The data risk problem hiding in plain sight

United Kingdom, Jul 15, 2026

Why many organisations still lack visibility into where sensitive data resides, who can access it and how it is being used

Authored by Mike Fry, Infrastructure, Data & Security Solutions Director, Logicalis UK&I

Improving visibility into sensitive data has become a critical business priority as organisations seek to strengthen governance, reduce risk and support AI adoption. Organisations have spent years investing in cloud platforms, SaaS applications and digital transformation initiatives, creating vast volumes of data spread across increasingly complex environments. At the same time, recent research shows that 94% of organisations are actively exploring opportunities to incorporate AI into their business.

Yet many still struggle to answer some of the most fundamental questions about their information assets:

  • Where does sensitive data reside?
  • Who can access it?
  • How is it being used?

These visibility gaps are creating growing challenges around governance, compliance and risk management. While the issue is not new, the rapid adoption of AI is exposing it in ways that can no longer be ignored.

For many organisations, the challenge is no longer collecting data. It is understanding, controlling and securing it.

Why organisations are losing sight of their data

Modern data estates look very different from those of a decade ago. Information that was once stored within a relatively controlled environment is now distributed across cloud platforms, SaaS applications, collaboration tools and hybrid working environments.

As data increasingly spans multiple jurisdictions, organisations must also contend with growing data sovereignty considerations, adding further complexity to understanding where sensitive information resides and how it should be governed.

As organisations have embraced new technologies, data has become increasingly fragmented. Sensitive information is often duplicated across multiple systems, shared between users and retained long after its original purpose has passed.

The result is that many organisations now possess more data than ever before while having less visibility into where it resides and how it is being managed.

This creates significant governance challenges. It also makes it significantly harder to identify unnecessary risk, enforce consistent policies and maintain confidence in the quality of business data. Organisations cannot effectively protect, classify or control information if they do not have a clear understanding of where it exists in the first place.

How AI is exposing long-standing weaknesses

The growth of AI is bringing these challenges into sharper focus. AI systems rely on access to high-quality, well-governed data, yet many organisations are discovering that underlying weaknesses in data management, ownership and governance are constraining their ambitions.

AI is not creating a new data problem. It is exposing one that has existed for years.

When organisations begin deploying AI across business processes, weaknesses in data quality, classification and access controls quickly become more visible. Information that was previously hidden within fragmented systems suddenly becomes part of a much larger operational and governance challenge.

This is one reason why data readiness is becoming an increasingly important part of AI readiness. Organisations cannot confidently scale AI if they lack confidence in the data underpinning it.

Why governance and regulation are increasing the pressure

Alongside AI adoption, regulatory expectations around data governance continue to evolve. The introduction of frameworks such as the EU AI Act, combined with growing scrutiny around data management and accountability, is placing greater emphasis on transparency and control. Organisations are increasingly expected to demonstrate not only that they can protect sensitive information, but also that they understand where it resides, who can access it and how it is being used.

This is particularly important as organisations deploy AI more widely. Emerging regulations place greater emphasis on governance, accountability and the ability to understand and explain how AI systems are developed and used. For many organisations, meeting these expectations starts with having a clearer understanding of the data those systems rely upon.

At the same time, boards are paying closer attention to cyber risk, compliance and operational resilience. As a result, data visibility is no longer just a technical issue for IT teams. It is becoming a strategic business concern.

Without clear visibility into sensitive information, organisations may struggle to demonstrate compliance, assess risk exposure or respond effectively to security incidents.

Moving from visibility to control

Improving visibility starts with understanding what data exists, where it resides and how it moves across the organisation.

This requires a more proactive approach to data discovery, classification and governance across cloud, SaaS and hybrid environments. Once organisations have a clearer picture of their data estate, they can establish stronger controls around access, retention and protection.

Technology plays an important role, but governance is equally important. Organisations need clear ownership, consistent policies and processes that ensure data is treated as a strategic asset rather than simply a by-product of business operations.

Building the foundation for future innovation

Ultimately, organisations that gain greater visibility and control over their data will be better positioned to reduce risk, strengthen governance and support future innovation.

AI may be accelerating the conversation, but the underlying challenge extends far beyond any single technology trend. As data volumes continue to grow and regulatory expectations evolve, organisations need confidence that they understand and can govern the information they hold.

For CIOs, the challenge is no longer simply protecting data. It is creating the visibility and control needed to use it with confidence.

Only then can organisations reduce risk, strengthen governance and unlock the full value of future AI and digital transformation investments.

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