Connecting artificial intelligence to your business data can make employees more productive. An AI assistant may be able to locate documents, summarize email threads, review meeting notes, answer questions about projects, and find information across multiple systems in seconds.
That convenience also raises an important question: What can the AI see?
Before enabling an AI platform across your organization, review the information and permissions it may inherit. AI does not automatically correct years of oversharing, outdated access, or poorly managed files. It can make those existing problems much easier to discover.
AI Can Find Information Faster Than People Can
A traditional permissions problem may remain unnoticed for years.
An employee might technically have access to an old SharePoint site, a broadly shared cloud folder, or a document library that is no longer relevant to their role. The employee may never realize that access exists because finding the information would require knowing where to look.
AI changes that dynamic.
When an AI tool is connected to company systems, employees may be able to ask a question in plain language and receive information gathered from emails, documents, meetings, chats, and other sources they are permitted to access.
This does not necessarily mean the AI platform is bypassing security. In many cases, it is using the permissions already assigned to the employee. The real problem is that those permissions may be broader than the organization intended.
Existing Oversharing Becomes More Important
Oversharing occurs when information is accessible to more people than necessary. It can develop gradually as employees create sites, share links, change roles, join project teams, and copy files into new locations.
Common examples include:
- SharePoint sites open to everyone in the organization
- Cloud folders shared through broad or public links
- Former project members who still have access
- Documents stored in the wrong team or department
- Sensitive files without appropriate labels or restrictions
- Old accounts and security groups that were never removed
- Confidential information copied into general collaboration spaces
- External users who retain access after a project ends
These issues already present security and privacy risks. AI can increase the impact because it can search, summarize, and connect information much faster than a person browsing folders manually.
Microsoft explains that Microsoft Copilot accesses information according to a user’s existing permissions. If an employee is already authorized to access a document, Copilot may be able to use that document when responding to the employee.
That makes permission accuracy essential.
“The AI Respects Permissions” Is Only Part of the Answer
It is reassuring to hear that an AI platform respects existing access controls. But that protection is only as effective as the permissions already in place.
Consider an employee who can access salary information stored in an incorrectly shared folder. The employee may never discover the file through ordinary browsing. If a connected AI assistant can search across the employee’s authorized content, however, a general question about compensation or budgeting could make the information much easier to surface.
The AI did not create the access. It exposed an existing permissions problem.
This is why AI readiness should include more than purchasing licenses and turning on features. Businesses should first understand where sensitive data is stored, who can access it, and whether those permissions still reflect current job responsibilities.
Do Not Forget Other Cloud Systems
Microsoft 365 and SharePoint are common examples, but the same concern applies to other platforms.
Businesses may have sensitive information stored across:
- Google Drive and shared drives
- Dropbox, Box, or other cloud storage
- Customer relationship management systems
- Project management platforms
- Accounting and financial applications
- Human resources systems
- Help desk and ticketing platforms
- Internal knowledge bases
- Third-party applications connected through integrations
An AI tool may connect directly to these services, use an application integration, or rely on data copied from them by employees.
Each connection expands the information the AI may be able to retrieve or act upon. Before approving an integration, determine exactly what data it can access and whether the connection uses the individual employee’s permissions or a broader service account.
Review Permissions Before Deployment
A full data-governance project can take time, but businesses can begin with several practical steps.
Identify sensitive information
Locate financial records, personnel information, customer data, intellectual property, credentials, legal documents, regulated information, and other confidential content.
Review broadly shared locations
Look for SharePoint sites, Teams, cloud folders, and shared drives that are open to the entire organization or accessible through overly broad links.
Confirm ownership
Every important site, folder, and data repository should have a current owner responsible for approving access and reviewing its contents.
Remove unnecessary access
Review inactive accounts, former employees, outside collaborators, outdated security groups, and employees who changed roles.
Apply least privilege
Give users only the access they need to perform their responsibilities. The NIST AI Risk Management Framework provides a structured approach for identifying and managing security, privacy, and other risks associated with AI.
Review connected applications
Understand which AI tools, agents, plug-ins, and integrations can connect to company data. Confirm what permissions they request before approving them.
Test with a limited group
Begin with a controlled pilot using selected employees and approved data. Test what the AI can retrieve before expanding access across the company.
Treat Temporary Restrictions as a Starting Point
Some platforms provide controls that can temporarily limit what AI can discover while administrators review permissions. Microsoft, for example, offers SharePoint controls intended to reduce the risk of overshared content appearing in search and Copilot experiences.
These protections can be useful during deployment, but restricting AI discovery does not necessarily correct the underlying access problem. Businesses should still review and remediate the permissions themselves.
The long-term goal is not simply to hide information from AI. It is to ensure that employees, applications, and AI systems all have appropriate access.
Good AI Security Begins With Good Data Governance
AI can reveal weaknesses that already exist in your environment. Overly broad permissions, unmanaged sharing links, forgotten accounts, and disorganized cloud storage were risks before AI arrived. Connected AI tools can make those risks more visible and more consequential.
Before deployment, take inventory of your information, review access, clean up sharing, and decide which systems the AI should be allowed to use.
V2 Systems helps businesses manage the cloud environments, identities, permissions, and security controls that support modern workplace technology. Our Managed Cloud Services can help organizations improve visibility and control across their cloud systems, while our blog on shadow IT and SaaS sprawl explains why unapproved tools and unmanaged data connections create additional risk.
Before you ask what AI can do for your business, find out what it can see..
Make AI Access and Security a Priority
Before connecting AI to your business applications and data, it’s important to understand what information it can access and whether existing permissions provide the right level of protection. V2 Systems’ NEW Managed AI Services for Business can help your organization consider AI-related security risks, access controls, and data protection as you plan your AI strategy. Don’t leave your business data to chance. Contact V2 Systems to discuss how your organization can approach AI adoption more securely.
