Despite 52% of organizations in the U.S. claiming success in operationalizing AI technology, many still struggle to prepare their data for artificial intelligence, as revealed by Snowflake’s latest research. The report, titled “The Radical ROI of Gen AI,” highlights the challenges faced by early AI adopters in integrating data, enforcing governance, and ensuring data quality.
Financial institutions are leading the way in AI adoption, with a focus on improving financial performance through cybersecurity and customer service enhancements. AI tools are being utilized to make data AI-ready, particularly in financial institutions where structured and unstructured data formats need to be considered. Generative AI technology is helping streamline processes like data scanning and governance enforcement without the need for extensive coding.
SMBs are finding that AI investments are paying off, with 92% of early adopters reporting positive ROI. By leveraging AI for tasks such as sales productivity analysis and legacy application migration, organizations are seeing significant returns on their investments.
Key goals for AI preparedness include breaking down data silos, integrating governance guardrails, measuring and monitoring data quality, preparing data for AI, and efficiently scaling storage and compute resources. These challenges are being addressed by early AI adopters through a variety of data management approaches to ensure successful AI implementation.
