A traditional manufacturing company wants to implement AI to optimize its supply chain. The workforce is concerned about job displacement, and the IT department lacks AI expertise. The CEO wants to proceed but also wants to maintain employee morale. Which strategy best addresses both goals?

Implement AI gradually with a change management program and reskilling opportunities

Implement AI quickly to gain a competitive advantage

Outsource all AI development to avoid internal training

Keep the AI initiative secret until it is fully operational

A company is decommissioning an AI system that was used for customer churn prediction. The model was trained on customer data and is being replaced by a new system. Which step is most important during the decommissioning process?

Ensure that all customer data used by the old system is securely deleted or archived according to retention policies.

Notify all customers that their data was used for AI predictions and give them the option to opt out.

Immediately remove all references to the old system from documentation and internal wikis.

Keep the old model running in parallel for a month to compare performance with the new system.

What is a key due diligence step when selecting an AI vendor?

Choosing the cheapest option without review

Signing a contract without reading it

Assuming the vendor is compliant with all regulations

Assessing the vendor's security and privacy practices

A city government is developing an AI system to allocate public resources. The data available includes historical service requests, but the data is incomplete for certain neighborhoods. The city must ensure equitable allocation and comply with public records laws. Which approach best addresses the data quality issue while maintaining compliance?

Supplement the dataset with community surveys and document the data limitations

Use the existing data and accept the bias

Keep the data private to avoid public scrutiny

Remove all incomplete records from the dataset

What is a best practice for protecting the privacy of data used in AI training?

Sharing data with third parties for validation

Using data encryption at rest and in transit

Storing all data in a public cloud

GIAC Security Leadership

Domain 2Objective 5

Managing Artificial Intelligence GSLC Practice Questions (Page 3)

Part of the Technical Security Management domain, which makes up ~27% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 180-minute exam (~70–120 total, ~19–32 in this domain), expect 4–6 from this objective — we provide 61 practice questions to prepare you well beyond it. (estimate)

61questions here

13free pages

12concepts

Questions 11–15

11expert · hard
A traditional manufacturing company wants to implement AI to optimize its supply chain. The workforce is concerned about job displacement, and the IT department lacks AI expertise. The CEO wants to proceed but also wants to maintain employee morale. Which strategy best addresses both goals?
Select an answer first
12application · medium
A company is decommissioning an AI system that was used for customer churn prediction. The model was trained on customer data and is being replaced by a new system. Which step is most important during the decommissioning process?
Select an answer first
13foundation · easy
What is a key due diligence step when selecting an AI vendor?
Select an answer first
14expert · hard
A city government is developing an AI system to allocate public resources. The data available includes historical service requests, but the data is incomplete for certain neighborhoods. The city must ensure equitable allocation and comply with public records laws. Which approach best addresses the data quality issue while maintaining compliance?
Select an answer first
15foundation · easy
What is a best practice for protecting the privacy of data used in AI training?
Select an answer first

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