It’s 10 p.m. Do You Know Where Your Data Is?

A well-known public service announcement aired on American TV starting in the 1960s.

The message: It’s 10 p.m., do you know where your children are?

Today’s environment now compels enterprise CIOs to ask a similar question about their data.

Data has become one of the most important assets for a company, and as AI scales across enterprises, it’s becoming even more critical to business success. Yet data is becoming harder to manage, protect and govern as data volumes grow, regulations shift and AI raises the stakes. Only one-third of organizations have mature data governance and AI oversight in place, according to McKinsey.

Enterprise IT teams haven’t traditionally considered geopolitical concerns relative to technology decisions. But the shifting geopolitical environment, economic uncertainties, increased regulatory scrutiny, the rise of AI and mounting cybersecurity threats are changing how enterprise CIOs think about their data and what’s needed to ensure regulatory compliance.

As AI Scales Across the Enterprise, Data Matters More Than Ever

AI presents enterprises with a new opportunity to get value from their data. But there’s still a fundamental dependency on data preparation, data readiness, and data quality.

You can’t just feed any data into a large language model or use it for agentic AI. The data must be clean, structured, and well understood, or you’ll reach the wrong outcomes.

Yet only one in three emerging organizations ensures enhanced data quality for model training to establish explainable model outputs, according to our State of Data Infrastructure Global Report 2025.

Without trust, adoption stalls, outcomes are compromised, and value is lost.

Countries Across the Globe Are Establishing Sovereign Data Rules

At the same time, geopolitical events and the uncertainties they are creating are making data regulations more sovereign. A growing number of countries are establishing new data privacy and security rules that are far more nation-based than what we have seen in the past.

The EU started the trend with GDPR. But now it’s happening almost everywhere in the world as geopolitics causes countries to become far more sensitive about who has access to what data.

This puts new pressure on CIOs, who need to understand where their enterprise data lives and control how it is collected, stored, processed, transferred, and accessed. Sovereign data rules also elevate these concerns beyond IT teams and CIOs to a board-level issue.

Yet many enterprise CIOs admit that they don’t know what data they have or where it is.

That’s troubling, but it’s not entirely surprising.

Given our interconnected world and the way services are provided, data goes everywhere.

Leaders Must Understand What Rules Their Data is Subject To

Amid the move toward data sovereignty, CIOs and other enterprise leaders must take care to assess and address what existing and evolving laws and regulations their data is subject to.

Where data exists and traverses is not just a physical location, it’s a legal location.

When data flows through a network or the internet, it may move through different countries and various legal jurisdictions.

That makes decisions about whether to store data on premises or in the cloud far more critical.

Enterprises Need Data Infrastructure to Meet Requirements Today and Tomorrow

Existing IT infrastructure wasn’t built for AI. It was built for running the business and supporting customer relationship management tools, and core banking and other sector-specific platforms.

But in today’s environment:

• AI has greater workload requirements
• Complexity is mounting
• Data growth continues
• Regulations are rapidly evolving
• Reliability is non-negotiable

To gain AI advantage, meet regulatory requirements and remain competitive, enterprises must invest in AI-ready data infrastructure that is high-performance, reliable, scalable and easy to manage. Success in this environment hinges on their ability to take control of their data by classifying it, understanding what data is most critical and sensitive, determining which data is subject to which privacy laws and sovereign requirements, and acting on that understanding.

The consequences of inaction are significant. Companies can face regulatory penalties for data sovereignty violations. Also, AI initiatives using data that is not governed can produce unreliable outputs. In an environment where competitors are racing to implement AI, every delay matters. Enterprises that fail to control their data risk losing ground to competitors.

That way, they can put their data in the right place, at the right time, for the right cost.

To achieve their intended outcomes and keep their businesses growing, enterprises should also work with suppliers that deeply understand their requirements; address them across design, engineering, manufacturing and supply chain; and make their solutions easy to consume.

The Bottom Line

Most CIOs, chief data officers, chief privacy officers, chief information security officers and IT teams now understand the connection between AI-ready data infrastructure and AI outcomes.

But making that critical connection needs to be a whole-of-business concern.

In an uncertain world where AI is rapidly advancing and a growing number of countries are instituting new sovereign data rules, the most competitive enterprises are embracing AI-ready data infrastructure that is reliable, scalable, high-performance, flexible and enables compliance. Those that don’t risk being left behind permanently.