Managing Risk From Ai Used By Third Parties
MP4 | Video: h264, 3840x2160 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.17 GB | Duration: 0h 35m
You can't manage what you can't see
What you'll learn
Evaluate the riskiness of AI within a vendor relationship context, and identify what makes AI-related third-party risk different from traditional vendor risk.
Identify the common categories and model types of AI found in vendor relationships, and explain why existing vendor inventories often fail to capture them.
Define the core components of an AI governance framework, and explain how policy, process, and procedures work together within it.
Differentiate what makes AI governance different from existing third party frameworks
Identify AI Influences along the TPRM lifecycle.
Recognize how each component of AIMED is mapped to the appropriate stage of the TPRM lifecycle
Recognize why continuous, event-driven monitoring is required for AI vendors, and identify the key signals for reassessment.
Identify how the governance framework dictates what to monitor and what to report when something surfaces, and assess where your current program stands.
Requirements
None. No prior TPRM experience required.
Description
AI is already in your vendor ecosystem, and most third-party risk programs were not built to catch it. The risk does not begin when a vendor sets out to build a model. It begins when AI quietly shows up inside tools you already use, and no one is asking the right questions.This practical, foundational course gives you the frameworks to find, assess, and monitor AI across your vendors through a third-party risk lens. You will learn to recognize where AI lives in your vendor stack, from prebuilt features to proprietary models, and why it behaves differently from the software you are used to governing. You will see how to fold AI-aware questions into the lifecycle you already run, rather than bolting on a separate process. And you will learn what to watch for after the contract is signed, when models retrain, data shifts, and scope quietly expands.It is built around AIMED, Risk Tide's framework for evaluating AI vendor risk across presence, impact, model qualification, evidence of validation, and data use. You do not need a data-science background. You need to know what to ask, when to ask it, and when to bring in the experts who go deeper.
Procurement & Vendor Management, Internal Auditors, TPRM Professionals, Legal & Privacy, Risk & Compliance, CPAs
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