Tuesday, February 4, 2025
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According to IBM’s Jonathan Adashek, a staggering 99% of enterprise data is underutilized when it comes to AI integration. In a recent interview, Adashek highlighted a fundamental problem facing businesses today: vast amounts of data are left untapped, unable to unlock the full potential of AI-driven insights. As businesses race to adopt AI technologies, the disconnect between data availability and AI readiness is a critical issue that needs urgent attention.

Adashek points to the growing gap between the massive amounts of data collected by enterprises and their ability to apply that data effectively to AI systems. While organizations invest heavily in data storage and collection, much of that data is not structured in a way that makes it usable for AI models. The result is a vast reservoir of untapped potential that could otherwise drive smarter decision-making, improve operational efficiency, and fuel innovation.

The solution, according to Adashek, lies in better data governance and improved data quality. Businesses must take steps to ensure that their data is clean, organized, and properly labeled for AI systems to process effectively. This means not just gathering data, but curating it in a way that aligns with AI models’ needs. In other words, AI systems cannot function with just any raw data—they require a high degree of structure and organization to produce meaningful results.

IBM is positioning itself as a key player in helping companies bridge this gap. The company’s AI tools are designed to aid businesses in transforming their data into actionable insights. By focusing on creating data that is AI-ready, businesses can start to unlock the full potential of both their data and their AI capabilities.

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