CDAOs Focus on Data for AI Readiness to Drive Business Growth

Explore how CDAOs are mastering data to fuel AI innovation and propel business growth.

July 2025

As organizations race to integrate AI, CDAOs are at the forefront, ensuring data is not only secure and compliant but also readily usable for AI-driven innovation. This involves overcoming challenges related to diverse data types and employing advanced tools for efficient data access and management. Success hinges on user adoption, demonstrated through robust knowledge management and the growing influence of data insights within the organization.

Some key factors and considerations for CDAOs are:

• Data Security and Compliance: CDAOs must prioritize the security and compliance of both structured and unstructured data, ensuring it meets the stringent standards required for AI applications and adheres to evolving data privacy regulations.
• Enterprise Knowledge Management: Implementing consistent tagging and categorization systems is crucial for uniformly organizing data, maintaining its integrity, and enabling efficient scaling as data volumes continue to grow.
• AI and Process Integration: CDAOs need to optimize data for AI capabilities, which includes enlisting AI in core data management practices such as automated labeling and classification to enhance data visibility and utility.
• Data Catalog Adoption: CDAOs should champion the adoption of a curated data catalog to streamline data access, promote governance, and drive cost savings through platform consolidation.
• Federated Governance: Implementing a federated governance model, where business units actively participate in data curation and management, can effectively address the explosion of data and ensure that data responsibilities are distributed across the organization.