Microsoft Azure AI Fundamentals AI-900 Practice Question
A company has amassed a vast repository of documents, including PDFs, Word files, and scanned images of text. They want to enable employees to find specific information within these documents, such as policy details or client data, regardless of the file format.
Which type of AI workload would best address this need?
Knowledge mining is the appropriate AI workload because it orchestrates services such as OCR, natural language processing, and search indexing to ingest, enrich, and make large, heterogeneous document collections easily searchable.
Natural language processing focuses on understanding and generating language from already-available text but does not, by itself, provide the pipeline to ingest multiple file formats or build a search index.
Computer Vision can extract text from images and scanned pages through OCR, but on its own it lacks the enrichment and indexing steps required to turn a mixed-format content repository into a searchable knowledge base.
Content personalization tailors experiences to individual users' preferences and does not address the need to search across a document repository.
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Microsoft Azure AI Fundamentals AI-900
Describe Artificial Intelligence Workloads and Considerations
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