Embrace Data Quality for Generative AI Success

Data leaders face unprecedented pressure to deliver generative AI use cases, with a staggering 91% actively engaged in building solutions. The success of these initiatives hinges on understanding the nuances of data quality, which may differ from traditional considerations. Companies may find themselves at varying stages in their generative AI journey; some possess a fully equipped tech stack yet lack concrete business use cases, while others identify numerous potential applications without the necessary technological foundation. Addressing these disparities is crucial for aligning generative AI efforts with tangible business outcomes.