Control the Future of Data with AI and Information Governance

As business leaders know, great opportunity often brings great risk. Thus, big data drives strategy and informs decision making. But mismanaged data creates security and compliance nightmares. New AI tools promise to help but raise privacy and ethics concerns. However, AI and information governance together harness opportunity while minimizing risk.

For example, protected health information slides under the radar in numerous formats, from emails to meeting transcripts and chats. However, using AI-powered tools, information governance professionals can automatically find and tag sensitive data wherever it lives. This allows them to ensure compliance with privacy regulations.

On the other hand, new AI tools like ChapGPT can be used to create data that may sound convincing but prove inaccurate. Comprehensive information governance delivers visibility into data throughout the organization, including that created through AI. When data is visible, with clear data lineage, data stewards can evaluate it and take appropriate action.

Manage Data at Scale

The average company manages hundreds of terabytes of data. For that data to prove an asset rather than a liability, it must be located, classified, cleansed, and monitored. With so much data entering the organization so quickly from so many disparate sources, conducting those data tasks manually is not feasible.

Enter AI and machine learning. Tools such as Microsoft Purview use pattern matching and machine learning to classify data much more accurately and rapidly than humans can alone. With data properly classified, the organization can automate the data lifecycle, build a more defensible eDiscovery process and improve data quality.

Automation through AI also allows the organization to address policy enforcement and manage routine processes such as approvals more easily. It can even suggest necessary changes to policies and workflows to take the pain out of regulatory compliance.

Build Visibility to Ensure Trustworthy Data

For organizations to make accurate data-driven decisions, decision makers need clean, reliable data. By the same token, AI-powered analysis will only prove useful if based on complete and accurate data sets. That requires visibility into all relevant data. And it requires exhaustive checks for errors, duplicates, and outdated information.

AI tools scan internal and external data sources to create and maintain a dynamic data map automatically. And with automated monitoring, data stewards can follow that data as it moves, quickly addressing any data anomalies.

For example, marketing departments determine strategy by analyzing data from sales, website traffic and other sources. However, duplicate data from multiple departments can skew the process, resulting in faulty decisions and failed strategies. AI helps to quickly eliminate duplicates and reconcile data from multiple sources.

Secure Data Assets and Achieve Compliance

An important aspect of information governance includes data security. Privacy regulations, for example, require that organizations take all reasonable measures to keep confidential data safe from unauthorized access. This includes ensuring against inappropriate sharing and applying encryption to sensitive information.

With AI, the organization can tag critical data and then apply appropriate policies according to data type. For instance, data administrators can restrict external sharing based on data classification and user role. They might also restrict the ability to incorporate confidential data into AI algorithms.

Machine learning also boosts cyber security by learning to recognize unusual network and data activity. By alerting IT automatically of any anomalies in attempted data access, AI-enabled security systems can discover and halt potentially dangerous activity before a breach occurs.

Control the Future of Data with AI and Information Governance

AI and machine learning deliver critical capabilities to drive successful information governance. Not only does AI make processing and analyzing data possible at a large scale, but it saves time and improves accuracy by automating essential data tasks.

At the same time, advances in AI introduce challenges that demand increased vigilance. Data produced through AI can prove unpredictable, and AI-powered analysis may introduce unexpected bias.

To realize the benefits promised by AI while guarding against inaccurate or unethical results requires a careful balance between AI and information governance. The information governance experts at Messaging Architects bring the expertise to help you choose the right tools and implement them effectively.

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