Supply chain risk management is becoming more complex as companies move from linear supply chains to sprawling supply webs that include third, fourth, and fifth parties. At the same time, ethics and compliance teams are under pressure to perform deeper due diligence with limited resources.

In this episode of Ethicast, host Bill Coffin speaks with Craig Moss, Executive Vice President of Measurement at Ethisphere, about how AI data trading can help organizations close critical information gaps, improve supplier risk visibility, and create more value from the data they already have.

Craig explains why companies need to move beyond simply protecting or hoarding data, and instead think strategically about what data they can trade, what data they need, and how restricted-use legal frameworks can make those exchanges practical. He also shares a five-step pilot approach for data trading, including how to define the goal, assess data gaps, determine relative data value, prepare for negotiation, and govern the trade.

The conversation also explores the human side of AI-enabled risk management, including why problem definition, internal influence, partner negotiation, and governance still depend heavily on human judgment.

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