Secure your data first before exploring AI

Protecting Your Data in the Age of AI

Data has moved beyond the traditional boundaries of business, with organizations adopting multiple cloud infrastructures, platforms, and services to run their operations. As data continues to grow everywhere, artificial intelligence (AI) is both a tremendous asset in identifying useful information that can help us work more efficiently and a potential risk. Without proper security controls and data governance, adopting AI could expose sensitive and confidential data you may not even realize existed.

If you're like many of our clients exploring AI today, our advice is the same: before jumping on the AI bandwagon, make sure your data is secure first.

The challenge of modern data security

Twenty years ago, everything was stored on a file share, allowing organizations to easily block any external access. Today, your data lives in emails, chat messages, shared storage, cloud apps, various devices, and more, making it easier to share and collaborate. However, this cross-team collaboration, remote work, and sharing of sensitive information with partners and suppliers also make it more difficult to govern, secure, and monitor where sensitive data might end up.

As a result, data security incidents can happen anytime, anywhere, if the right controls are not in place.

Most organizations lack visibility into how their documents might be at risk of misuse, nor can they track where these documents go after being shared. In some cases, employees can copy documents to a USB drive or upload them to personal cloud storage, like Dropbox or Google Drive, meaning the organization loses visibility and control of sensitive information or IP. Even with proper work practices, files shared with colleagues, clients, or suppliers can be exfiltrated or sent elsewhere by a negligent user, whether intentionally or accidentally.

We often see this scenario play out in movies, where a confidential document is maliciously leaked to the press by an external party to disrupt the market or damage a company’s reputation. But this happens in real life, too. Fortunately, organizations can set up policies to label documents as "sensitive" or "confidential," ensuring that no matter where the files go, they are protected and cannot be accessed by external users—restricting access to a specific group or individual only.

"Today, your data lives in emails, chat messages, shared storage, cloud apps, various devices, and more, making it easier to share and collaborate. However, this cross-team collaboration and sharing of sensitive information also make it more difficult to govern, secure, and monitor where sensitive data might end up."

Data protection is key to AI readiness

Being AI-ready starts with the ability to protect sensitive data wherever it travels throughout its lifecycle. Whether a document is at its starting point or endpoint doesn’t matter; what’s important is identifying risks and preventing unauthorized access across different apps, services, and devices.

Strengthening data security is now easier with Microsoft Purview—a comprehensive set of solutions that helps your organization govern, protect, and manage data no matter where it’s stored. With an integrated approach to information protection, insider risk management, and data loss prevention (DLP), Microsoft Purview helps you:

• Discover and automatically classify data, preventing unauthorized use across apps, services, and devices, including data in file shares.
• Understand user intent and context around sensitive data to identify critical risks and apply policies based on roles.
• Enable Adaptive Protection to assign the right DLP policies to high-risk users.

Support for multi-cloud, hybrid, SaaS data | Partner ecosystem

Microsoft Purview gives you powerful controls to ensure sensitivity labels are applied wherever needed.

Sensitivity labels cover your entire data landscape, representing your information taxonomy and defining the priority assigned to each category of sensitive information. You can use terms like "Public," "General," "Confidential," or "Restricted" to set protection levels for your files. These labels then follow the document and map to the policy that governs its use.

You can apply content labels manually by users or automatically based on classification in Office apps, Power BI reports, and Azure Data using encryption and visual markings for protection. Container labels can be set manually by site/Team or group owners for SharePoint sites, Teams channels, and Microsoft 365 groups, using access control, privacy settings, and conditional access.

Microsoft Purview elevates your policy and augments your investigation with rich signals, helping you to:

1. Know the context by leveraging classification and labelling of sensitive data from Information Protection.
   
   
2. Understand the intent by automatically applying risk insights from Insider Risk Management to DLP policies.
   
   
3. Integrate alert investigation by integrating DLP alerts with Microsoft 365 Defender and Sentinel for a richer investigation experience.
   
   
4. Leverage machine learning to identify the most critical insider risks among noisy signals – from correlating data signals and detecting sequences to detecting anomalies.

AI adoption demands secure and well-governed data

Have you ever saved a file somewhere because you think you might use it in the future, but five or ten years later, it’s still there sitting in folders or sites that you never opened again? Gartner calls it dark data. From a compliance regulation point of view, dark data already poses security risks. AI will increase those risks because it can look at every corner of your Microsoft Cloud tenant and every bit of your business data, thereby surfacing data you should have disposed of previously.  

AI is fast becoming a critical part of every business in solving real-world problems and driving business outcomes. However, it is only as good as the quality of your data security and governance.

At Professional Advantage, we offer end-to-end services that help our clients secure their data to adopt AI successfully – from use case development, best-fit AI solution planning, infrastructure readiness, and responsible AI planning to solution deployment and support.