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Natural Language Processing (NLP) Market worth $68.1 billion by 2028 - Exclusive Report by MarketsandMarkets™
[September 22, 2023]

Natural Language Processing (NLP) Market worth $68.1 billion by 2028 - Exclusive Report by MarketsandMarkets™

CHICAGO, Sept. 22, 2023 /PRNewswire/ -- The deep integration of NLP with AI, enhanced comprehension of human language, and proliferation of applications across numerous industries will define the NLP market's future. In the digital age, NLP will continue to be a transformational force in improving decision-making, automation, and communication.

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The Natural Language Processing Market is estimated to grow from USD 18.9 billion in 2023 to USD 68.1 billion by 2028, at a CAGR of 29.3% during the forecast period, according to a new report by MarketsandMarkets™. Natural Language Processing (NLP) refers to the branch of computer science, specifically the branch of Artificial Intelligence (AI), concerned with giving computers the ability to understand text and spoken words in much the same way human beings can. NLP drives computer programs that translate text from one language to another, respond to spoken commands, and quickly summarize large volumes of text—even in real time.

Browse in-depth TOC on "Natural Language Processing (NLP) Market"
377 - Tables
73 - Figures
431 - Pages

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Scope of the Report

Report Metrics


Market size available for years


Base year considered


Forecast period


Forecast units

USD Billion

Segments covered

Offering (Solutions – [Deployment Mode], Services), Type, Application, Technology, Vertical, and Region

Geographies covered

North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

Companies covered

IBM (US), Microsoft (US), Google (US), AWS (US), Meta (US), 3M (US), Baidu (China), Apple (US), SAS Institute (US), IQVIA (UK), Oracle (US), Salesforce (US), OpenAI (US), Inbenta (US), LivePerson (US), SoundHound AI (US), MindMeld (US), Veritone (US), Dolbey (US), Automated Insights (US), Bitext (US), Conversica (US), UiPath (US), Addepto (US), RaGaVeRa (India), (US), Eigen (US), (India), Crayon Data (Singapore), Narrativa (US), deepset (US), Ellipsis Health (US), DheeYantra (US), (US), Rasa (US), MonkeyLearn (US), TextRazor (England), and Cohere (Canada).

Services segment to account for higher CAGR during the forecast period

NLP market relies heavily on its services segment to achieve effective software operations. To increase the efficiency of the entire process, managed and professional services are installed, which are the services considered in this report. Companies such as Microsoft, IBM, and SAS Institute have started providing platforms for embedding NLP technologies. These platforms can be coded across various programming languages. Major players like Microsoft have formed partnerships with SMBs that develop speech-to-text software, making them available across their integrated platforms. For example, AWS offers an Amazon Comprehend service that uses machine learning for extracting key phrases and identifying the language in each text. Amazon Comprehend works seamlessly with any AWS-supported application and offers useful features such as sentiment analysis, tokenization, and automated text file organization.

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Cloud segment is expected to hold the largest market size for the year 2023

Organizations can reap numerous benefits by deploying their systems on the cloud. These benefits include easy availability, scalability, reduced operational costs, and hassle-free deployments. AI platform providers are focusing on developing robust cloud-based deployment solutions for their clients, as many organizations have migrated to either private or public cloud. This mode of deployment offers additional flexibility for business operations and real-time deployment ease to companies implementing real-time analytics. The cloud-based deployment of NLP has made it easy for users to apply predictive capabilities to the entire organization. The major vendors offering cloud-based NLP solutions are IBM, Microsoft, AWS, and Google.

The healthcare and life sciences vertical is projected to grow at the highest CAGR during the forecast period

In the healthcare industry, accuracy and efficiency are crucial because they directly impact human health. Therefore, the margin of error must be close to zero. Natural Language Processing (NLP) offers several applications and use cases that address healthcare challenges. NLP technologies are revolutionizing the healthcare sector by automating the tedious task of transcribing notes from clinical staff, extracting essential information, and enabling clinicians to refine their problem list. With the help of NLP tools, clinicians can quickly filter relevant clinical data from unstructured patient-related documentation, flag any necessary updates, and cross-reference the same with the current problem list. The adoption of Electronic Health Records (EHRs) has increased the demand for NLP solutions in the healthcare sector. NLP solutions are readily implemented in EHRs to convert free text conversations into insights, thereby bridging the gap between complex medical terms and patients' understanding of their health. This helps improve patient interactions, and, in turn, the quality of patient care. NLP solutions also aid in identifying gaps in physicians' performance and potential errors in care delivery, thereby contributing to value-based reimbursements.

Top Key Companies in Natural Language Processing (NLP) Market:

The report profiles key players such as IBM (US), Microsoft (US), Google (US), AWS (US), Meta (US) and 3M (US).

Recent Developments:

  • In August 2023, Meta introduced SeamlessM4T, a groundbreaking AI translation model that stands as the first to offer comprehensive multimodal and multilingual capabilities. This innovative model empowers individuals to communicate across languages through both speech and text effortlessly. Its impressive features include speech recognition for nearly 100 languages, speech-to-text translation for nearly 100 input and output languages, and speech-to-speech translation supporting almost 100 input languages and 36 output languages (including English).
  • In August 2023, Google Cloud announced a partnership with AI21 Labs, an Israeli startup revolutionizing reading and writing through generative AI and large language models (LLMs). AI21 Labs utilizes Google Cloud's specialized AI/ML infrastructure to expedite model training and inferencing. This partnership enables customers to seamlessly integrate industry-specific generative AI capabilities through BigQuery connectors and functions.
  • In March 2023, Baidu unveiled ERNIE Bot, its latest innovation in generative AI, featuring a knowledge-enhanced LLM. This cutting-edge technology can understand human intentions and provide precise, coherent, and fluent responses that approach human-level comprehension and communication.
  • In February 2022, SoundHound AI expanded its partnership with Snap to offer automatic captioning for Snapchat videos. By utilizing SoundHound's Automatic Speech Recognition (ASR) software, Snapchatters can easily generate transcriptions of the audio content in their Snaps in real time. This feature enhances the accessibility and user experience for individuals who may prefer or require captions while viewing videos on the platform.
  • In February 2022, Meta announced its latest innovation, the Universal Speech Translator, where Meta is designing novel approaches to translating from a speech in one language to another in real time so it can support languages without a standard writing system as well as those that are both written and spoken.

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Natural Language Processing (NLP) Market Advantages:

  • Improved user experiences in chatbots, virtual assistants, and voice-activated gadgets are made possible by NLP, which enables more natural and intuitive interactions between people and computers.
  • Organisations can use NLP to extract useful insights from unstructured text data, including customer reviews, social media posts, and news articles.
  • NLP increases operational efficiency by automating time-consuming processes like content categorization, sentiment analysis, and language translation.
  • NLP algorithms enhance user engagement and happiness by customising information, recommendations, and user experiences based on individual preferences.
  • Search engines that use NLP produce more precise, contextually appropriate search results, which enhance information retrieval.
  • Language barriers are eliminated thanks to NLP, which also makes it possible for businesses to grow internationally and communicate with more people.
  • NLP-driven chatbots and virtual assistants provide round-the-clock customer service, quickly answering questions and problems to increase client satisfaction.
  • NLP analyses sentiment in reviews, social media, and consumer feedback to assist businesses understand public opinion and adjust their plans.
  • By examining patterns and abnormalities in text data, NLP can spot fraudulent activity, boosting the security of online interactions and financial transactions.

Report Objectives

  • To define, describe, and predict the Natural Language Processing (NLP) Market by offering (solutions and services), type, application, technology, organization size, vertical, and region
  • To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
  • To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
  • To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
  • To profile key players and comprehensively analyze their market rankings and core competencies
  • To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the NLP market

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