
IDC Perspective: The Business Value of Natural Language Processing Applications in Enterprises
Description
IDC Perspective: The Business Value of Natural Language Processing Applications in Enterprises
This IDC Perspective covers the business value of natural language processing (NLP) applications in enterprises. It reviews the current state of NLP, the synergies between NLP and text analytics, the way NLP is currently used by enterprises, and sample customer success scenarios. It also includes an analysis of large language models, its associated challenges, and what the future holds. It provides guidance to the technology buyer on how to embrace NLP and maximize ROI."NLP is rapidly becoming as integral to an enterprise as communication itself. Although NLP has made big strides over the last few years, context, relevance, and time to market for NLP solutions continue to be challenging," says Ritu Jyoti, group VP, artificial intelligence (AI) and automation research at IDC. "Enterprises need foundational language models that capture business context, bias detection, and mitigation to detect and fix bias from models created elsewhere," she adds.
Please Note: Extended description available upon request.
This IDC Perspective covers the business value of natural language processing (NLP) applications in enterprises. It reviews the current state of NLP, the synergies between NLP and text analytics, the way NLP is currently used by enterprises, and sample customer success scenarios. It also includes an analysis of large language models, its associated challenges, and what the future holds. It provides guidance to the technology buyer on how to embrace NLP and maximize ROI."NLP is rapidly becoming as integral to an enterprise as communication itself. Although NLP has made big strides over the last few years, context, relevance, and time to market for NLP solutions continue to be challenging," says Ritu Jyoti, group VP, artificial intelligence (AI) and automation research at IDC. "Enterprises need foundational language models that capture business context, bias detection, and mitigation to detect and fix bias from models created elsewhere," she adds.
Please Note: Extended description available upon request.
Table of Contents
12 Pages
- Executive Snapshot
- Situation Overview
- NLP and Text Analytics Synergies
- Common NLP Applications in Enterprises
- Out-Of-The-Box or Custom Models
- Out-Of-The-Box NLP Models
- Custom NLP Models
- Customer Success Scenarios
- Unlocking Value from Clinical Documents and Research Materials
- NLP for Customer Care: Virtual Assistants
- NLP in Print and Media
- NLP for Supply Chain Resilience
- NLP in Life Insurance
- NLP in Knowledge Extraction and Intelligent Document Processing
- NLP: Large Language Models in the Financial Industry
- NLP Business Solutions: Embedded AI
- Large Language Models: Today and the Future
- Advice for the Technology Buyer
- Learn More
- Related Research
- Synopsis
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