Natural Language Processing (NLP) Market Research Report Information By Technology (Auto-coding, Text analytics, Pattern & Image recognition, and Speech analytics), By Type (Rule-based, Statistical, and Hybrid), By Deployment (On-Cloud and On-Premise), By Service (Integration and Consulting & maintenance), By Vertical (Healthcare, Retail Sector, and Media & Entertainment), And By Region (North America, Europe, Asia-Pacific, And Rest Of The World) – Market Forecast Till 2030.

Natural Language Processing Market Overview

Natural Language Processing Market Size was valued at USD 50.9 billion in 2021. The natural language processing market industry is projected to grow from USD 64.94 Billion in 2022 to USD 357.7 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 27.6% during the forecast period (2024 - 2030).

Key factors that are driving the market growth include increasing adoption of a cloud-based solution, emerging demand for cloud-based solution, and increasing demand for text-based analytics.

Figure 1: Natural Language Processing Market Size, 2022-2030 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

Latest Industry News of Natural Language Processing Market

Users can quickly, safely, and effectively harness potent Large Language Model technologies for social listening, media monitoring, and other consumer intelligence tasks using Converseon's Conversus 5.0, its Leading No Code NLP Platform with LLM and GPT Enhancements, which will be released in March 2023.

This release makes it possible for businesses to more quickly and successfully use these technologies to meet their consumer and intelligence objectives, including social listening, media monitoring, reputation management, customer experience (CX) evaluation, and brand tracking.

In the upcoming years, market growth is anticipated to be driven by the introduction of newer, more useful items that will increase consumer interest in them.

NLP Market Trends

Rising adoption of cloud-based NLP and AI-based software among small & medium businesses to aid market growth

Organizations are adopting cloud-based NLP solutions to reduce the time required for the collection of insightful data and processing. Chabots and voice search natural language processing technology collect data using various AI-powered and cloud-based tools such as interactive voice recognition systems. This data helps process various predictive and market analyses for a particular product.

On the other hand, technological advancement in AI has drastically transformed Big Data analytics and has driven efficient services by automating time-consuming data collection tasks. Several leading players are launching AI-based software tools for automating businesses around the globe. For instance, in July 2022, SecureKloud Technologies introduced DataEdge, a cloud-based and AI-powered data analytics platform that enables organizations to power insights for decision-making. Rising cloud transformation solutions with the DataEdge platform provide scalable, highly modular, and API-driven solutions for unlocking data-powered insights.

Natural Language Processing Market Industry News

May 2023- Large Language Models are now supported by Argilla, an open-source data curation tool. In order to assist users in completing the whole lifecycle of creating, assessing, and enhancing Natural Language Processing Models—from the early experimental stage to deployment in production environments—Argilla has been made available. Through faster data curation, this technology leverages both human and machine input to create some solid LLMs.

Argilla supports the user at every stage of MLOps cycle, from model monitoring through data labeling. Data annotation and labeling are essential steps in the training of supervised NLP models because they provide high-quality labeled datasets from the annotation and labeling of raw textual data. On the contrary, model monitoring is indeed an essential phase that keeps the model's dependability and consistency by continuously observing the performance and behavior of deployed models.

Since Argilla is open-source software, anybody can use and alter it at no cost. Hugging Face Transformers, Stanford Stanza, Flair, spaCy, and other popular NLP libraries are supported, and users may mix their favorite libraries without developing a specific interface. By covering the gap between model iteration, data collection, and production monitoring, Argilla offers an end-to-end solution for ML model development. By designing a user-friendly setting where domain specialists can quickly read, annotate, and experiment with data and engineers have total control over the data pipelines, Argilla focuses on the user and developer experience. Argilla offers a variety of cutting-edge data annotation techniques, going beyond conventional hand-labeling operations.

In addition to supporting data curation, assessment, model monitoring, debugging, & explainability, Argilla is a framework that is ready for production. It streamlines tool integration and automates operations involving humans in the loop. The Docker command "docker run -d -name argilla -p 6900:6900 argilla/argilla-quickstart:latest" may be used to locally install it on the device.

Natural Language Processing Market Segment Insights

Natural Language Processing Technology Insights

Based on the technology, the natural language processing (NLP) market segmentation includes auto-coding, text analytics, pattern & image recognition, and speech analytics. The auto-coding segment held the majority share in 2021, accounting for approximately 51-55% of the natural language processing market revenue. As natural language processing assists compliance teams in analyzing and identifying critical information stored in structured data and uncovering anomalies and hidden patterns from massive datasets with the help of topic tagging, sentiment analysis, and other techniques, NLP tools are also being used more and more in risk and threat detection activities.

Natural Language Processing Type Insights

Based on type, the natural language processing market segment includes rule-based, statistical, and hybrid. In 2021, the statistical segment held the highest market revenue share. Pattern matching, a highly valuable skill in the healthcare sector, is the main emphasis of rule-based NLP. The technique is useful for the healthcare sector since it enhances the electronic health record (EHR) process by facilitating the discovery of arbitrary phrases and enhancing data management effectiveness.

Natural Language Processing Service Insights

The natural language processing (NLP) market segmentation, based on the service, includes integration and consulting & maintenance. The integration segment had the highest market revenue share in 2021. The engines, platforms, tools, and interfaces that make up an NLG program process the translation of computer code into a language that is intelligible by humans. Deep learning is used by data analysis scientists as well as non-technical persons to analyze information and data. Natural language processing software also aids in producing actionable insights based on digital data. With accelerating software implementation, lowering deployment costs & risks, maximizing the value of existing installations by optimizing them, and other associated factors, the service segment is expanding at a substantial CAGR during the forecast period.

The service segment consists of a range of services offered to businesses that use tools for generating natural language. The demand for these services is projected to increase significantly with the increased use of natural language generation software across various industries since they help businesses implement and utilize natural language generation tools effectively and utilize the full potential of the software.

Natural Language Processing Deployment Insights

Based on the deployment, the natural language processing market segment includes on-premise and on-demand. On-premise dominated the market in 2021 and is expected to be the fastest-growing segment during the forecast period of 2022-2030. The on-premises NLP deployment offers full control, visibility, and authentication security controls over data. In addition, it is easier to scale to match corporate demand and improve efficiency with built-in redundancy. The increased adoption of cloud-based NLP is anticipated to fuel the expansion of the market. The cloud segment is expected to experience the fastest growth over the forecast period.

Figure 2: Natural Language Processing Market, By Deployment, 2022 & 2030 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

Natural Language Processing Vertical Insights

Based on vertical, the natural language processing (NLP) market segment includes healthcare, retail sector, and media & entertainment. Healthcare dominated the market in 2021 and is expected to be the fastest-growing segment during the forecast period of 2022-2030. The leading share is attributable to the increasing adoption of advanced technologies and software such as predictive analytics, NLP tools, automation tools, and cloud-based software in the healthcare sector. Healthcare researchers can monitor prominent online comment boards to understand consumer apprehensions during the COVID-19 pandemic.

Natural Language Processing Regional Insights

By Region, the study provides market insights into North America, Europe, Asia-Pacific, and the Rest of the World. The North American natural language processing (NLP) market is anticipated to expand at a significant CAGR during the study period, accounting for USD 21.68 billion in 2021. The region dominates AI and machine learning technologies, making it one of the key marketplaces for natural language processing technologies. Further, the prevalence of key market participants in the U.S. drives innovation in the region subsequently fueling the natural language processing market growth. Regional governments are also increasingly encouraging the use of AI, ML, and NLP technologies, which is allowing market participants to expand their presence in the region.

Figure 3: Natural Language Processing Market Share By Region 2022 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

The European natural language processing market is the world's second-largest due to the rising cloud computing adoption among enterprises in Europe. According to the European Commission Organization, around 42% of European enterprises have adopted cloud-based services in 2021 and are proliferating. Such an increase in the adoption of cloud services is expected to strengthen the market growth. The improved focus and increased spending on IT infrastructure are expected to drive the growth of the NLP market in the UK. The government has also laid high emphasis on new software. France is increasing its focus on developing artificial intelligence through regular investments, attracting new consumers. This will likely have a positive impact on the growth of the NLP market.

Moreover, companies such as Facebook and Google are planning to invest in expanding and creating new facilities related to AI in Paris, bolstering the adoption of NLP. Further, the German NLP market held the largest market share, and the France natural language processing (NLP) market was the fastest-growing market in the European region.

The Asia Pacific natural language processing market is expected to grow at the fastest rate of CAGR during the forecast period. The growth is attributable to increasing smartphone usage, rapid technological advancements, the digitalization of economies, and government initiatives in developing countries from the region. Furthermore, this region holds leading positions in cutting-edge industries like robotics and has a strong IT infrastructure, software, and service offerings. These factors would create profitable growth prospects for the market. The regional dominance in the semiconductor industry also helps the companies gain a position in the NLP market, as many NLP chips and hardware manufacturers are Asia-based. Moreover, China’s natural language processing market held the largest market share, and the Indian NLP market was the fastest-growing market in the Asia-Pacific region.

Natural Language Processing (NLP) Key Market Players & Competitive Insights

The key industry vendors focus on the expansion of their consumer base to obtain a competitive advantage. Therefore, key companies take several strategic actions, including mergers & acquisitions, new product/technology development partnerships, and collaborations. Stakeholders can also emphasize product differentiation and technological advancements. Intensive efforts on organic and inorganic growth strategies are likely to help companies expand their penetration across untapped areas.

SAP SE is a European multinational software company based in Walldorf, Baden-Württemberg. It develops enterprise software to manage business operations and customer relations. The company is the world's leading enterprise resource planning software vendor. In July 2022, SAP SE acquired Askdata, a data interaction, and collaboration platform. The key objective of the acquisition is to assist consumers in making appropriate choices with AI-driven natural language searches.

Key Companies in the NLP market include

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  IBM (US)

  
  


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  HP (US)

  
  


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  Oracle (US)

  
  


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  Microsoft (US)

  
  


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  Apple (US)

  
  


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  Netbase Solutions (US)

  
  

Natural Language Processing Industry Developments

December 2023:

GPT-4 Turbo with Vision, a large multimodal model, is available on Azure OpenAI, enabling image analysis with textual responses. Enhanced features include Optical Character Recognition and video prompt support. REST API allows direct calls to the chat API. Azure OpenAI now supports full VPN and private endpoint protection, including for storage and AI Search resources, ensuring secure data usage.

March 2023:

Baidu introduced ERNIE Bot, a knowledge-enhanced LLM, showcasing its abilities in literary creation, business writing, math, Chinese language understanding, and multi-modal generation. ERNIE Bot integrates supervised fine-tuning, reinforcement learning, prompt learning, and knowledge enhancement for comprehensive functionality.

April 2023:

Generative AI is reshaping industries, with a focus on ML's pivotal role in fostering innovation. Amazon's strides in democratizing ML are showcased, notably through services like Amazon Bedrock. Also, infrastructure improvements like Amazon EC2 Trn1n instances and EC2 Inf2 instances, optimized for generative AI, are highlighted. Lastly, Amazon Code Whisperer, an AI coding tool aiding developer productivity, is introduced, offering code suggestions based on natural language cues and prior code.

May 2023:

Google's next-gen language model offers enhanced multilingual, reasoning, and coding capabilities. Available in four sizes, from Gecko to Unicorn, it powers over 25 Google products, including Workspace features and Med-PaLM 2 for medical insights. Sec-PaLM enhances cybersecurity, while the PaLM API enables developers to leverage its capabilities responsibly. Gemini, our upcoming model, promises groundbreaking multimodal capabilities for future innovation.

Natural Language Processing Market Segmentation

NLP Technology Outlook

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  Auto-coding

  
  


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  Text analytics

  
  


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  Pattern & Image recognition

  
  


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  Speech analytics

  
  

NLP Deployment Outlook

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  On-Cloud

  
  


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  On-Premises

  
  

NLP Type Outlook

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  Rule-based

  
  


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  Statistical

  
  


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  Hybrid

  
  

NLP Service Outlook

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  Integration

  
  


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  Consulting & maintenance

  
  

NLP Vertical Outlook

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  Healthcare

  
  


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  Retail Sector

  
  


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  Media & Entertainment

  
  

Natural Language Processing Regional Outlook