Data governance needs to be made ready for AI

Improving data quality (42 percent), security (40 percent), and analytics (40 percent) remain top data governance drivers, but in 2024 ensuring data readiness and quality for AI (34 percent) has made the list as the fourth most cited driver of data governance programs.

A report from Quest Software and ESG (Enterprise Strategy Group) also shows organizations report evolving data and governance to an AI-ready state (33 percent) as a top three bottleneck impacting the data value chain, behind understanding the quality of source data (38 percent) and tied with finding, identifying and harvesting data assets (33 percent).

"As AI continues to be a force multiplier of the data-driven enterprise, ensuring that your organization’s data and governance is AI-ready is now a top-level business need," says Bharath Vasudevan, VP of product management at Quest Software. "With data intelligence emerging as a key enabler of AI data readiness and operational efficiency, businesses will now have the ability to effectively position and ensure their data as a strategic growth asset rather than an accelerator of business risk."

Among other findings data marketplace adoption is up 71 percent year-on-year, with 95 percent of organizations either planning to create or already have a self-service data marketplace; 78 percent of respondents cite significant or game-changing benefits.

The report shows 84 percent of organizations are delivering data products, with 86 percent modeling their data. Of these, 71 percent view data modeling as crucial or transformative for enhancing data product delivery and fostering collaboration. Additionally, 86 percent plan to invest in data products in the next 12 to 24 months.

"Organizations are seeing the business returns of focusing time and investment in data intelligence programs when a clearly articulated data intelligence strategy is in place," says Stephen Catanzano, senior analyst at Enterprise Strategy Group. "The challenge for organizations today is to balance their attention between getting more business value from reliable data right now while at the same time laying the groundwork to reduce the risk from and accelerate value from future AI use."

You can get the full report here.

Image credit: nialowwa/depositphotos.com