Introduction

The traditional risk management models are built on static audits, self-reported data, and compliance checklists and are no longer sufficient to provide the real-time visibility businesses need. In a recent podcast, Patrick Neyts (CEO, VECTRA International) and Craig Moss (EVP, Ethisphere) discuss why static compliance models are failing and how AI-powered supply chain mapping, predictive analytics, and the Hourglass Approach are transforming risk management. 

Why Traditional Supply Chain Models Are Failing

For decades, businesses have managed supply chain risks using the “funnel approach” which starts with thousands of suppliers and narrows them down to a select few for deeper assessment. However, this doesn’t work anymore:

• Hidden risks – Suppliers don’t operate in silos and they form interconnected constellations that traditional models fail to capture.
• Regulatory overload – Global ESG laws (CSDDD, CSRD, SEC Climate Disclosures) aren’t just complex, they’re financially dangerous. Companies failing to comply risk hefty fines, supply chain bans, and contract losses.
• Static audits are outdated – Risk visibility remains limited when businesses rely on manual reporting and infrequent assessments.

A Smarter Model for Supply Chain Due Diligence

If businesses could combine AI with supply chain risk assessment to create a scalable, proactive risk management system, they would need an updated model. That’s where the Hourglass Approach comes in.

Step 1: AI scans all the suppliers, gathering vast amounts of risk data in real time.

Step 2: AI filters through the data, identifying high-risk suppliers and key vulnerabilities.

Step 3: Businesses conduct deeper assessments on the highest-risk suppliers.

Step 4: AI applies insights from the high-risk suppliers across the entire supply chain, creating a truly scalable risk management model.

This AI-powered model transforms supply chain due diligence from a reactive, resource-intensive process into a predictive, scalable framework. However, there’s a lot more than these steps.

How AI Is Transforming Supply Chain Risk Management

AI is a tool that goes beyond just automation. If utilized properly, AI can be a game-changer for risk management and ESG compliance.

Here are a few ways AI is making an impact:

1. AI-Powered Supply Chain Mapping

Identifies hidden supplier relationships across multiple tiers. Provides real-time monitoring of supplier risks, instead of relying on outdated self-reported data.

2. Predictive Compliance & Risk Alerts

Instead of waiting for a supplier to fail or facing a compliance lawsuit, companies get real-time risk alerts that allow them to act before it’s too late.

3. Smarter ESG Due Diligence

Automates supplier audits, making compliance smarter and more scalable. Tracks real-time compliance with global ESG regulations.

4. Personalized Supplier Communication

AI customizes ESG messaging based on supplier risk level, industry, and geography. Instead of sending generic compliance updates, AI tailors specific action points for each supplier.

The Evolution of Supply Chain Due Diligence

The landscape of supply chain risk management is shifting, and businesses that rely on outdated compliance models will struggle to keep up. AI-driven risk assessment, real-time supply chain mapping, and the hourglass approach are not just innovations but they are necessities for companies looking to navigate complex global regulations and mitigate risks effectively. 

But this is just the beginning. To gain deeper insights into how AI is revolutionizing supply chain risk management and why the Hourglass Approach is a game-changer, watch the full podcast featuring Patrick Neyts and Craig Moss. Don’t miss this opportunity to stay ahead of the curve - watch now!