<2> Scaling Agentic AI Means Trusting Your Data – Here’s What Most CDOs Are Investing In
<3> The Importance of Data Quality in Agentic AI Adoption
As the adoption of agentic AI continues to grow, organizations are facing a significant challenge: scaling their AI systems while maintaining data quality and reliability. A recent survey of chief data officers (CDOs) reveals that data quality and retrieval issues are major deployment barriers for agentic AI adopters.
<4> The Survey Results
According to the survey, half of agentic AI adopters cite data quality and retrieval issues as significant challenges in deploying their AI systems. This is a concerning trend, as data quality is a critical factor in the success of AI systems. Poor data quality can lead to biased decision-making, inaccurate predictions, and decreased system reliability.
<5> Investing in Data Quality Solutions
To address these challenges, CDOs are investing in data quality solutions that can help improve the accuracy and reliability of their data. Some of the key areas of investment include:
<6> Data Profiling and Enrichment
Data profiling and enrichment involve analyzing and improving the quality of existing data. This can include data cleansing, data standardization, and data augmentation. By investing in data