DBTA Trusted AI at Scale: Modern Data Governance and Security Strategies

The "wait and see" phase of AI is over. According to recent DBTA research, 59% of organizations are actively piloting or scaling AI initiatives across the enterprise. Yet fewer than half these initiatives are succeeding for most organizations. Data quality, data access, trust, and data lineage remain major challenges, contributing to 77% of AI failures today.

To address these challenges, organizations are increasing investments in data quality, governance, and compliance to strengthen the data foundation for AI. In parallel, many are prioritizing stronger security controls and safeguards to better protect sensitive data across AI environments.

To discuss modern governance and security strategies that support trusted AI at scale, DBTA is bringing together industry experts for this special roundtable webinar.

You'll Learn How To:

• Improve data quality, trust, and lineage for AI
• Strengthen governance and compliance frameworks
• Secure sensitive data across AI environments
• Increase visibility and oversight across the AI lifecycle

Make Data Fast, Trusted, and AI-Ready

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