- A
Key Phrase Extraction
Why wrong: Key Phrase Extraction identifies important phrases in text (e.g., 'service quality', 'billing department') but does not detect or redact personally identifiable information.
- B
Sentiment Analysis
Why wrong: Sentiment Analysis determines whether text is positive, negative, or neutral. It does not identify or redact PII.
- C
Personally Identifiable Information (PII) Detection
PII Detection in Azure AI Language can automatically identify and optionally redact sensitive data such as names, addresses, phone numbers, and social security numbers. This is the correct feature for the law firm's requirement.
- D
Language Detection
Why wrong: Language Detection identifies the language of a text (e.g., English, Spanish). It does not handle PII identification or redaction.
Quick Answer
The correct choice is the Personally Identifiable Information (PII) Detection feature in Azure AI Language. This prebuilt service is specifically designed to identify and redact sensitive data like names, addresses, and social security numbers from text without requiring any custom training or machine learning expertise, making it the perfect fit for the law firm’s need to automatically redact PII from thousands of legal documents. On the Microsoft Azure AI Fundamentals AI-900 exam, this question tests your understanding of prebuilt Azure AI Language capabilities versus custom solutions like Custom Text Classification or Custom Named Entity Recognition—a common trap is confusing PII Detection with standard Named Entity Recognition (NER), which identifies entities but does not automatically redact them. Remember, if the scenario emphasizes automatic redaction of personal data without training, PII Detection is your answer. A helpful memory tip: think “PII = Protect It Immediately” to recall its built-in redaction purpose.
AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure
This AI-900 practice question tests your understanding of describe features of natural language processing workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A law firm needs to automatically redact personal identifiable information (PII) such as names, addresses, and social security numbers from thousands of legal documents before making them public. They want to use a prebuilt Azure AI Language feature without custom training. Which feature should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Personally Identifiable Information (PII) Detection
Option C is correct because PII Detection is a prebuilt Azure AI Language feature specifically designed to identify and redact personal identifiable information such as names, addresses, and social security numbers from text. It requires no custom training, making it ideal for the law firm's use case of automatically redacting PII from legal documents before public release.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Key Phrase Extraction
Why it's wrong here
Key Phrase Extraction identifies important phrases in text (e.g., 'service quality', 'billing department') but does not detect or redact personally identifiable information.
- ✗
Sentiment Analysis
Why it's wrong here
Sentiment Analysis determines whether text is positive, negative, or neutral. It does not identify or redact PII.
- ✓
Personally Identifiable Information (PII) Detection
Why this is correct
PII Detection in Azure AI Language can automatically identify and optionally redact sensitive data such as names, addresses, phone numbers, and social security numbers. This is the correct feature for the law firm's requirement.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Language Detection
Why it's wrong here
Language Detection identifies the language of a text (e.g., English, Spanish). It does not handle PII identification or redaction.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates might confuse Key Phrase Extraction with entity recognition, but Key Phrase Extraction does not identify specific PII categories like names or SSNs, only general topics.
Trap categories for this question
Keyword trap
Key Phrase Extraction identifies important phrases in text (e.g., 'service quality', 'billing department') but does not detect or redact personally identifiable information.
Detailed technical explanation
How to think about this question
Azure AI Language's PII Detection uses pre-trained models to recognize categories such as PersonName, PhoneNumber, and USSocialSecurityNumber, and can return redacted text or labeled entities. Under the hood, it leverages transformer-based neural networks fine-tuned on large annotated corpora, and supports batch processing for scalability. A subtle behavior is that it can also detect PII in unstructured text like legal clauses, but may miss context-specific abbreviations or non-standard formats without custom entity recognition.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of Natural Language Processing workloads on Azure — This question tests Describe features of Natural Language Processing workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Personally Identifiable Information (PII) Detection — Option C is correct because PII Detection is a prebuilt Azure AI Language feature specifically designed to identify and redact personal identifiable information such as names, addresses, and social security numbers from text. It requires no custom training, making it ideal for the law firm's use case of automatically redacting PII from legal documents before public release.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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