AI is one of a managed service provider’s (MSPs) biggest assets and greatest responsibilities.
While AI tools like Microsoft Copilot can drive massive productivity gains, they also bring existing data security issues to the surface. That’s because AI interacts with vast volumes of structured and unstructured data—files, emails, chats, calendars—based on user access. If environments aren’t properly secured, that access can lead to unintended data exposure.
For MSPs, the challenge is clear: preparing client environments to ensure AI-powered tools only access the right data, under the right conditions. It’s not just about external cyberattacks. Weak data governance, misconfigured permissions and accidental misuse can all turn AI into a liability instead of a value driver.
Let’s break down how MSPs can get ahead of AI data risks, before Copilot is even turned on.
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How AI adoption reveals data security gaps
Traditional data protection strategies, like encryption, access control and monitoring, are essential, but they weren’t built for the scale and speed of AI-driven workflows.
When AI enters the picture, security gaps that were once hidden become visible:
- AI oversharing – Copilot can unintentionally generate content that includes sensitive information if underlying permissions aren’t tightly controlled.
- Shadow AI & unapproved tools – Employees may use AI-powered applications outside of IT’s governance, increasing data exposure risks.
- Unsecured data inputs & outputs – AI relies on clean, well-classified data, but without guardrails, it can process and output confidential content in risky ways.
- Compliance & regulatory violations – AI that interacts with PII, financials or healthcare data without security controls may trigger GDPR, HIPAA or SOC 2 violations.
A recent incident involving an AI chatbot revealed confidential client data due to improper sensitivity labeling, underscoring the importance of secure data governance before AI rollout.
Safeguarding sensitive data before AI is deployed
To help clients confidently adopt Copilot and other AI tools, MSPs must ensure data is classified, protected, and governed appropriately from day one.
1. Establish clear data classification & DLP policies
Without classification, AI doesn’t know what data is sensitive.
- Microsoft Purview enables MSPs to apply labels and access policies to sensitive information.
- Data Loss Prevention (DLP) policies prevent AI-generated content from being shared or stored in unauthorized ways.
- Encryption & conditional access help restrict how and where AI-generated insights are used or shared.
AI trained on unclassified files has been known to resurface confidential content during seemingly innocuous user queries. Classification is essential.
2. Strengthen identity and access management for AI tools
AI doesn’t make access decisions, it follows the permissions it’s given.
- Use Microsoft Entra ID to enforce phishing-resistant MFA, conditional access, and least-privilege policies.
- Implement Role-Based Access Control (RBAC) to ensure only specific users can generate AI-based insights tied to sensitive operations.
- Apply Zero Trust principles to continuously verify users and monitor AI data interactions.
The rise in identity-based attacks, including AI-powered phishing, underscores the need for airtight access governance in every AI deployment.
3. Detect internal misuse & monitor AI-generated content
Not all risks are external. Employees may misuse or mishandle AI-generated data—knowingly or not.
- Microsoft Purview Insider Risk Management detects abnormal patterns in data usage or AI content sharing.
- Enable AI activity auditing to track how Copilot-generated insights are accessed, stored, and shared.
- Apply automated content restrictions to prevent AI from outputting information beyond what users are cleared to see.
Real-world example: A team member pasting AI-generated sales data into a public chat tool may not seem like a breach, but without monitoring, it could lead to serious exposure.
4. Build an AI-ready culture of data protection
Security doesn’t stop with IT. Clients need company-wide understanding of how to work with AI securely.
- Deliver AI security training for employees using tools like Copilot.
- Configure usage policies that define approved data sources, sharing limits, and compliance requirements.
- Offer ongoing AI readiness assessments to evaluate risks and adapt policies as AI usage expands.
According to Microsoft Secure Score Report 2024, organizations that conduct proactive AI security training see 60% fewer AI-related data exposures.
Protect client data from AI-Powered threats
Make Copilot data-safe with MSP-led security strategies
Helping clients adopt AI isn’t just about enabling new tools—it’s about preparing environments to use those tools safely and responsibly.
- Secure data before Copilot is enabled, not after.
- Leverage Microsoft Purview, Entra ID and Insider Risk Management to gain full visibility and control.
- Support clients with end-to-end training, policy enforcement and automated protection.
Want to help clients adopt AI safely and confidently? Sherweb supports MSPs with tools, training and expert guidance for Copilot-ready security.
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