TECH SUPPLIER Nov 2019 - Special Study - Doc # US45584319
Natural Language Processing by Artificial Intelligence Industry and Use Case: A Quantitative and Qualitative Assessment
This IDC study overlays market forecasts from IDC's Worldwide Semiannual Artificial Intelligence Systems Spending Guide with a specific technology, natural language processing (NLP), to provide both a qualitative and quantitative assessment of the AI NLP market opportunity.
Many solutions that address important AI use cases make use of natural language processing as a key component in understanding written and spoken language and enabling the extraction of valuable insights. This study identifies the top AI Spending Guide use cases where natural language processing is a key component of the solution and provides qualitative guidance around what those use cases are and how they deliver business value for enterprises. It also provides a quantitative forecast of what the U.S. AI software spend will be on those use cases now and over the next five years. These use cases are focused within five industries that IDC has identified as spending the most on NLP solutions: retail, banking, discrete manufacturing, healthcare, and securities and investments.
Vendors across the AI NLP and AI systems market will benefit from insights that combine quantitative spending guide data with qualitative analyst expertise around NLP, including knowledge from existing end-user surveys and interviews. This study may be used as a companion piece to IDC's Worldwide Semiannual Artificial Intelligence Systems Spending Guide and IDC's worldwide industry research. Technology suppliers may utilize this research to help them with their strategic planning, product development product marketing, and overall AI journey.
"Worldwide AI systems spend has moved beyond the early adopters to mainstream industrywide use-case implementation," said Marianne Daquila, research manager, Customer Insights and Analysis at IDC. "Leading digital organizations are using NLP to derive insights from content-specific values such as sentiment, intent, and relevance. NLP advances are providing enterprises of all types with the ability to uncover hidden insights from unstructured data. These insights are helping companies personalize their relationship with customers, thwart fraudulent losses, and keep factories running."
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