As early adopter organizations are making headlines with new and exciting Generative AI capabilities, those weekly headlines remind us that GenAI solutions also carry additional risks. Understandably, many organizations are beginning to turn attention to governance and management practices that allow them to capture value quickly while also ensuring responsible use of powerful tools.
In this discussion, we’ll explore:
* Dimensions of Risk: Identify the risk factors with GenAI solutions and how they compare to traditional AI
* Intellectual Property and Observability: Navigate the complexities of public-vs-private models and training data to manage legal, ethical and data protection implications
* Redefining “Quality”: Adapt quality monitoring of input and output data to improve predictability of GenAI solutions
* Critical Participation: Recognize key voices across the organization and how their roles change
* Supporting Initiatives: Advocate for Data Governance, MLOps and other programs to support risk management