Using AI to Manage Supplier Risk

In our increasingly interconnected business world, organizational supply chains have become multi-layered supply webs. As a result, the task of managing supply chain due diligence has become more important—and more challenging—than ever. But what if you could use generative AI and large language models to analyze things like program assessment data to accurately extrapolate your total universe of inherent and residual risk? Discussing this with us in this episode is Craig Moss, executive vice president of measurement at Ethisphere. Craig is also a director at the Digital Supply Chain Institute and the Cyber Readiness Institute and is on the board for the Association of Professional Social Compliance Auditors. Craig's most recent byline with the Dow Jones Risk Journal is “Using AI to Manage Supply Chain Risk.” which explains how generative AI, when applied to program maturity data and ESG assessment data, provide E&C teams with an hourglass-shaped funnel through which supplier risk suddenly becomes a whole lot more manageable. Read “Using AI to Manage Supply Chain Risk,” at www.dowjones.com FREE REPORT - AI in Ethics & Compliance: Risk to Manage, Tool to Leverage: www.ethisphere.com Chapters (00:01:36) - How program maturity assessment data can be used to find risk patterns and manage a much bigger scale of inherent and residual risk, especially within their supply chain?(00:04:41) - How a combination of quantitative data and qualitative intelligence can inform an organization's overall approach to a more holistic compliance and ESG program(00:07:05) - How generative AI and large language models can help companies manage a wide spectrum of compliance and ESG risks