Document classification, the process of organizing documents into categories based on their content, can indeed be applied effectively in the cloud. Instead of running software on local computers, cloud-based classification leverages remote servers accessed over the internet. Users upload documents via web interfaces or APIs, and cloud services analyze the text, structure, or metadata using machine learning models to automatically assign relevant categories or labels, returning the results back to the user.

Common practical applications include automating email routing and organization within cloud email platforms like Microsoft 365 or Google Workspace, where emails are classified into folders like "Support Tickets" or "Sales Inquiries." Another key use is in legal and compliance workflows within cloud storage platforms like Box or AWS S3, where incoming contracts, invoices, or policy documents are automatically tagged for easier retrieval, retention policy application, and regulatory audits.

Cloud classification offers significant scalability to handle large document volumes and eliminates local infrastructure management. However, reliance on internet connectivity and potential data privacy concerns when sending sensitive documents to a third-party cloud are limitations. Reputable cloud providers mitigate privacy risks with strong encryption, compliance certifications, and private cloud deployment options. As AI models improve, classification accuracy for complex documents continues to increase, driving wider adoption across industries for efficiency gains.