As organisations grow more confident in deploying AI—particularly in “containerised” environments where internal data isn’t exposed publicly—the hidden dangers of poor access controls are becoming harder to ignore.
While many assume that keeping AI models separate from public datasets protects sensitive content, in reality, over-permissioning within collaboration tools can create a back door to data leaks, claims ACA Group.
Modern workplaces rely heavily on platforms like SharePoint for document storage and knowledge sharing. However, the integration of AI assistants and chatbots into these systems is exposing a critical vulnerability. Over-permissioning—granting users or groups more access than they genuinely require—can allow AI to surface confidential material in response to simple queries.
This problem often stems from misconfigured permissions, overly broad group-level access such as “everyone” or “all authenticated users”, the absence of regular permission reviews, and “permission creep” over time. Sometimes, convenience takes precedence over security, with teams sharing folders or libraries too liberally.
AI compounds this risk because of how it processes data. These tools are designed to search across everything a user can access and generate context-aware responses. That means if an employee—deliberately or inadvertently—has permission to view a sensitive file, AI will consider that file as fair game.
Consider a scenario where a junior staff member asks an AI chatbot about pricing strategies for the next quarter. If they have inherited access to a confidential document detailing that plan, the AI could summarise it—unintentionally revealing sensitive competitive intelligence. This is not a malfunction but a direct consequence of the existing permissions structure.
The risk extends beyond pricing data. HR files containing salaries, legal contracts stored in broadly accessible libraries, or M&A strategy decks in shared folders could all be inadvertently exposed. If AI is integrated into these systems, it becomes a mirror reflecting every access flaw in the organisation.
Mitigation requires a disciplined approach to access control. Regular audits of document permissions, using tools like Microsoft Purview or the SharePoint Admin Center, can highlight overly broad access. Enforcing the principle of least privilege ensures staff only see what is essential for their role. For sensitive files, disabling inherited permissions and hosting them in restricted sites adds another layer of security.
Organisations can also deploy sensitivity labels and data loss prevention policies to limit AI’s ability to process classified material. Just as importantly, employee awareness is key—staff must understand both the implications of sharing documents and how AI interprets available data.
Ultimately, AI’s security is only as strong as the permissions underpinning it. By tightening controls and aligning AI use with sound governance, companies can benefit from AI’s capabilities without putting confidential data at risk.
Copyright © 2025 RegTech Analyst
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