AI governance & data intelligence pivotal for 2024

The 2024 State of Data Intelligence Report identifies AI governance as a key challenge for organizations adapting to AI demands while emphasising the critical role of data intelligence in business operations.

Quest Software, in collaboration with ESG (Enterprise Strategy Group), has released its annual report which sheds light on the challenges and advancements in data intelligence strategies across global enterprises.

The report highlights that 2024 has been a pivotal year for organisations navigating the complexities of AI integration, particularly in terms of data readiness and operational efficiency. It offers guidance and benchmarking tools to assist IT and business leaders in refining their data intelligence initiatives.

Findings indicate that AI governance remains a significant concern, with data quality, security, and analytics identified as top drivers for data governance. Ensuring AI data readiness is cited as the fourth most critical factor, marking its debut among primary governance considerations.

Data marketplace adoption has surged, with a 71% increase year-on-year. A notable 95% of organisations are either in the process of establishing or already have a self-service data marketplace. Significant business benefits were reported by 78% of respondents, indicating the strategic value of these marketplaces in addressing skill shortages and enhancing data utilisation.

The report also reveals that 84% of organisations are now delivering data products, with data modelling recognised as a foundational aspect of this delivery. According to Quest Software, 86% of these organisations view data modelling as essential for improving data product delivery and collaboration, and plan to invest in this area within the next two years.

Bharath Vasudevan, VP of Product Management at Quest Software, highlighted the importance of being AI-ready, stating, "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." He noted that data intelligence could transform data into a strategic asset rather than a source of business risk.

Furthermore, 36% more organisations reported having a clear data intelligence strategy compared to last year. Key strategic priorities include enhancing high-value data usage, improving data quality, and strengthening governance practices for AI preparedness.

Stephen Catanzano, Senior Analyst at Enterprise Strategy Group, commented on the need for a balanced approach: "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. 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."

The report underscores AI governance and metadata management as challenging aspects for businesses, with metadata management seeing a 21% rise in importance. Other significant challenges include data quality monitoring and remediation, as well as managing data policies and controls.

Bharath Vasudevan added, "The fundamentals of data intelligence such as strong metadata management, data modeling, data lineage, integrated data quality and business-supporting governance, visibility and accessibility to high-value, trusted data are non-negotiables today. They are proving to be the difference makers in succeeding in this era of greater business self-service and ensuring your data will be an asset."