Free AIF-C01 Exam Braindumps
AWS Certified AI Practitioner Questions 216–220 (page: 45)

Updated On: 1-Oct-2026

A company has developed a generative AI application by using Amazon Bedrock. The application produces catalogs that are updated weekly. The company needs to select a pricing model for weekly catalog updates.
Which Amazon Bedrock pricing model meets these requirements MOST cost-effectively?

  1. On-Demand
  2. Provisioned Throughput
  3. Batch
  4. Model evaluation

Answer(s): C

Explanation:

Batch is the most cost-effective choice for weekly catalog updates because it is designed for asynchronous,
non-real-time workloads, and AWS states that Amazon Bedrock batch inference can process large jobs offline at lower cost, including pricing at up to 50% of on-demand inference for supported models.



A company has developed an ML model to approve or reject loan applications. The model’s decision-making process must be transparent and explainable to comply with regulatory requirements. The company must document the decision-making process for audit purposes.
Which solution will meet these requirements?

  1. Amazon Textract
  2. Amazon SageMaker Model Card
  3. AWS Cloud Formation
  4. Amazon Comprehend

Answer(s): B

Explanation:

Amazon SageMaker Model Card enables you to document a model’s decision-making process, including transparency and explainability details, which helps meet regulatory and audit requirements for AI-driven decisions such as loan approvals.



A company wants to build a customer-facing generative AI application. The application must block or mask sensitive information. The application must also detect hallucinations.
Which solution will meet these requirements with the LEAST operational overhead?

  1. Use AWS Lambda functions to build a policy evaluator.
  2. Select a foundation model (FM) that includes policies that remove harmful content by default.
  3. Use Amazon Bedrock Guardrails to implement safeguards for the application based on use cases.
  4. Host a custom build policy evaluator on Amazon EC2 instances.

Answer(s): C

Explanation:

Amazon Bedrock Guardrails provides managed safeguards for generative AI applications, including sensitive information filtering or masking and contextual grounding checks that help detect hallucinated responses. It minimizes operational overhead compared with building and maintaining a custom policy evaluator.



A company is developing an AI solution to help make hiring decisions.
Which strategy complies with AWS guidance for responsible AI?

  1. Use the AI solution to make final hiring decisions without human review.
  2. Train the AI solution exclusively on data from previous successful hires.
  3. Test the AI solution to ensure that it does not discriminate against any protected groups.
  4. Keep the AI decision-making process confidential to maintain a competitive advantage.

Answer(s): C

Explanation:

Responsible AI requires evaluating systems for fairness and potential bias, especially in high-impact use cases such as hiring. Testing the solution for discrimination against protected groups helps ensure the AI system supports fair and accountable decision-making.



A pharmaceutical company wants to analyze user reviews of new medications and provide a concise overview for each medication.
Which solution meets these requirements?

  1. Create a time-series forecasting model to analyze the medication reviews by using Amazon Personalize.
  2. Create medication review summaries by using Amazon Bedrock large language models (LLMs).
  3. Create a classification model that categorizes medications into different groups by using Amazon
    SageMaker.
  4. Create medication review summaries by using Amazon Rekognition.

Answer(s): B

Explanation:

Amazon Bedrock provides access to a variety of large language models (LLMs), which are well-suited for tasks such as text summarization. By using LLMs, the pharmaceutical company can automatically generate concise and coherent summaries of user reviews for each medication. These models are designed to understand and process large amounts of text, making them ideal for summarizing user reviews in a clear and efficient manner.
Amazon Bedrock allows the company to utilize LLMs that can generate summaries, which is exactly what is needed in this case.



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