Which of the following is a typical business goal that a generative AI strategy in testing aims to achieve?

Eliminating all software defects before release

Reducing the time to market for software releases

Increasing the number of testers on every project

Replacing the need for test environments

Which factor is most relevant when assessing organizational readiness for generative AI in testing?

The availability of skilled personnel who understand AI and testing

The organization's social media presence

The number of test cases currently automated

The brand of computers used by the testing team

A testing organization wants to develop a generative AI strategy. They have a mature testing process, but the team is distributed across multiple time zones and uses different tools. The strategy must be realistic and achievable. What is the most important component of the strategy?

A phased implementation plan that starts with a single team and a specific use case.

A training program for all team members before any implementation.

A comprehensive tool selection process that evaluates all available AI tools.

A governance framework that covers all possible risks and ethical issues.

A small software company wants to implement a generative AI strategy for testing. They have a limited budget and a small team with no AI expertise. They need to decide how to allocate resources. Which resource allocation approach is most appropriate?

Build a custom in-house AI solution to have full control and avoid recurring costs.

Start with a low-cost, user-friendly AI tool and provide basic training to existing testers.

Invest heavily in a commercial AI testing platform and hire AI specialists to manage it.

Use only free open-source AI tools and rely on community support for training.

What is an ethical consideration when using generative AI in testing?

Guaranteeing that AI produces more test cases than human testers

Ensuring AI tools are the most expensive on the market

Hiding AI usage to avoid stakeholder concerns

Ensuring transparency about AI-generated test artifacts

Certified Tester Testing with Generative AI

Domain 5Objective 2

Key Aspects of a Generative AI Strategy in Software Testing CT-GENAI Practice Questions (Page 1)

Part of the Deploying and Integrating Generative AI in Test organizations domain, which makes up ~23% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~6–9 in this domain), expect 1–1 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

8concepts

Questions 1–5

1foundation · easy
Which of the following is a typical business goal that a generative AI strategy in testing aims to achieve?
Select an answer first
2foundation · easy
Which factor is most relevant when assessing organizational readiness for generative AI in testing?
Select an answer first
3expert · hard
A testing organization wants to develop a generative AI strategy. They have a mature testing process, but the team is distributed across multiple time zones and uses different tools. The strategy must be realistic and achievable. What is the most important component of the strategy?
Select an answer first
4application · medium
A small software company wants to implement a generative AI strategy for testing. They have a limited budget and a small team with no AI expertise. They need to decide how to allocate resources. Which resource allocation approach is most appropriate?
Select an answer first
5foundation · easy
What is an ethical consideration when using generative AI in testing?
Select an answer first

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