© 2024 ServiceNow, Inc. All rights reserved. ServiceNow, the ServiceNow logo, Now, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries. Other company names, product names, and logos may be trademarks of the respective companies with which they are associated. Deep Learning is an artificial neural network, which is an algorithm that mimics the structure of the brain with many layers. It has the ability to learn hierarchical abstractions and automatically learns the best outcome for the problem. In other words, it imitates the human brain, continuously learning and improving itself. What can you do with AI? Here are some real-world examples of how the AI in the Now Platform to elevate work experiences. Supercharge productivity Free your people from repetitive tasks using autonomous AI agents that proactively learn, reason, collaborate, and solve problems. Detect major incidents Quickly identify critical issues by proactively identifying similarities across open incidents or cases. Route and prioritize work Classify requests so incidents, cases, and tasks automatically get to the right team, at the right time. Deliver better self-service Make it easy for users to get what they need with a 24/7 Virtual Agent that understands their requests in natural language. Optimize knowledge bases Deflect tickets and reduce call volume by uncovering knowledge gaps and preventing duplicate content. Recommend actions and deliver answers Connect the dots for agents by suggesting relevant tasks and content that help them solve issues faster. Empower users with search Gain highly accurate and relevant search results for an enhanced user experience. Quickly identify opportunities to automate End the struggle with how and when to turn-on automation solutions from ServiceNow and increase deflection while lowering mean-time-to-resolve (MTTR). Discover hidden patterns Continuously group clusters of related items to uncover trends and the best opportunities for improvement. Classification Uses historical data to automatically apply the correct labels—category, assignment group, and priority—to incoming requests, freeing your employees to work on more meaningful tasks. Similarity Analyzes text to find connections across incidents, cases, events, and knowledge articles to help detect major incidents, recommend relevant content, and suggest actions the agent should take. Clustering Works behind the scenes to continuously group and describe records so you can focus on the next step—using those concepts to fill knowledge gaps, add new catalog items, or train teams with new skills. Intelligent document processing Accelerate and automate document processing with AI models that identify, understand, and extract text and data. Foundational NLP A base level of analyzing language, NLP extracts the most important pieces of information from blocks of information and converts between speech and text. Natural language understanding Enables you to make requests the same way you would ask another human. NLU comprehends each request by recognizing what you would like to do (intent) and all of the supporting details (entities). Large language models Use targeted, purpose-built LLMs to recognize, summarize, translate, predict, and respond to natural language inputs. Sentiment analysis Detect and understand sentiment in human messages and determine the appropriate response to ensure the best service. Multi-language support Predict the language used in requests and automatically assign to someone who speaks that language for support—or use dynamic translation for a seamless localized experience. Intelligent search Consumer-grade search experience delivering highly accurate and relevant results based on user context using natural, everyday language. Semantic search Improve search accuracy by understanding user intent and context. Natural language query Deliver immediate answers by converting plain language questions into database query code before returning the results as user-friendly lists, numeric values, or dynamic charts.