Language Processing Market Upcoming Trends, Segmented by Type, Application, End-User and Region -Addstructure, Apple, Dialogflow, DigitalGenius, Google, IBM, Klevu, Microsoft, Mindmeld, NetBase, Satisfi Labs, Twiggle, Inbenta-he global NLP Market Size was

New Jersey (United States) - The global NLP Market Size was valued at $12.1 billion in 2021, and is projected to reach $351.5 billion by 2032, growing at a CAGR of 41.9% from 2021 to 2032.

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Some of the Top companies Influencing this Market include:

Addstructure, Apple, Dialogflow, DigitalGenius, Google, IBM, Klevu, Microsoft, Mindmeld, NetBase, Satisfi Labs, Twiggle, Inbenta

The Natural Language Processing (NLP) is a part of artificial intelligence (AI) that enable the computer to interpret human language, obtains meaning, and make communication more convenient by using voice enabled artificial intelligence (AI) and conversational intelligence technologies. In addition, the NLP features such as autocorrect and autocomplete tool help to analyze personal language patterns and identify the most appropriate suggestions for the individual users or public. Furthermore, natural language processing automates much of the physical process, provides analytics and business intelligence for growth and helps to order and organize the processes. In addition, growing data and increasing complexities in large businesses would open numerous opportunities for natural language processing market

Language Processing Market Types:

Interactive Voice Response (IVR), Optical Character Recognition (OCR), Pattern and Image Recognition, Auto Coding, Classification and Categorization, Text Analytics, Speech Analytics, Professional Services, Support and Maintenance Services.

Language Processing Market Applications:

Banking, Financial Services, and Insurance (BFSI), Manufacturing, Healthcare and Life Sciences, Retail and Consumer Goods, Research and Education, High Tech and Electronics, Media and Entertainment

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On the basis of component, the solution segment dominated the overall natural language processing (NLP) industry in 2020, and is expected to continue this trend throughout the forecast period. Factors such as increase in competition in businesses, legislation, user needs, and project risks, the adoption of NLP increases, which drives the growth of the market. In addition, NLP solutions offer the necessary tools to analyze both numerical and linguistic data, which is beneficial for the market. However, the services segment is expected to witness highest growth in the upcoming years. The adoption of NLP services provides numerous benefits to the industry verticals such as speeds up software implementation, maximizes the value of existing installation by optimizing it, and minimizes the deployment cost & risks, and others, which further fuels the market growth.

The report provides insights on the following pointers:

Market Penetration: Comprehensive data on the product portfolios of the top players in the Language Processing market.

Product Development/Innovation: Detailed information about upcoming technologies, R&D activities, and market product debuts.

Competitive Assessment: An in-depth analysis of the market's top companies' market strategies, as well as their geographic and business segments.

Market Development: Information on developing markets in its entirety. This study examines the market in several geographies for various segments.

Market Diversification: Extensive data on new goods, untapped geographies, recent advancements, and investment opportunities in the Language Processing market.

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The current estimation of 2030 is projected to be higher than pre-COVID-19 estimates. The global COVID-19 pandemic has drastically affected businesses across the world. COVID-19 pandemic has positively impacted the adoption of NLP based services due to lockdown imposed by governments of different countries. Post COVID-19 situation, companies are focusing on advanced technology such as artificial intelligence (AI), machine learning (ML), computing technology and analytics across industries such as BFSI, healthcare, IT and telecom and others, to perform contactless operation. This factor also creates demand for AI-driven NLP technology, which drive the adoption of natural language processing (NLP) market globally.

Moreover, the pandemic has introduced considerable challenges for companies that are trying to execute key processes, report accurately about data spread over multiple locations, operate complex systems, and efficiently communicate with teammates; particularly where they don't already have the infrastructure for such processes. Hence, a greater number of companies are investing in natural language processing (NLP). NLP provides the limitless scalability and continual enhancement of functionality, which are critical in accomplishing digital transformation, which boost the growth of the market. For instance, in June 2020; IBM Data and artificial intelligence (AI) team resolution collaborated to consolidate state and county-level information across websites, and local government sites around 50 states of the U.S. The IBM Watson NLP, and IBM Data & Governance (IDG) help to create clean, and easily understandable insights source that enabled people or individuals to understand COVID-19 activity in their communities.

Shift from Product-Centric to Customer-Centric Experience Drive the Global Natural Language Processing Market

As a communication, consumption, and interaction method, the internet has empowered consumers. Companies have had to reconsider their branding and business methods. Attracting customers away from competitors in today's competitive economy takes more than the dominant product-centric or company-centric paradigm. In some circumstances, proactive communication can forecast a customer's next move and pre-empt queries. Customer engagement systems combine AI capabilities to allow end users to create scalable, personalized customer experiences without the need for human programming or logic construction. Such elements contribute to market expansion.

Cognitive technology is the next generation of artificial intelligence to improve end-user industrial application-based usefulness. It is used to create new cognitive computing initiatives. AI may help businesses automate business processes, get insights through data analysis, and engage with consumers and workers.

According to the findings of a Harvard Business Review study, cognitive technologies (152); robotics, cognitive automation, and cognitive insights (57); cognitive engagement (24); and cognitive insights provided by machine learning differed from those available from traditional analytics in three ways: I they are more data-intensive and detailed; (ii) the models are typically trained on some portion of the data set; and (iii) the models improve. Amelia, a lifelike intelligent-agent avatar, is being used as an internal employee help desk for IT support by SEB bank in Sweden and Becton, Dickinson, and Company in the United States. Such occurrences generate enormous market growth potential.

Key questions covered in this report?

A complete overview of different geographic distributions and common product categories in the Language Processing Market.
When you have information on the cost of production, the cost of products, and the cost of production for future years, you can fix up the developing databases for your industry.
Thorough break-in analysis for new enterprises seeking to enter the Language Processing Market.
Exactly how do the most essential corporations and mid-level companies create cash within the Market?
Conduct a thorough study on the overall state of the Language Processing Market to aid in the selection of product launches and revisions.
Table of Contents

Global Language Processing Market Research Report 2022 - 2029

Chapter 1 Language Processing Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Language Processing Market Forecast

Europe is the second-largest market for natural language processing. It is expected to reach an estimated USD 23 billion by 2030, growing at a CAGR of 26.4%. The region's most important markets are the United Kingdom, Germany, and France. The increased emphasis and spending on IT infrastructure are projected to boost growth in the UK NLP market. Furthermore, the government has placed a high value on new software. France is expanding its focus on artificial intelligence development through regular investments, luring new customers. This is anticipated to influence the country's NLP market growth positively.

Asia-Pacific is the fastest-growing region. The region is seeing an increase in AI and ML technology usage, particularly among SMEs. Asia's voice assistance market is also thriving, and the region is home to many consumer electronics makers, including smart speakers and smartphones. Since many NLP chips and hardware makers are situated in Asia, the businesses' regional supremacy in the global semiconductor sector also helps them achieve a foothold in the NLP market.

y deployment, the global natural language processing market is segmented into On-premise and Cloud. The On-premise occupied the most significant market share and is expected to grow at a CAGR of 23.5% over the forecast period.
By organization size, the global natural language processing market is segmented into Large Organizations and Small & Medium Organizations. Small & Medium Organizations occupy the largest market share, and it is expected to grow at a CAGR of 26% over the forecast period.
By type, the global natural language processing market is segmented into Hardware, Software, and Services. The Hardware segment occupies the largest market share and is expected to grow at a CAGR of 21.9% over the forecast period.
By processing type, the global natural language processing market is segmented into Text, Speech/Voice, and Image. The Text processing segment occupies the most significant market share and is expected to grow at a CAGR of 23.4% over the forecast period.
By end-user, the global natural language processing market is segmented into Education, BFSI, Healthcare, IT & Telecommunication, Retail, Manufacturing, Media & Entertainment, and Others. The IT & Telecommunication segment occupies the largest market share and is expected to grow at a CAGR of 26.1% over the forecast period.

In addition, Social media channel plays a key role for growth of the natural language processing market. Increasing competition in various verticals has led to demand for real-time market insights related to customer demands and other factors. For gaining real-time market insights, it is important for companies to analyze large volumes of unstructured data generated. Natural language processing systems are required to convert the unstructured human language data into machine language and also derive insights from human language with sentiments and emotions. Social media is one of the major platforms, which provides large volume of unstructured data to organizations. Facebook, Twitter, Google+, Pinterest, Instagram, LinkedIn, YouTube etc. are some of the popular social media channels. For example: According to coherent market insights, It is estimated that in every 60 seconds, near about 27,000 videos are streamed on YouTube, around 3 million posts are shared on Facebook, around 430,000 tweets are posted on Twitter, and around 120 new users get registered on LinkedIn. Moreover, the increasing tools for social media analytics also accelerates the demand for NLP. For example: NetBase solution uses natural language processing to analyze social media and other web content.

However, the main hurdles include the need for effective predictive technologies, the need to narrow the gap between machine and man, the implementation of strict government regulations, and fluctuating customer adoption trends, Complexities due to the usage of code-mixed language while implementing NLP solutions. Code-switching or Code-Mixed (CM) language is the alternation of languages within a conversation or utterance and is a common communicative phenomenon that occurs in multilingual communities across the world. Traditionally, CM language has been associated with informal or casual speech. There is evidence that in several societies, such as urban India and Mexico, CM language has become the default code of communication. It has also pervaded written text, especially in computer-mediated communication and social media. NLP tasks, such as normalization, language identification, language modeling, part-of-speech tagging, and dependency parsing, machine translation, and Automatic Speech Recognition (ASR), face issues while working on non-canonical multilingual data in which two or more languages are mixed.

In November 2021, IBM had announced new natural language processing (NLP) enhancements planned for IBM Watson Discovery, and designed to help business users in industries such as financial services, insurance and legal services enhance customer care and accelerate business processes by uncovering insights and synthesizing information from complex documents.

• In May 2021, Verint Intelligent Virtual Assistant (IVA) was recognized in the natural language processing (NLP) product category, as Verint was amongst the winners of Business Intelligence Group's Excellence in Artificial Intelligence Awards.

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