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 the 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

Speaker: Robert Bagley

Robert Bagley is a Director and thought leader in Perficient's AI Practice, focused on building and growing integrated programs for long-term operational impact. His career includes senior delivery and strategy roles across multiple industries, and his personal passion is for Customer Experiences and Journey Science as a beacon for integrating data management, advanced analytics, and applied AI/ML with measured returns that align with core business goals. Robert holds a Bachelor of Science in Electrical Engineering from the Georgia Institute of Technology and currently resides in Charleston, South Carolina.