Data You Thought You Knew – The Hidden Risks Powering Your AI
Author: The Somerford Team
Release Date: 29/10/2025
AI isn’t just the next wave of enterprise tech, it’s a tsunami of change and disruption. In a matter of months, tools like Microsoft Copilot are rifling through documents to serve up insights, while customer service bots effortlessly summarise entire histories in seconds. The productivity gains feel limitless, the momentum unstoppable.
But beneath this gold rush lies a hidden fault line: most organisations have no clear picture of what data their AI is actually consuming (or who ends up seeing it once it’s surfaced).
The irony? The very intelligence designed to empower could just as easily expose. The problem isn't just theoretical.
We’ve already seen cases where employees inadvertently accessed executive compensation data via Copilot. Similar incidents are playing out quietly across industries: sensitive HR files exposed through conversational search, confidential contracts retrieved by the wrong stakeholder, health records surfacing in unintended contexts.
These moments aren’t just embarrassing, they’re compliance and security failures with potential regulatory, financial, and reputational consequences.
The Hidden Data Landscape Feeding AI
Most enterprises are swimming in a data swamp:
• ROT Data (Redundant, Obsolete, Trivial) — legacy files and versions that serve no business purpose but still sit indexed in systems.
• Dark Data — forgotten repositories, archived folders, cloud buckets with unknown contents.
• Shadow SaaS — AI-enabled tools procured by departments outside IT governance, connected to core systems without oversight.
AI doesn’t discriminate between “useful” and “toxic” data. If it has access, it consumes. That means everything from a product roadmap draft to payroll spreadsheets may sit one prompt away from exposure.
Why Traditional Security Models Break Down
Traditional enterprise security was perimeter-based: build walls, restrict entry, and trust what’s inside. But with SaaS and AI:
• Perimeters dissolve. Data flows across platforms (OneDrive, Slack, Notion, Salesforce) and into AI models that can recombine it in unexpected ways.
• Access controls are too coarse. A user entitled to one file in SharePoint may, through AI summarisation, indirectly gain access to 50 others.
• Auditability is weak. Most organisations can’t trace how a specific record made its way into an AI-generated output.
This breakdown makes it almost impossible to answer two simple, but vital, questions:
1. What exactly is my AI consuming?
2. Who has visibility into the outputs?
The False Comfort of “We Trust the Vendor”
Executives often reassure themselves: “We’re using Microsoft, Google, or OpenAI, surely they’ve thought about this.”
The reality: hyperscalers provide the tool. They don’t govern your data inputs, entitlements, or compliance posture. Consider:
• Microsoft Copilot will happily index your SharePoint—even if half its contents are outdated or non-compliant.
• OpenAI models can generate answers based on data you allow them to ingest—even if that data includes sensitive financial projections.
• Google integrates with Gmail and Drive—meaning AI can summarise sensitive deal discussions if entitlements aren’t tightly managed.
Responsibility for safe adoption sits firmly with the enterprise.
Enter the Partnership: Data Discovery + AI Governance
This is where Somerford Associates and Securiti converge to close the gap between ambition and control:
Deep Data Discovery
We are the catalyst and provide the foundation: a Data Discovery Assessment designed to uncover blind spots before AI tools amplify them.
The assessment delivers a tailored report across two categories:
• High-Level Key Findings
• Identification of sensitive and regulated data across SaaS, on-prem, and cloud environments.
• Analysis of ROT (Redundant, Obsolete, Trivial) data that clutters systems and creates unnecessary risk.
• Data classification (sensitive, confidential, regulated, public) with lineage mapping to show who has access and how it’s being used.
• Mapping of data assets to compliance and regulatory frameworks to highlight potential gaps.
• High-Level Recommendations
• Strategies for reducing exposure through data risk remediation.
• Practical approaches for ROT remediation to shrink the attack surface.
• Guidance on tagging, labelling, and organising data for greater visibility and governance.
• Other actionable steps to improve data security and regulatory alignment.
Securiti : Intelligent AI Governance
Building on this foundation, Securiti applies dynamic governance to ensure safe adoption of AI:
• ROT elimination so irrelevant files never reach the indexing stage.
• Dynamic access controls (attribute-based, role-based, contextual) that adapt in real time.
• Continuous monitoring of how AI applications are surfacing and recombining information.
• Policy guardrails applied at scale, leveraging AI itself to govern AI interactions.
Together, collaboration creates a closed loop of visibility, control, and enforcement.
Together, this approach shifts the posture from reactive to proactive: don’t wait for an incident to prove what you should have already known.
The New Playbook for AI-Era Data Security
Winning in the AI era doesn’t mean slowing down innovation. It means laying the right foundation:
• Discover before you deploy. Know what data exists, where it lives, and what sensitivity it carries.
• Reduce attack surface. Eliminate ROT and dark data that only create noise and risk.
• Govern access continuously. Move beyond static permissions to dynamic, policy-driven controls.
• Monitor AI outputs. Ensure visibility into what’s being surfaced, to whom, and why.
This playbook doesn’t stall AI, it accelerates it responsibly.
Why This Matters Now
The competitive advantage of AI is real. Organisations that hesitate risk being left behind. But those who leap without governance are building on a house of cards.
Trust is fragile. One incident, an exposed salary file, a leaked health record, can destroy stakeholder confidence and invite regulatory scrutiny.
The winners won’t just be the first to deploy AI. They’ll be the ones who deploy it safely, with security and governance baked into the core. Because when it comes to AI, it’s not just about what your systems know. It’s about the data you thought you knew and the risks hiding within it.
If you want to know more about the data AI could have access to without your knowledge, you can discover more here - What Your AI Knows (That You Don’t)!
You can also take the first step: Request a Data Discovery Assessment today. Understand what your AI already knows, and move forward with confidence.