FIRESIDE CHATS ON STRATEGIC GROWTH
Join us for Episode 12 of Turbocharge Tomorrow as Cirith Anderson, SVP of Risk Management at Rivermark Community Credit Union, shares how organizations can build and deploy AI responsibly while governance, compliance, and regulation continue to catch up.
Episode #12: AI Is Moving Faster Than Your Risk Model
AI is rapidly becoming part of how products are built, decisions are made, and businesses operate. But while adoption continues to accelerate, the frameworks designed to manage risk are still evolving.
In this episode of Turbocharge Tomorrow, Cirith Anderson, SVP of Risk Management at Rivermark Community Credit Union, joins host Ethan Cole PhD, to discuss how organizations are approaching AI risk in practice. From data leakage and hallucinations to bias and automated decision-making, Cirith explores where risk emerges in AI systems and how teams can address it without slowing progress.
Episode Highlights:
In this episode, Cirith Anderson explains why traditional risk and compliance frameworks don’t always map cleanly to AI systems. As organizations adopt copilots, automation, and generative AI tools, new forms of risk are emerging that require different ways of thinking about governance and oversight.
The conversation explores some of the most common areas where AI introduces risk, including data leakage, hallucinations, biased outputs, and decision-making transparency. Cirith shares how organizations can better understand these challenges and identify where risk is most likely to appear throughout the AI lifecycle.
They also discuss how risk appetite is evolving as AI adoption accelerates. Rather than viewing compliance and risk teams as obstacles to innovation, Cirith outlines how organizations are finding ways to align engineering, data, legal, and risk stakeholders earlier in the process to reduce friction and improve outcomes.
The episode closes with a practical discussion on what “good enough” governance looks like today. While regulations continue to evolve, Cirith shares how organizations can establish clear accountability, implement sensible controls, and continue moving forward with AI without waiting for perfect rules to emerge.