In this episode of The Third Party Risk Institute Podcast, we tackle one of the most urgent challenges in risk management today: artificial intelligence entering your organization through third-party vendors. AI promises efficiency and insights, but behind the buzzwords lie hidden risks that can compromise compliance, trust, and resilience.

We break down the building blocks of AI data, algorithms, and infrastructure to show you where vulnerabilities really start, and how to ask the right due diligence questions before onboarding an “AI-powered” vendor. From model drift and explainability gaps to cloud concentration and fourth- and fifth-party dependencies, this episode arms you with the literacy needed to separate hype from reality.

What we cover in this episode:
• The “black box” problem in AI and why explainability is a regulatory must-have
• Key risks in data provenance, model drift, adversarial attacks, and bias amplification
• How hyperscale cloud reliance creates hidden concentration risk for enterprises
• The overlooked fourth- and fifth-party risks in AI supply chains
• Practical due diligence questions to embed in RFPs and vendor questionnaires
• How regulators from the EU AI Act to U.S. financial agencies are already shaping expectations

You’ll walk away with practical guidance on:
• Identifying red flags in vendor claims about AI
• Shifting from one-time reviews to continuous monitoring of AI vendors
• Embedding AI-specific obligations into contracts, including audit rights and incident reporting
• Building functional literacy so you can challenge vendors and protect your organization

This episode is perfect for:
• Third-Party Risk Management, Procurement, and Compliance Leaders
• CROs, CISOs, and Risk Executives navigating AI-driven vendor ecosystems
• Internal Audit, Legal, and Governance Professionals under regulatory pressure
• Anyone seeking to translate AI complexity into concrete risk oversight

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