As AI shapes business decisions, making unstructured data AI-ready is a key governance priority. The quality, accessibility and security of unstructured data directly determine the performance of AI applications, particularly for GenAI. To unlock its value for AI initiatives, data and business leaders should evolve their governance strategies to effectively manage, protect and utilize unstructured data, ensuring it is AI-ready while meeting compliance and security requirements.

D&A leaders must develop DataOps as an essential practice to redefine their data management operations. This involves establishing business value before pursuing significant data engineering initiatives, and preventing duplicated efforts undertaken by different teams in managing the common metadata, security and observability of information assets within the data platforms.

Overlooked risks and unintended consequences of GenAI can disrupt operations, ethics, security and value realization. CDAOs should understand the second- and third-order effects of GenAI adoption and proactively address hidden challenges to safeguard their organizations’ competitiveness and resilience.