Are you aware of the data sensitivity issues surrounding Microsoft Copilot for M365? 

Picture this: A high-stakes meeting is in progress at a thriving enterprise, where confidential business strategies and sensitive employee information are being discussed. Suddenly, an email drafted by Microsoft Copilot, our powerful AI-driven assistant, inadvertently includes snippets of this classified conversation. While the productivity enhancements offered by Copilot are compelling, this scenario highlights the critical importance of managing data security risks associated with its use. As organisations increasingly adopt AI-driven tools to enhance productivity, the introduction of Microsoft Copilot for Microsoft 365 presents both opportunities and challenges. This article explores the data sensitivity, governance, and architecture dependencies crucial to the functional running of Microsoft Copilot for M365. 

Discover the Power of Microsoft Copilot: Transforming Productivity in M365 

Copilot for Microsoft 365, is an AI-powered assistant designed to help users with various tasks, from drafting emails and documents to generating data insights and automating repetitive processes. By leveraging advanced machine learning algorithms and natural language processing, Copilot aims to enhance productivity and reduce the cognitive load on users. Microsoft work trend index report indicated a 70% increase in productivity and a 68% improvement in the quality of work since integrating Copilot into workflows. 

Underlying Technologies of Microsoft 365 Copilot 

Microsoft 365 Copilot is powered by several cutting-edge technologies: 

• Large Language Models (LLMs): These models, like ChatGPT, are trained on vast amounts of text data to understand and generate human-like text. 
• Microsoft Graph: This API connects multiple services within Microsoft 365, providing a unified view of user data and enabling Copilot to contextually understand and assist with tasks. 
• Azure AI Services: These cloud-based AI services provide the computational power and infrastructure necessary to run large-scale AI models efficiently and securely. 

By integrating these technologies, Microsoft 365 Copilot can seamlessly assist users within their familiar Microsoft 365 environment, enhancing their productivity without disrupting their workflows. 

Data Security Risks of Adopting Microsoft Copilot 

While integrating Microsoft Copilot for M365  can significantly enhance productivity, many organisations are unprepared or unaware of how to handle the associated risk it can create. The effectiveness of preventing accidental data sharing and restricting information visibility within Microsoft 365 relies heavily on how organisations configured user permissions. While Microsoft provides robust access control systems, achieving comprehensive data security and managing access controls effectively can still be challenging. Below, we delve into some of the primary risks that Microsoft Copilot for Microsoft 365 introduces. 

1. Exposure of Sensitive Data

Organisations often struggle to maintain visibility over sensitive data storage, leading to inadvertent exposure to unauthorised users. Excessive or poorly managed access permissions further increase this risk, as unnecessary access can lead to inappropriate viewing, modification, or sharing of sensitive data, especially if exploited by malicious insiders or external threat actors. 

2. Exposure of Copilot-Generated Sensitive Data

Microsoft Copilot generates content from various data sources, which can unintentionally include sensitive information. Users may not always recognise this, leading to inadvertent sharing with unauthorised parties. Additionally, Copilot-generated content may contain confidential business data or employee information, and without proper oversight and controls, this sensitive data risks exposure, potentially causing data breaches and privacy violations. 

3. Improper Use of Sensitivity Labels

Copilot-generated content often inherits sensitivity labels from referenced files, which can result in inconsistent labelling and complicate data classification efforts. If organisations do not consistently apply and enforce these labels, there’s a heightened risk of exposing sensitive information to unauthorised parties. 

Ensuring Data Security with Microsoft Copilot 

To mitigate these risks and ensure the security of sensitive data while using Microsoft Copilot, organisations should consider the following measures: 

• Implement Robust Access Controls: Ensure that access permissions are tightly managed and regularly reviewed to prevent unnecessary access to sensitive data. 
• Utilise Sensitivity Labels Effectively: Apply and enforce sensitivity labels consistently across all data and Copilot-generated content to maintain proper data classification and protection. 
• Monitor and Audit Data Access: Regularly monitor and audit data access to detect and respond to any unauthorised access or anomalies. 
• Educate Users: Train employees on the importance of data security and the potential risks associated with Copilot-generated content, emphasising the need for vigilance and proper handling of sensitive information. 

Source: 

https://www.microsoft.com/en-us/worklab/work-trend-index/copilots-earliest-users-teach-us-about-generative-ai-at-work