On demand · Risk · AI
AI supplier risk with live customer feedback
How procurement teams use continuous supplier risk with real customer perspectives.
What this session covers
This session treats supplier risk as a continuous process rather than an annual questionnaire cycle, and pairs the product walkthrough with the perspective of the procurement teams who live with the result. It covers how due-diligence questionnaires attach to the supplier record, how AI reads the certificates and written responses that come back, and how monitoring between assessments catches certification drift before a buyer raises a purchase order against an affected supplier. The framing throughout is practical: which risk domains are worth asking about, and what has to be true for a flag to reach the person actually placing the order.
What you can do after watching
- Replace the annual risk refresh with continuous monitoring of certification status, vulnerabilities and risk-score drift, so a lapse raises an alert instead of waiting for the next review window.
- Keep risk on the same supplier master used for onboarding, contracts and spend, so a flag reaches the requisitioner at purchase-order time rather than sitting in a GRC tool procurement never opens.
- Ask industry-grouped questions across the financial, operational, legal and ESG domains instead of sending one generic form that misses the controls specific to a category.
- Let AI evaluation handle certificates, commitments and responses and track the follow-ups, so analysts review the exceptions rather than every submission.
- Judge the program on whether risk data changes a buying decision, which is the test the customer perspective in this session applies to it.
Related: supplier risk
Next step
Show us the mess.
We'll show you the record.
Thirty minutes with someone who has run procurement, using your data, framed for webinar follow-ups.
Working session, not a pitch
Bring a raw spend export or supplier list. See your own data.
Replace or orchestrate
We'll say which path fits, including when neither does yet.
No homework required
Messy files are fine. Clean-ups are the product's job.
