Sponsored Content
Organizations that manage large volumes of data are increasingly turning towards artificial intelligence-backed solutions for efficient, scalable data governance and compliance.
At the same time, many organizations still need to allocate extra resources to keep up with evolving regulatory requirements. In this guide, we’ll walk you through how to maximize AI’s potential to solve data management and compliance challenges while ensuring ease and scalability in use.
Reinvent Your Content Management Process
One of the main causes of poor governance is unstructured data — information that doesn’t follow a predefined format, including documents, videos, and images. According to a Box-sponsored IDC whitepaper, 90% of business data is unstructured.
The vast amount of information businesses generate often remains hidden in systems and is typically difficult to access and use. Managing fragmented data puts businesses at risk of compliance gaps and security breaches.
But if you move your business-critical information to an AI-powered content management platform, you can automatically classify and protect your information, reducing these security risks.
Intelligent systems provide:
- AI algorithms to automatically categorize information, extract key metadata, and transform raw information into actionable insights
- Enterprise-grade security controls, such as access permissions, encryption, and audit logging, to protect sensitive files
- Customizable retention schedules to meet regulatory and business needs
- Systematic disposition management for outdated information
For a hassle-free migration to these cloud-based solutions, choose a reliable content migration tool. Make sure this tool’s features include both on-premise and cloud connectors to support smooth integration across different environments without losing data or productivity.
AI-Driven Classification
Many organizations still manually tag confidential data, leading to inconsistent labeling and dangerous blind spots. This can be particularly risky for organizations that share data online. For example, financial services file sharing entails big risks due to the confidentiality of data in these files.
With AI-powered classification, the system automatically scans documents, images, and even audio files to detect personally identifiable information (PII), financial records, and other regulated data types.
AI models analyze content patterns, contextual relationships, and metadata to accurately classify information according to your governance policies. This approach helps reduce the risk of oversights when handling sensitive customer information or intellectual property.
For best results, start with a baseline classification scheme that aligns with your regulatory requirements, then allow the AI to learn from user corrections and feedback. This progressive learning approach improves accuracy over time while adapting to your specific business context and terminology.
Develop AI-Enhanced Risk Assessment Frameworks
Traditional risk assessments rely heavily on historical data and manually developed models. AI, on the other hand, continuously analyzes massive datasets to identify emerging risks before they become problems.
Machine learning algorithms can detect subtle patterns and correlations that human analysts might miss, particularly when dealing with complex regulatory environments.
AI can even reduce false positives by learning from previous assessments and refining its detection capabilities. This means your security team spends less time chasing phantom threats and more time addressing genuine risks.
To get started, strengthen your existing risk management framework with AI analysis tools. Focus first on high-volume, data-intensive processes where manual oversight is most challenging.
AI will supplement your team’s expertise by handling the heavy computational lifting. Doing so will free your specialists to focus on additional governance challenges that require human judgment.
The Future of Data Governance: Powered by AI
AI is steadily changing data governance by empowering businesses to stay compliant and agile without getting bogged down by manual tasks.
Instead of replacing human force, it enables teams to focus on high-value activities that require human intervention. As data continues to grow, AI will be the critical partner businesses need to thrive.
