Best Practices for Generative AI Risk Management and Prevention

Executives recognize that a new paradigm is needed to mitigate AI risk but aren’t well equipped to navigate this new world of generative AI without stifling innovation. In this webinar, representatives from 451 Research (S&P Global), Robust Intelligence, and Databricks share best practices and practical lessons for managing and preventing AI risk.

Generative AI holds great promise and many enterprises are under pressure to build applications that can give them a competitive edge. However, obstacles to its widespread adoption exist today - namely a lack of confidence in the third-party large language models (LLMs) and the security, ethical, and operational risks they present.

Nick Patience, Co-founder & Managing Analyst, S&P Global Market Intelligence
Nitin Wagh, Lead ML Product Specialist, Databricks
Kojin Oshiba, Co-founder, Robust Intelligence

Best Practices for Generative AI Risk Management and Prevention

Executives recognize that a new paradigm is needed to mitigate AI risk but aren’t well equipped to navigate this new world of generative AI without stifling innovation. In this webinar, representatives from 451 Research (S&P Global), Robust Intelligence, and Databricks share best practices and practical lessons for managing and preventing AI risk.

Generative AI holds great promise and many enterprises are under pressure to build applications that can give them a competitive edge. However, obstacles to its widespread adoption exist today - namely a lack of confidence in the third-party large language models (LLMs) and the security, ethical, and operational risks they present.

Nick Patience, Co-founder & Managing Analyst, S&P Global Market Intelligence
Nitin Wagh, Lead ML Product Specialist, Databricks
Kojin Oshiba, Co-founder, Robust Intelligence