NATURAL LANGUAGE PROCESSING MARKET ANALYSIS

Natural Language Processing Market Size and Trends

Global natural language processing market is estimated to be valued at US$ 26.71 billion in 2024 and is expected to reach US$ 132.91 billion by 2031, exhibiting a compound annual growth rate (CAGR) of 25.8% from 2024 to 2031. NLP technologies allow humans to interact with computers using their normal, daily language instead of computer codes. It is being integrated across industries like healthcare, BFSI, retail, automotive and more to improve operations.

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There has been huge demand for NLP due to increasing focus on enhancing customer support services using chatbots and virtual assistants. Furthermore, integration of NLP with artificial intelligence and machine learning allows developers to build more human-like conversational agents. Many organizations are also implementing NLP-based applications to automate repetitive tasks and improve their decision making abilities.

Increased Use of Virtual Assistants and Chatbots

Growing demand for virtual assistants can drive the natural language processing market growth. Brands across various sectors are developing their own virtual assistants and chatbots to provide enhanced customer support and improve user experience. These AI-powered virtual tools are being used by many companies to automate repetitive tasks, answer basic customer queries, book appointments, and complete other such activities using natural conversational abilities. As users get more accustomed to interacting with virtual agents for their everyday needs, there is need for advanced natural language capabilities. Many businesses are also deploying virtual assistants to make their websites and mobile applications more interactive. This is encouraging NLP technology providers to come up with more sophisticated linguistic and conversational solutions.

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Advancements in Conversational Commerce and Dialog Systems

Increasing focus on conversational commerce and development of dialog systems can drive the market growth. Brands have realized the revenue potential of voice assistants and are keen on offering optimized shopping experiences through conversational interfaces. This requires powerful NLP platforms that can understand customers, recognize intents, personalize responses, and enable seamless transactions verbally. Technology companies are making continued investments innovations related to dialog management, deep learning for language modeling, and other aspects of human-chatbot conversations. Their aim is to create highly engaging dialog systems for various business processes and customer service functions. As more firms prioritize building conversational interfaces for service sectors like retail, tourism, healthcare, and automotive, these will rely extensively on advanced language technologies. This fuels the incorporation of sophisticated NL features such as sentiment analysis, entity recognition, question answering and summarization.