CXOs this year have witnessed a rollercoaster economy amid plenty of turbulent events - from ongoing inflation affecting consumer spending to large stock market swings, major overseas conflicts, and the uncertainties of an election year. Not surprisingly, the economic forecast remains murky at best. According to a CNBC CFO survey, CFOs seem to agree that inflation will remain elevated into 2026 and 54% say the economy is either in a recession or will enter one over the next year.
Corporate leaders have been managing their workforces and business strategies during times of significant upheaval in recent years, starting with the COVID-19 pandemic. The problems that have been simmering beneath the surface for years - such as unsustainable costs in key consumer sectors like healthcare - are now becoming too hard to ignore.
Yet here's the glitch: Nobody wants to be left behind in the latest wave of technological disruption. Chief officers are looking at AI with a hard eye. They want to leverage AI magic soon for both operational efficiency and competitive advantage. They know that AI will eventually require notable investment across people and technology.
If data is the fuel to power AI, IT leaders must ensure the organization's data is in the best shape possible. This requires that IT teams clean up the data mess and get control of the unstructured data that is fueling AI and ML. A looming barrier is that today's data estate incurs high costs to manage, impeding the budget for AI.
Let's discuss why this is so:
If you can get metrics on your data from the data center to the cloud, create data management policies for different data sets, and automatically move stale or cold data to lower-cost archival storage such as in the cloud, the savings can be astounding. On a 4PB NAS environment with a 30% year-over-year growth rate, your enterprise could save over $2.6 million or more annually with the right cold data tiering and/or archiving strategy alone.
Here are three ways to model potential cost savings from unstructured data management:
Unstructured data has been piling up unnoticed for years in data centers. Today, enterprises finally can classify, organize, and move it to affordable AI and ML tools where it can generate new value. But first, business leaders need to understand its costs and risks, and how to reduce both with the right data management strategy.