IBM watsonx Governance Lifecycle Advisor Associate (C1000-195) Certification Sample Questions

The purpose of this Sample Question Set is to provide you with information about the IBM watsonx Governance Lifecycle Advisor v1 - Associate exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the C1000-195 certification test. To get familiar with real exam environment, we suggest you try our Sample IBM watsonx Governance Lifecycle Advisor Associate Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual IBM Certified watsonx Governance Lifecycle Advisor v1 - Associate certification exam.

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IBM C1000-195 Sample Questions:

01. Before an external audit, a logistics company's compliance lead wants to chase owners whose high-risk AI use cases still lack a completed attestation questionnaire. She needs one list that she can work through and share.

What should the advisor build?

a) A fairness evaluation report for each high-risk deployment in production

b) A custom report of high-risk use cases showing each questionnaire's completion status

c) An export of the risk atlas entries used in high-risk assessments

d) The factsheet of each high-risk use case, opened and reviewed one at a time by the compliance lead

02. While building a complete AI inventory, a regional water utility surveys its departments. It finds customer-service staff pasting customer letters into a public generative AI chatbot that the governance team never approved and that appears in no AI use case.

Which term describes this kind of AI use, which a complete inventory must bring to light?

a) Shadow AI

b) External models

c) Retired assets

d) Challenger models

03. At a regional bank, a validator testing a mortgage-approval model finds that approval rates for applicants over 60 fall below the fairness acceptance criterion agreed for the use case. The model owner wants the launch to proceed on schedule.

What should the validator do?

a) Adjust the fairness criterion so the model passes, and note the change in the report

b) Record the failed criterion in the validation findings and withhold sign-off until it is remediated or formally accepted

c) Approve the model and ask the risk manager to add a production fairness monitor

d) Retrain the model with rebalanced data and then complete the validation

04. The exam blueprint names four governance stages: Development, Validation, Production and Retirement. The lifecycle view of an AI use case in watsonx.governance shows phases instead.

Which phase corresponds to the Production stage?

a) Develop

b) Track

c) Operate

d) Validate

05. A grocery chain promoted version 2.0.0 of its replenishment model to production last night. By morning its order quantities are badly wrong for most stores, and orders are due at noon. Version 1.4.0 served production for a year, and its validation, approval and facts are still recorded in the same approach. The chain's policy allows a return to the last approved version under its change procedure.

Which two actions should the governance advisor support?

(Choose two.)

a) Redeploy version 1.4.0 under the change procedure as the last approved version

b) Keep version 2.0.0 out of production until a corrected version passes validation

c) Register version 1.4.0 in a new approach to approve it again

d) Delete version 2.0.0 and its facts so the use case shows only the working version

e) Patch version 2.0.0 in production now and document the patch after the orders are placed

06. On a Friday evening, a media company's production summarization prompt template starts including personal information from source articles in its output. The on-call engineer can adjust the PII guardrail threshold in minutes, but the next change review meeting is on Tuesday.

Which approach best fits sound change management?

a) Apply the fix under an expedited emergency approval, then document it and review it at the next meeting

b) Leave the output unchanged until Tuesday so the fix passes the normal review

c) Apply the fix now and treat it as a configuration tweak that needs no record

d) Move the use case back to Develop and revalidate it before any threshold is changed

07. Which stakeholder independently tests a model against its acceptance criteria and signs off on that testing before the model can move to production?

a) Model owner

b) Risk manager

c) Validator

d) Model developer

08. Which characteristic of AI systems makes AI governance necessary in addition to traditional IT governance?

a) Hosting on shared infrastructure with uptime targets

b) Requirement for user access reviews on applications holding business records

c) Dependence on software release management and formal version control processes

d) Behavior learned from data that can shift after deployment

09. An insurance group builds one pricing model on Amazon Web Services and a second model in a notebook that its data scientists deploy on their own infrastructure. The governance lead wants both governed in watsonx.governance.

Which two statements are true?

(Choose two.)

a) The notebook model is treated as an external model, like the AWS model

b) External models must be rebuilt in a watsonx project before they can be evaluated

c) watsonx.governance can evaluate both models once each deployment is set up for evaluation

d) The AWS model is external, while notebook models are tracked as project assets

e) External models are listed in the inventory without a lifecycle phase

10. During risk identification for a telecom provider's churn-prediction use case, the risk manager records that customer behavior shifts quickly after competitor price changes, so the data the model scores in production may stop resembling its training data.

Which evaluation should be planned to give evidence on this risk?

a) Drift evaluation comparing production data with the model's training data

b) Model health monitoring of the deployment

c) Fairness evaluation across a monitored and a reference group

d) Explainability analysis of individual predictions

Answers:

Question: 01 Answer: b	Question: 02 Answer: a	Question: 03 Answer: b	Question: 04 Answer: c	Question: 05 Answer: a, b
Question: 06 Answer: a	Question: 07 Answer: c	Question: 08 Answer: d	Question: 09 Answer: a, c	Question: 10 Answer: a

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