Introduction

In the rapidly evolving landscape of artificial intelligence (AI), enterprise adoption of AI-powered tools like Microsoft Copilot and ChatGPT Enterprise is accelerating. These platforms promise to enhance productivity, automate workflows, and unlock new business insights. However, with this technological leap comes significant security and compliance challenges. Skyhigh Security, a leading cybersecurity firm, has introduced comprehensive solutions within its Skyhigh AI suite specifically designed to secure these AI tools for corporate use.

Background: The Rise of AI in the Enterprise

Microsoft Copilot is integrated deeply within Microsoft 365 applications, assisting users with drafting, data analysis, email automation, and more. ChatGPT Enterprise empowers companies with advanced conversational AI for customer service, knowledge management, and internal communications. According to Skyhigh Security’s 2025 Cloud Adoption and Risk Report, a startling 11% of files uploaded to AI applications contain sensitive corporate data, yet less than 10% of organizations have data protection policies tailored for AI data flows.

This rapid AI adoption outpaces security preparedness, creating vulnerabilities in data exfiltration, compliance, and data governance.

Security Challenges in AI Adoption

  1. Data Exfiltration and Ingestion: Employees may unknowingly share sensitive intellectual property (IP), personally identifiable information (PII), or regulated data via AI prompts or file uploads.
  2. Compliance Violations: AI interactions may expose organizations to non-compliance with GDPR, HIPAA, or sector-specific regulations.
  3. Data Persistence Risks: Data uploaded to AI systems may be stored or reused in ways that organizations cannot control or audit.
  4. Visibility and Control Gaps: Legacy data loss prevention (DLP) tools and policies often do not extend to AI platforms, resulting in blind spots.

Thyaga Vasudevan, EVP of Product at Skyhigh Security, highlights the dilemma: “Once sensitive data is shared with these chatbots, organizations lose control of what happens to that data.”

Skyhigh Security’s AI Protection Solutions

Skyhigh Security’s solution builds upon its Security Service Edge (SSE) platform and introduces AI-specific safeguards designed to:

1. Advanced Data Protection

  • Real-time Scanning and Classification: Every prompt, response, and file uploaded to ChatGPT Enterprise or Microsoft Copilot is scanned and classified based on sensitivity—identifying IP, PII, financial data, source code, and more.
  • Context-Aware Policy Enforcement: Administrators define granular policies controlling data uploads based on content type, user role, department, and contextual factors. For example, finance teams may upload financial models, while R&D’s product designs remain restricted.
  • Device Coverage: Protections span managed and unmanaged devices, including desktops and mobiles.

2. Threat Investigation and User Behavior Analytics

  • Forensic Analysis: Comprehensive logging and audit trails provide visibility into who accessed what data and when.
  • User and Entity Behavior Analytics (UEBA): Behavioral monitoring detects anomalous usage patterns such as shadow IT AI tools or potential insider threats.

3. Integration and Automation

  • API-Driven Controls: Leveraging Microsoft and OpenAI APIs, the solution integrates without disrupting workflow, preserving the seamless user experience.
  • Data Loss Prevention (DLP) Enhancements: Near real-time DLP policies prevent data leaks proactively, complemented by on-demand scans of existing data repositories such as SharePoint, Teams, and OneDrive.
  • User Just-In-Time Alerts: When policy violations are imminent, users receive warnings or submission blocks, increasing security awareness and reducing accidental disclosures.

Implications and Industry Impact

Skyhigh Security’s tailored approach addresses key enterprise concerns by adding a critical security layer over native platform controls. This is essential because:

  • Enterprises face a growing regulatory burden demanding transparent data governance around AI.
  • Native AI platform safeguards, while robust, currently do not meet all real-world enterprise policy complexities.
  • The blend of real-time AI-contextual controls and traditional DLP forms a unified, proactive defense strategy.

These solutions enable enterprises to confidently integrate AI without sacrificing data privacy or compliance.

Technical Details

  • Security Service Edge (SSE): Skyhigh utilizes SSE architecture to provide cloud-delivered security controls seamlessly across users and data.
  • Near Real-Time Data Loss Prevention (NRT-DLP): Immediate detection and blocking of unauthorized data transmissions.
  • On-Demand Scanning (ODS): Deep content inspection of data at rest to prevent legacy exposures.
  • API-Based Integration: Policy enforcement hooks directly into Microsoft 365 Copilot and OpenAI enterprise endpoints for prompt/response scanning.
  • User and Entity Behavior Analytics (UEBA): Machine learning models track baseline behaviors and flag deviations potentially indicating security risks.

Future Outlook

Skyhigh Security plans ongoing enhancements:

  • Incorporating AI/ML to reduce false positives in threat detection.
  • Expanding CASB API coverage to additional AI and cloud-native applications.
  • Enhancing visibility and control over high-risk user activities based on ML-derived risk scores.

Conclusion

The integration of AI tools like Microsoft Copilot and ChatGPT Enterprise offers transformative productivity benefits, but also elevates enterprise risk if left unsecured. Skyhigh Security’s purpose-built AI protection solutions provide a robust, granular, and scalable framework to secure sensitive data, enforce compliance, and investigate threats in the new AI era. Enterprises seeking to harness AI’s full potential must consider layered security strategies such as those pioneered by Skyhigh to safeguard their digital futures.

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