Gartner Predicted 30% of Generative AI Projects Will Be Abandoned After Proof of Concept By End of 2025. One of the contributing factors is that new GenAI solutions often overlook the sensitivity of the data required to deliver business value, leading to significant risks and inefficiencies. This presentation will explore the critical issues that need to be addressed to avoid common pitfalls, starting with the prevention of bias that can result in faulty conclusions. We will discuss the challenges associated with unstructured and other forms of data as they are fed into Large Language Models (LLMs), emphasizing the necessity of protecting data at all stages: during inquiry (at prompt or motion) and at rest when stored in a Vector Database.
Our session will detail how Privacera AI Governance (PAIG), can be deployed as a foundational element of your GenAI stack to effectively safeguard and secure data under these various conditions.In this session we will illustrate how PAIG can be applied to solve compelling use cases involving unstructured, semi-structured, and structured data. The presentation will conclude with an inspiring healthcare use case from an early adopter of PAIG, demonstrating the tangible benefits and enhanced data security achieved through its implementation.
