Certified: The ISACA AAIR Audio Course

In this episode, we take something that often sounds abstract and make it feel practical: vendor risk for A I systems. New learners sometimes imagine vendor risk as a checkbox activity where you confirm the vendor is reputable and then move on, but A I changes the stakes because the vendor may influence data, decisions, and outcomes in ways your organization does not fully control. If your organization buys a model, uses an A I feature inside another product, or relies on a third-party service to process information, you are inheriting that vendor’s choices, weaknesses, and blind spots. The goal here is not to make you suspicious of every vendor, but to help you understand what questions matter and why they matter before you commit. We will connect three practical ideas: due diligence, the contract, and ongoing oversight, because treating vendor risk as a one-time review is one of the fastest ways to end up with unexpected exposure. By the end, you should be able to explain how organizations turn vendor promises into real controls and how they keep those controls working over time.

Before we continue, a quick note: this audio course is a companion to our course companion books. The first book is about the exam and provides detailed information on how to pass it best. The second book is a Kindle-only eBook that contains 1,000 flashcards that can be used on your mobile device or Kindle. Check them both out at Cyber Author dot me, in the Bare Metal Study Guides Series.

To make vendor risk feel real, start by recognizing what a vendor relationship actually is in the A I context. It is not just buying software; it can be outsourcing parts of decision-making, outsourcing data processing, or outsourcing model behavior you cannot fully predict. A vendor might host the model, provide the training data, manage the updates, or supply the interface your users interact with, and each of those roles creates different risks. Beginners often think the vendor is responsible for whatever the model does, but in practice your organization is the one facing customers, regulators, and reputational damage if things go wrong. Vendor risk is the mismatch between how much impact the vendor has and how little visibility you have into their decisions. When that mismatch is large, you need stronger controls, clearer terms, and better monitoring. If you do not close the mismatch, you end up relying on trust when you should be relying on evidence.

Due diligence is the process of learning what you are really buying and whether it fits your risk tolerance, and it should begin earlier than most people expect. A beginner mistake is to treat due diligence as a security questionnaire sent right before purchase, but the best due diligence starts when the product team is still deciding between options. You want to ask what the system does, what it cannot do, and what conditions make it behave badly, because limitations matter as much as capabilities. You also want to understand what data the vendor touches, what data the vendor stores, and what data the vendor might reuse, because those choices can create privacy and compliance consequences. Another key due diligence idea is dependency mapping, meaning you learn what third parties your vendor relies on, because your risk chain can be longer than you realize. When you treat due diligence as learning, not paperwork, you can spot risks early enough to choose a safer option or adjust your design before you are locked in.

A strong due diligence mindset includes asking for clarity about model scope and intended use, because A I vendors often market broad capability while the safest performance happens inside narrow boundaries. You want the vendor to explain what tasks their system is designed to handle, what tasks it is not designed to handle, and what kinds of inputs create unstable or unsafe outputs. If the system is used for decision support, you should ask how it handles uncertainty, how it communicates confidence, and what guardrails exist to prevent harmful recommendations. If the system produces text or images, you should ask what safety filters exist and what categories of content are blocked or restricted. You are not looking for perfect answers; you are looking for whether the vendor can describe boundaries honestly and consistently. A vendor that cannot explain limitations in plain language is a vendor that may not manage those limitations well. That matters because your organization will be blamed for misuse even when the root cause is unclear boundaries.

Data questions are often the heart of A I vendor risk, because data is both the fuel and the possible leak point. You need to know whether your data is used only to provide the service or whether it could be used to improve the vendor’s models, and whether you can opt out of any reuse. You also need to know where data is stored, how long it is retained, and how it is protected, because retention and access patterns can create long-lasting exposure. Another beginner-friendly concern is data mixing, where your data might be processed in a way that puts it near other customers’ data, which can raise questions about separation and potential leakage. If the vendor uses your data for fine-tuning or training, you need to understand what that means for deletion and what it means for future model behavior. You should also ask what happens to logs, because logs can contain sensitive content even when the main storage is controlled. Good due diligence makes the invisible flow of data visible enough to manage.

Security due diligence still matters, but with A I you must expand what you consider part of security beyond the classic idea of keeping attackers out. You want to understand access controls, authentication, encryption, and incident response, but you also want to understand abuse resistance, such as how the system responds to attempts to manipulate it into doing unsafe things. You should ask about monitoring for misuse, rate limits, and safeguards that prevent one user from causing broad harm. You also want to know how updates are handled, because model updates can change behavior without obvious signs, which can create risk if your organization depends on stable outputs. Another security concern is availability and resilience, because if your business depends on the vendor, downtime becomes a risk event, not just an inconvenience. A simple way to summarize security due diligence is to ask how the vendor prevents compromise, how they detect problems, and how they contain damage. If their answers are vague, you should assume you will be surprised later.

Legal and privacy due diligence should not be treated as separate tasks that happen after security, because many vendor risks are about obligations and rights rather than technical weaknesses. For legal, you want to know what promises the vendor is making, what they refuse to promise, and what happens when performance or safety fails. For privacy, you want to know what personal data is involved, what justification is used to process it, and what transparency is expected for end users. You should also care about geography and jurisdiction, meaning where data processing happens and which rules might apply. Another important due diligence concept is permitted use, meaning what you are allowed to do with the system and what the vendor prohibits, because violations can create operational risk and contract risk. If a vendor prohibits certain sensitive uses but your product roadmap heads in that direction, you will face conflict later. Early alignment prevents you from building on top of a service you are not allowed to use the way you want.

Once due diligence reveals risks, the contract becomes the tool that turns expectations into enforceable commitments. Beginners often think contracts are just about price and basic terms, but for A I vendor risk, contract terms are where you define responsibilities, controls, and remedies. A contract can require certain security measures, require notice timelines for incidents, and require specific behaviors around data retention and deletion. It can also define ownership, such as who owns outputs, who owns fine-tuned models, and what happens if the relationship ends. Contracts can require cooperation, such as the vendor providing evidence for audits or answering risk questions on a schedule. Importantly, contracts can set boundaries, such as restricting the vendor from using your data for training or requiring that your data be segregated. Without clear contract language, you may have no leverage when you discover a risk you assumed was handled. The contract is not a substitute for trust, but it is the foundation for accountability.

One of the most important contract topics is data rights and data handling, because vague language here can create large privacy and compliance risks. You want clarity on whether your inputs are retained, whether they are used for improvement, and whether they are shared with sub-processors. You want clear deletion commitments, including what deletion means in practice, whether it includes backups, and how deletion is confirmed. You also want to address logs and telemetry, because some vendors treat logs as separate from customer data even when logs contain customer content. Another key point is confidentiality, meaning the vendor’s employees and systems should not access your data except as needed to provide the service, and access should be controlled and auditable. If your organization handles sensitive data, the contract should reflect that reality with stronger protections. Beginners should remember that unclear terms are not neutral; they usually benefit the party with more power. Making vendor risk real means insisting on clarity where it matters most.

Another contract area that matters a lot for A I is change management, because model behavior can shift even when the interface stays the same. You want to know how the vendor announces changes, what notice you get, and whether you can delay or opt out of changes that create risk. You also want to know how the vendor tests updates for safety and quality, and whether those tests are meaningful for your use case. If your organization relies on consistent behavior for compliance or safety, you may need stronger terms around versioning and stability. Contracts can also address service levels, meaning uptime expectations and response times, because outages and degraded performance can become operational risk. For A I systems that influence decisions, you should care about quality regressions, not just downtime. A vendor update that increases hallucinations can be just as damaging as an outage if users act on incorrect information. This is why ongoing oversight must exist, because contracts alone cannot predict every change.

Ongoing oversight is the part many organizations underinvest in, and it is where vendor risk becomes a living practice instead of a one-time review. Once the system is in use, real risk shows up in real outputs, and you need ways to notice problems early. Oversight includes performance monitoring, safety monitoring, and compliance monitoring, and it should be tied to your specific use case. For example, if the A I system helps users draft messages, oversight might focus on unsafe content, privacy leakage, or misleading claims. If the A I system supports decisions, oversight might focus on error patterns, drift, and user over-reliance. Oversight also includes relationship management, meaning regular check-ins, shared incident drills, and clear points of contact. A vendor relationship without ongoing conversation is a relationship where surprises build silently. Beginners should think of oversight as a safety habit that continues for as long as the vendor is part of your system.

A key idea in ongoing oversight is verification, meaning you do not rely only on what the vendor says, but you also watch what the system does. You can verify by sampling outputs, tracking complaints, reviewing unusual spikes in certain types of results, and monitoring for patterns that suggest drift or abuse. You can also verify by checking whether the vendor is meeting reporting obligations and whether they disclose incidents and changes as promised. Another oversight practice is auditing, which can include requesting evidence of controls, reviewing third-party assessments, or requiring periodic updates on security and privacy practices. The goal is not to punish vendors; the goal is to keep risk visible and manageable. Vendors also benefit from this structure because clear oversight signals that your organization takes safety seriously and will not accept vague reassurances. Oversight should be predictable and proportional, not random and reactive. When oversight is built into normal operations, it becomes easier to respond calmly when something goes wrong.

Incident handling is one of the clearest places where vendor risk becomes real, because incidents force you to discover whether roles and responsibilities are actually understood. You need to know how to contact the vendor, how quickly they respond, what information they will provide, and what actions they can take to contain harm. You also need to know how evidence is preserved, because logs and records matter when investigating what happened and proving that you acted responsibly. If the incident involves personal data, privacy and legal requirements may impose strict timelines and communication expectations, and you need vendor cooperation to meet them. Another incident concern is coordination with your own teams, because your internal security, privacy, and product teams must act in sync with the vendor’s response. A vendor who treats incidents as purely technical events can conflict with your need to communicate responsibly. Ongoing oversight should include practicing incident workflows so that when a real event happens, everyone knows what to do. This is how you avoid confusion under pressure.

As you bring all of this together, the most important beginner lesson is that vendor risk is not a feeling and it is not a reputation score; it is a set of questions and controls that turn uncertainty into managed exposure. Due diligence is where you learn what the vendor is really offering and what risks come with it, contracts are where you turn critical expectations into obligations, and ongoing oversight is where you make sure those obligations stay true over time. If you skip due diligence, you buy risk you did not understand. If you skip strong contract terms, you have little leverage when problems appear. If you skip oversight, you discover issues only after users are harmed or trust is lost. A I makes these steps more important because behavior can be complex, changes can be frequent, and data can be sensitive in unexpected ways. When you can describe these ideas clearly, you are already thinking like someone who can manage A I vendor risk in a responsible way, even at a beginner level.