Editor’s note: This article is based on insights shared during an engaging live virtual event hosted by CIO Dive and CFO Dive on October 30. You can watch the recorded sessions here.
Enterprises have been intrigued by the potential of Generative AI to enhance efficiency and elevate customer experience through the implementation of tools like chatbots, document summarization, and digital assistants across various functions such as call centers and engineering teams.
However, scaling Generative AI at an enterprise level has proven to be more challenging than initially anticipated due to concerns surrounding AI bias, model hallucinations, and data privacy.
“Deploying generative AI carries inherent risks for any organization looking to leverage it,” noted Jaime Montemayor, Chief Digital and Technology Officer at General Mills. During a recent virtual event, Montemayor highlighted the importance of careful consideration when implementing Generative AI technologies.
General Mills, however, was well-equipped for early adoption and successfully introduced an internal Generative AI chatbot named MillsChat in