Stay informed about AI Governance, Enterprise AI, Responsible AI, and ModelOp Center
The possibilities for AI use grow almost daily, so it’s important not to limit innovation. Unfortunately, many organizations do just that by tethering themselves to proprietary tools and solutions.
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.
Modern organized enterprises recognize that the adoption of a data-driven strategy is crucial to compete in an increasingly digitalized market.
In recent years, the banking industry has been at the forefront of AI and ML adoption. A recent survey by Deloitte Insights shows 70% of all financial services firms use machine learning to manage cash flow, determine credit scores, and protect against cybercrime.
Digital twin technology continues to be adopted by manufacturing industries to support business strategy and gain efficiencies in operations and customer service.
Enterprises need AI-ready model governance to drive business value and protect the enterprise against massive regulatory and brand risks.
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