While organizations aggressively pursue AI initiatives, the requirement to master their data has never been more critical. Our research revealed that a substantial majority—a combined 88%—agreed that to support diverse AI use cases, data readiness must be assessed across different departments and must support both structured and unstructured data.¹ Further, the demand for real-time data access underscores the need for robust and flexible infrastructure that can accommodate diverse data sources and AI-driven workloads. This heightened demand, coupled with widespread adoption of various data strategies to address data integration and data accessibility, is positioning the market for significant growth.

But the path to accelerate AI adoption through improved data readiness is paved with significant challenges. There are inconsistent data formats and data integration concerns—58% of organizations highlighted data integration as a key factor affecting readiness. Data quality continues to cause pain within organizations, highlighted by 68% of organizations citing that as the top factor affecting data readiness in support of AI initiatives. And there continues to be a gap in expectation vs. reality when it comes to effectively delivering access to real-time data that supports AI applications. Together, these challenges clearly indicate a push toward more agile and responsive data management strategies.

Enterprises are not just looking for technology; they’re looking for partners that provide trustworthy, scalable, and secure AI-ready data solutions. This includes robust data governance, comprehensive metadata management, and capabilities to handle ever-increasing volumes of both structured and unstructured data. Moreover, tools that empower developers to work faster and more efficiently are in high demand. Ideally, the solutions should simplify access and integration across various data sources, enhance data quality and observability, and facilitate the creation of trustworthy, transparent data pipelines. And pairing all of this with advanced AI-powered tools, intelligent automation, and user-friendly interfaces is the only way the requirements can be satisfied.

^1. Source: Enterprise Strategy Group Research Report, Data Readiness for Impactful Generative AI, April 2025. All research presented in this brief are taken from this research report.