, richer, relentless. Realizing its value requires storage infrastructure that can bear the weight and keep delivering.

Data is the AI economy’s capital. Storage is the bedrock of data value. Together, they hold the key to competitive advantage and business transformation.

Learn how mass-capacity data storage can unlock your organization’s data value in the age of AI.