Stu Bailey

Enterprises need AI-ready model governance to drive business value and protect the enterprise against massive regulatory and brand risks.

Getting models into production can be difficult, but that isn’t the only challenge you will face with machine learning models throughout their lifetime. Once the model has made it into production, it must be monitored in order to ensure that everything is working properly.

Digital twin technology continues to be adopted by manufacturing industries to support business strategy and gain efficiencies in operations and customer service.

Recently I had the pleasure of opening a panel discussion on “Governance and Risk Management for AI and ML Models.” The discussion centered on the challenges wrought by the rapidly growing use of artificial intelligence (AI) across their enterprises.