How to safely deploy Microsoft Copilot in your enterprise

Microsoft’s AI chatbot-turned-full system integration “Copilot” is quickly becoming commonplace in many workplaces. The AI software, which rolled out in November 2023, is capable of a range of tasks, from summarising large documents to automating repetitive tasks across different applications. 

Microsoft Copilot has the potential to transform enterprise productivity by leveraging AI-driven insights and automation. However, with increased capabilities come heightened responsibilities around data security and governance.  

Before integrating Copilot into your workflows, it’s important to establish a secure, well-governed data foundation to ensure compliance, minimise risks, and maximise the platform’s potential. 

Is Microsoft Copilot safe for enterprise use?

The question many organisations are asking is: Is Microsoft Copilot safe? The answer largely depends on the measures taken to secure data before deployment.  

While Copilot is designed with built-in security features, its safety ultimately depends on how effectively enterprises manage their data ecosystems and apply robust data governance policies. Without a robust strategy in place, organisations may face Microsoft Copilot security concerns such as unauthorised data access, compliance violations, or inadvertent exposure of sensitive information. 

Enterprises must establish a secure, well-governed data environment. Implementing a comprehensive set of data governance policies and procedures with clearly defined boundaries will mitigate potential Microsoft Copilot security risks. 

The importance of a secure data ecosystem for Copilot deployment 

Deploying Copilot without securing your data can expose your organisation to unnecessary security risks. The tool’s effectiveness relies on access to high-quality, well-governed information. Without proper data classification, risk mitigation measures, and clear data governance policies, enterprises risk facing data breaches, compliance failures, and operational inefficiencies. 

Achieving this level of AI data readiness requires a system that can discover, classify, and organise both structured and unstructured data across your enterprise. A robust data governance policy can provide the framework necessary for securing and governing data in preparation for Copilot deployment. 

Key steps to protect enterprise data 

By following best practices in data governance policies and standards, enterprises can minimise security risks, ensure compliance, and enable Copilot to operate efficiently within a secure environment. 

1. Establish and enforce user permissions: Restricting access to sensitive information by setting appropriate user permissions helps mitigate potential data breaches. Only authorised personnel should have access to critical data assets.

2. Conduct regular access audits: Routine auditing of user access ensures that permissions remain up-to-date and reflect the current organisational structure. EncompaaS automates these audits, allowing enterprises to proactively address any potential vulnerabilities.

3. Manage AI outputs effectively: Monitoring AI-generated outputs is essential to prevent unintended disclosures of sensitive data. The EncompaaS platform offers AI governance tools designed to track and flag anomalies before they escalate into larger issues.

Strategies for a safe and compliant deployment 

A successful Copilot deployment requires alignment with your organisation’s broader data governance policies and standards. By embedding governance, privacy, and monitoring measures into your AI strategy, you can be sure your deployment is safe, compliant, and effective over time. 

• Align with data governance frameworks 
  Your organisation’s data governance policy should define how information is accessed, managed, and utilised. EncompaaS ensures that data governance policies are applied automatically, maintaining compliance with global regulations such as GDPR and CCPA.
   
• Anonymise sensitive data 
  Anonymisation of sensitive information, such as personally identifiable information (PII), ensures that data privacy requirements are met. EncompaaS automatically identifies and anonymises sensitive data across systems to enhance privacy and reduce risk. 
  
  
• Monitor AI-generated content 
  Ensuring the safety and integrity of AI-generated outputs is critical. The EncompaaS platform provides monitoring capabilities to detect irregularities, ensuring compliance with internal policies and regulatory requirements. 

The role of data preparation in securing Copilot deployment 

According to Gartner, more than 60 percent of AI projects fail to meet business objectives due to poor data quality and inadequate risk controls​. In this context, the question shifts from “Is Microsoft Copilot safe?” to “Is your data governance policy robust enough to support Copilot safely?” 

EncompaaS prepares enterprise data by normalising and organising it, ensuring its accuracy and relevance for AI applications. This preparation helps prevent common AI-specific issues, such as data drift, algorithmic bias, and compliance violations. 

Mitigating Microsoft Copilot security concerns with better data governance 

While Copilot comes with built-in security features, enterprises must take a proactive approach to mitigate Microsoft Copilot security concerns. Key risks include permission management gaps, where poor control over user permissions could inadvertently expose sensitive data. There is also a risk of data repurposing, where data collected for one lawful purpose could unintentionally be used for another, creating compliance issues. Bias risks arise if Copilot amplifies inherent biases in datasets or relies on outdated information, potentially leading to inaccurate or unfair outcomes.  

Mitigating these concerns requires establishing robust governance around how data is accessed, managed, and used by AI systems. 

Effective data governance encompasses a strategic framework that controls how data is accessed, managed and utilised across the organisation. This involves setting clear policies on who can access specific types of data, defining usage guidelines for AI-generated outputs, and ensuring that sensitive information is handled in compliance with relevant regulations. 

How EncompaaS enables secure and effective Copilot integration 

Successfully deploying Microsoft Copilot requires a robust approach to data security, governance, and ongoing monitoring. EncompaaS helps enterprises establish a strong foundation for AI-driven initiatives by: 

• Automatically discovering and classifying data across repositiories to reflect the sensitivity of the information 

• Applying governance policies that comply with organisation-specific requirements and international data protection standards 

• Monitoring data quality continuously to ensure consistent and reliable AI outputs 

By integrating Copilot within a framework of strong data governance policies and standards, organisations can enhance data integrity, ensure compliance, and scale their AI initiatives securely. 

Prepare for a successful Copilot deployment with EncompaaS 

For enterprises looking to deploy Microsoft Copilot securely and effectively, EncompaaS offers a trusted solution. Our data preparation platform ensures that your data is secure, compliant, and fully prepared for AI-driven initiatives, enabling you to focus on innovation with confidence. 

By embedding strong data governance policies and procedures into your deployment strategy, your organisation can mitigate Microsoft Copilot security risks while unlocking the full potential of AI.