Rakesh Abbu Rajaram
Senior Solutions Engineer Arrow EMEA
June 26, 2026
5 Min
AI is transforming the way employees work but most of that transformation is happening outside IT's line of sight.
The problem isn't that employees are using AI. It's that they're using it without security teams knowing. Customer records, financial data, intellectual property and confidential documents are being uploaded into AI applications every day, with no visibility into where that data goes, how it is stored or who can access it. This is Shadow AI and it's creating a new category of risk that traditional security tools were never designed to handle.
At the same time, organisations face a second, equally pressing challenge: Shadow Data.
Sensitive data is no longer sitting neatly on a central file server. It's spread across Microsoft 365, cloud storage, SaaS apps, collaboration platforms and endpoints. Most organisations simply don't know where all of their sensitive data resides which makes it almost impossible to protect.
Traditional security tools were designed to protect networks and devices. They weren't built for today's cloud-first world where data constantly moves between users, applications and AI services.
Without visibility, security teams are left asking critical questions:
Without those answers, organisations are left exposed to compliance failures, insider threats and costly data breaches.
Shadow AI isn't a future problem — it's happening now.
Research shows that 78% of employees admit to using AI tools that haven't been approved by their employer.
Meanwhile, 20% of organisations have already experienced a data breach linked to Shadow AI, with those incidents costing significantly more than traditional breaches.
As AI adoption accelerates, organisations need a way to embrace innovation without losing control of their most valuable asset, their data.
The most effective approach starts with not with blocking AI, but with understanding your data.
Data Security Posture Management (DSPM) provides organisations with visibility into where sensitive data exists across cloud services, SaaS apps and endpoints. It discovers, classifies and prioritises data so security teams know exactly what needs protecting.
Once that visibility exists, Cloud Managed Data Loss Prevention (DLP) applies policies that help prevent sensitive information from being shared with unauthorised users, cloud applications or AI services, essentially putting guardrails around data that DSPM has identified as high risk.
Together they answer two fundamental questions:
By combining discovery with protection, organisations gain complete visibility and control over their data while enabling employees to use AI safely and responsibly, rather than shutting it down entirely.
Most organisations are surprised by what they discover once they begin looking for Shadow AI and Shadow Data. The good news is that you don't need a lengthy deployment or complex infrastructure project to understand your exposure.
Our complimentary AI Readiness Data Security Risk Assessment provides a personalised view of your organisation's exposure, showing you where sensitive data resides, how AI tools are being used aross your businessand where the biggest risks exist.
Your assessment includes:
Discover your Shadow AI and Shadow Data risks before they become your next security incident.
👉 Book your free Shadow AI & Data Security Assessment today.