Preparing your data security posture before deploying AI reduces the risk of exposing sensitive information and helps you adopt AI with confidence. Generative AI changes how people access and use data. Employees are using AI to find information, create content, and speed up work. Without preparation, this can lead to: - Data oversharing: Users may gain access to sensitive data via AI apps because content is not labeled correctly or access controls are too broad. - Data leakage: Users may paste or upload sensitive data into unsanctioned AI tools, or sanctioned tools that don’t inherit your data protection controls. - Noncompliant usage: AI can be used to generate content that violates ethics standards or regulations (for example, material that hides insider trading or other illegal activities). Many organizations also lack basic visibility into their data. About 30% of decision-makers say they don’t know where all their business‑critical data is, and 83% of organizations experience more than one data breach in their lifetimes. At the same time, 75% of knowledge workers are already using AI at work, and 78% are bringing their own AI tools—often without IT oversight. By focusing on data security first, you can: - Understand where sensitive data lives and who can access it. - Clean up permissions and remove obsolete or overshared content. - Apply labels and protection so AI tools respect your existing security model. - Put data loss prevention policies in place before AI-generated content starts to flow. This upfront work helps you avoid reacting out of fear (for example, blocking AI entirely, as about 48% of organizations have done) and instead move toward secure, governed AI adoption that supports innovation and compliance.

You can think of AI readiness as a structured data hygiene program. The white paper outlines four key steps to prepare your data for secure AI adoption, especially when using Copilot for Microsoft 365. 1. Know your data Start by gaining visibility into what data you have and where it lives. - Use Microsoft Purview Information Protection to discover sensitive data. - Leverage Content Explorer and Activity Explorer to see where sensitive data is stored and how it’s being used. - Classify and label sensitive data using built‑in or custom sensitive information types (SITs). - Encourage users to apply labels directly in Microsoft 365 apps as they work. Why this matters for AI: Once you know what is sensitive and where it resides, you can anticipate which data might be referenced by AI tools and ensure it is handled appropriately. 2. Govern your data Next, address compliance and access governance. - Review SharePoint sites and file permissions to identify overshared or open content. - Remediate sites and files with overly broad access. - Apply SharePoint-wide policies for content management. - Delete old or obsolete data that no longer needs to be retained. - Use Microsoft Purview machine learning classifiers to detect and mitigate risks. Why this matters for AI: Cleaning up permissions and content reduces the chance that AI will surface data to users who should not see it, and helps you avoid regulatory issues later. 3. Protect your data Then, apply protection that AI will respect. - Use Microsoft Purview Information Protection to classify, label, and protect data based on sensitivity. - Configure labels to enforce protections such as encryption, rights management, and watermarks. - Use unified labeling across Microsoft apps, services, devices, and data platforms. With Copilot, any generated response inherits the highest sensitivity label of the referenced files that the user is allowed to access. For example, content labeled “highly confidential” can be encrypted and restricted to a small group, while “general” content can be shared more broadly. Why this matters for AI: Label inheritance ensures that Copilot outputs carry forward the same protections as the underlying data, supporting end‑to‑end protection. 4. Prevent data loss Finally, put controls in place to prevent data exfiltration. - Configure Microsoft Purview Data Loss Prevention (DLP) policies to stop sensitive data from being shared inappropriately. - Apply DLP across channels such as cloud uploads, USB transfers, external sharing, on‑premises file shares, SharePoint libraries, Teams chats, and the Chrome browser. - Extend Purview capabilities to Windows 10 devices and other key endpoints. Why this matters for AI: DLP can prevent users from sending sensitive data in AI prompts and protect AI-generated content from being moved to unsanctioned locations. Taken together, these four steps—know, govern, protect, and prevent—create a foundation that allows you to adopt Copilot and other AI tools in a secure, compliant, and manageable way.

Copilot for Microsoft 365 is designed to fit into your existing Microsoft 365 security, compliance, and privacy model, which helps you adopt AI without rebuilding your controls from scratch. Here are the key reasons it is well‑suited for secure AI adoption: 1. Built on your existing Microsoft 365 security and compliance - Copilot runs on top of the Microsoft 365 platform, using the same identity, access, and compliance controls you already manage. - It only has access to content that the user is already authorized to see. - It is managed with the same tools and standards you use today for Microsoft 365. 2. Strong data protection commitments - You control your data; it is not used to train the foundational large language models behind Copilot. - Your data is encrypted. - You can control data location and residency for data at rest, including support for an EU data boundary for storing and processing. - You receive commercial data protection for web‑grounded prompts that use the latest web data. 3. Sensitivity labels and protection carry through AI - Copilot recognizes labeled and protected files. - Any Copilot response inherits the highest sensitivity label of the referenced content that the user can access. - Microsoft Purview Information Protection can apply labels automatically (autolabeling) or allow users to label content themselves. - Protections such as encryption, watermarking, and rights management can be enforced on both source data and AI outputs. 4. Integrated governance and risk management Once Copilot is deployed, Microsoft Purview helps you secure and govern its usage: - AI Hub: Gives visibility into how AI apps (including Copilot and third‑party tools) are used, where sensitive data flows, and where unlabeled or overshared content is referenced. - Data protection: Ensures Copilot responses respect user permissions and uses DLP and adaptive protection to restrict high‑risk users from pasting sensitive data into AI prompts. - Compliance tools: Audit logs Copilot interactions, manages retention and deletion of interaction content, detects noncompliant usage via communication compliance, and supports investigations through eDiscovery. 5. Flexible deployment paths - Copilot is an add‑on for Office 365 E3/E5 and Microsoft 365 E3/E5. - An optimization assessment helps you choose between a “Core” path and a “Best‑in‑class” path, depending on your current licensing, data security posture, and desired level of controls. As organizations weigh both the benefits and risks of AI, many are more willing to adopt AI when it includes assurance mechanisms for secure and compliant use. Copilot for Microsoft 365 is designed to align with that expectation by combining productivity gains with integrated security, compliance, privacy, and responsible AI capabilities.