This question is based on identifying Natural Language Processing (NLP) workloads, which is a fundamental topic in the Microsoft Azure AI Fundamentals (AI-900) certification. According to the official Microsoft Learn module “Describe features of natural language processing (NLP) workloads on Azure”, NLP enables computers to understand, interpret, and generate human language — both written and spoken.

A bot that responds to queries by internal users – YesThis is an example of a natural language processing workload because it involves understanding and generating human language. A chatbot interprets user input (queries written or spoken) using language understanding and text analytics, and then produces appropriate responses. On Azure, this can be implemented using Azure AI Language (LUIS) and the Azure Bot Service, both core NLP technologies.

A mobile application that displays images relating to an entered search term – NoThis application involves searching for or displaying images, which falls under the computer vision workload, not NLP. Computer vision focuses on analyzing and interpreting visual data like photos or videos, while NLP deals with language and text processing.

A web form used to submit a request to reset a password – NoA password reset form involves structured input fields and user authentication, not natural language understanding or generation. It’s part of standard web development and identity management, not an NLP-related process.

Therefore, based on Microsoft’s AI-900 curriculum definitions:

✅ The only true NLP example is the bot responding to user queries, since it processes and understands natural language input to generate conversational output.