The rapid rise of Generative AI has uncovered a wealth of previously untapped data within businesses. This presents both exciting possibilities and significant challenges for IT leaders, as many companies find it difficult to translate their AI investments into tangible business benefits.

AI's rapid growth has unleashed a flood of data within businesses, but many struggle to harness its power effectively. While AI promises significant revenue gains, companies face major hurdles, primarily stemming from poor data quality. A Hitachi Vantara survey found that nearly 37% of US companies struggle with data quality in AI projects. This is a critical issue as data volumes are predicted to skyrocket by 122% by 2026.

Despite the allure of AI success stories, many companies lack a robust data strategy. Only 38% of respondents have access to the data they need when they need it, and only one-third trust the accuracy of AI model outputs. Alarmingly, 80% of data remains unstructured, hindering AI development.

While recognizing these challenges, many companies are slow to address them. Only 37% focus on improving data quality for AI training, and nearly half don't tag data for visualization. A significant 26% don't even check datasets for quality.

Hitachi Vantara emphasizes the crucial role of data quality in AI success. Simon Ninan, SVP of Business Strategy, warns that poor initial experiences can hinder future AI capabilities. He stresses the importance of clear use cases, ROI targets, and sustainable infrastructure that can handle massive datasets efficiently.

Data security is also a major concern. 54% of respondents consider data storage security their top priority. The fear of data loss and AI-powered hacking attempts is widespread, with 74% and 73% of respondents expressing significant concerns, respectively.

In essence, the success of AI hinges on a strong foundation of data management. Companies must prioritize data quality, invest in robust infrastructure, and develop a comprehensive AI strategy to unlock the full potential of this transformative technology.