한글목차

세계의 자연어 처리(NLP) 시장 규모는 2024년에 28억 2,600만 달러로 추정되며, 2025년부터 2031년까지 예측 기간 동안 CAGR 10.6%로 성장하여 2031년까지 57억 6,900만 달러로 확대될 것으로 예측됩니다.

자연어 처리(NLP)는 자바나 C++ 등의 인공언어가 아닌 자연어(구어 또는 문어 데이터)를 이용한 컴퓨터와 인간의 상호작용을 다루는 인공지능의 한 분야입니다.

세계 자연어 처리(NLP) 시장의 주요 기업으로는 3M, Linguamatics, Amazon AWS 등이 있습니다. 세계 상위 3개 업체가 약 35%의 점유율을 차지하고 있습니다. 미국이 가장 큰 시장이며, 약 65%의 점유율을 가지고 있습니다. 이어 유럽과 중국이 각각 약 25%의 점유율을 차지하고 있습니다. 제품별로는 기계 번역이 가장 큰 부문으로 약 45%의 점유율을 차지하고 있습니다. 또한, 용도별로는 전자건강기록(EHR)이 가장 큰 용도이며, 그 다음으로 컴퓨터 지원 코딩(CAC)이 그 뒤를 잇습니다.

이 보고서는 자연어 처리(NLP) 세계 시장에 대해 총 매출액, 주요 기업의 시장 점유율 및 순위에 초점을 맞추고 지역/국가, 유형 및 최종사용자별 분석을 종합적으로 제시하는 것을 목적으로 합니다.

자연어 처리(NLP) 시장의 규모, 추정 및 예측은 매출액 기준으로 제시되며, 2024년을 기준 연도로 하여 2020년부터 2031년까지의 과거 데이터와 예측 데이터를 포함합니다. 정량적 분석과 정성적 분석을 통해 독자들이 비즈니스/성장 전략을 수립하고, 시장 경쟁 상황을 평가하고, 현재 시장에서의 포지셔닝을 분석하고, 자연어 처리(NLP)에 대한 정보에 입각한 비즈니스 의사결정을 내릴 수 있도록 돕습니다.

시장 세분화

기업별

• Microsoft
• IBM
• Solventum
• Amazon AWS
• SAS
• Google
• Appen
• Dolbey Systems
• Linguamatics
• Verint Systems
• Quid
• HPE
• Baidu
• Huawei

유형별 부문

• 기계 번역
• 정보 추출
• 텍스트 및 음성 처리
• 기타

최종사용자별 부문

• 대기업
• 중소기업

지역별

• 북미
  • 미국
  • 캐나다
• 아시아태평양
  • 중국
  • 일본
  • 한국
  • 동남아시아
  • 인도
  • 호주
  • 기타 아시아태평양
• 유럽
  • 독일
  • 프랑스
  • 영국
  • 이탈리아
  • 네덜란드
  • 북유럽 국가
  • 기타 유럽
• 라틴아메리카
  • 멕시코
  • 브라질
  • 기타 라틴아메리카
• 중동 및 아프리카
  • 튀르키예
  • 사우디아라비아
  • 아랍에미리트
  • 기타 중동 및 아프리카

영문목차

The global market for Natural Language Processing (NLP) was estimated to be worth US$ 2826 million in 2024 and is forecast to a readjusted size of US$ 5769 million by 2031 with a CAGR of 10.6% during the forecast period 2025-2031.

Natural language processing (NLP) is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language (spoken or written data), not in the artificial languages such as Java and C++.

Global Natural Language Processing (NLP) key players include 3M, Linguamatics, Amazon AWS, etc. Global top three manufacturers hold a share about 35%. United States is the largest market, with a share about 65%, followed by Europe and China, both have a share about 25 percent. In terms of product, Machine Translation is the largest segment, with a share about 45%. And in terms of application, the largest application is Electronic Health Records (EHR), followed by Computer-Assisted Coding (CAC).

This report aims to provide a comprehensive presentation of the global market for Natural Language Processing (NLP), focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Natural Language Processing (NLP) by region & country, by Type, and by End User.

The Natural Language Processing (NLP) market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Natural Language Processing (NLP).

Market Segmentation

By Company

• Microsoft
• IBM
• Solventum
• Amazon AWS
• SAS
• Google
• Appen
• Dolbey Systems
• Linguamatics
• Verint Systems
• Quid
• HPE
• Baidu
• Huawei

Segment by Type

• Machine Translation
• Information Extraction
• Text and Voice Processing
• Others

Segment by End User

• Large Enterprises
• Small and Medium Enterprises

By Region

• North America
  • United States
  • Canada
• Asia-Pacific
  • China
  • Japan
  • South Korea
  • Southeast Asia
  • India
  • Australia
  • Rest of Asia-Pacific
• Europe
  • Germany
  • France
  • U.K.
  • Italy
  • Netherlands
  • Nordic Countries
  • Rest of Europe
• Latin America
  • Mexico
  • Brazil
  • Rest of Latin America
• Middle East & Africa
  • Turkey
  • Saudi Arabia
  • UAE
  • Rest of MEA

Chapter Outline

Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 2: Detailed analysis of Natural Language Processing (NLP) company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.

Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 4: Provides the analysis of various market segments by End User, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 5: Revenue of Natural Language Processing (NLP) in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.

Chapter 6: Revenue of Natural Language Processing (NLP) in country level. It provides sigmate data by Type, and by End User for each country/region.

Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.

Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.

Chapter 9: Conclusion.

Table of Contents

1 Market Overview

• 1.1 Natural Language Processing (NLP) Product Introduction
• 1.2 Global Natural Language Processing (NLP) Market Size Forecast (2020-2031)
• 1.3 Natural Language Processing (NLP) Market Trends & Drivers
  • 1.3.1 Natural Language Processing (NLP) Industry Trends
  • 1.3.2 Natural Language Processing (NLP) Market Drivers & Opportunity
  • 1.3.3 Natural Language Processing (NLP) Market Challenges
  • 1.3.4 Natural Language Processing (NLP) Market Restraints
• 1.4 Assumptions and Limitations
• 1.5 Study Objectives
• 1.6 Years Considered

2 Competitive Analysis by Company

• 2.1 Global Natural Language Processing (NLP) Players Revenue Ranking (2024)
• 2.2 Global Natural Language Processing (NLP) Revenue by Company (2020-2025)
• 2.3 Key Companies Natural Language Processing (NLP) Manufacturing Base Distribution and Headquarters
• 2.4 Key Companies Natural Language Processing (NLP) Product Offered
• 2.5 Key Companies Time to Begin Mass Production of Natural Language Processing (NLP)
• 2.6 Natural Language Processing (NLP) Market Competitive Analysis
  • 2.6.1 Natural Language Processing (NLP) Market Concentration Rate (2020-2025)
  • 2.6.2 Global 5 and 10 Largest Companies by Natural Language Processing (NLP) Revenue in 2024
  • 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Natural Language Processing (NLP) as of 2024)
• 2.7 Mergers & Acquisitions, Expansion

3 Segmentation by Type

• 3.1 Introduction by Type
  • 3.1.1 Machine Translation
  • 3.1.2 Information Extraction
  • 3.1.3 Text and Voice Processing
  • 3.1.4 Others
• 3.2 Global Natural Language Processing (NLP) Sales Value by Type
  • 3.2.1 Global Natural Language Processing (NLP) Sales Value by Type (2020 VS 2024 VS 2031)
  • 3.2.2 Global Natural Language Processing (NLP) Sales Value, by Type (2020-2031)
  • 3.2.3 Global Natural Language Processing (NLP) Sales Value, by Type (%) (2020-2031)

4 Segmentation by End User

• 4.1 Introduction by End User
  • 4.1.1 Large Enterprises
  • 4.1.2 Small and Medium Enterprises
• 4.2 Global Natural Language Processing (NLP) Sales Value by End User
  • 4.2.1 Global Natural Language Processing (NLP) Sales Value by End User (2020 VS 2024 VS 2031)
  • 4.2.2 Global Natural Language Processing (NLP) Sales Value, by End User (2020-2031)
  • 4.2.3 Global Natural Language Processing (NLP) Sales Value, by End User (%) (2020-2031)

5 Segmentation by Region

• 5.1 Global Natural Language Processing (NLP) Sales Value by Region
  • 5.1.1 Global Natural Language Processing (NLP) Sales Value by Region: 2020 VS 2024 VS 2031
  • 5.1.2 Global Natural Language Processing (NLP) Sales Value by Region (2020-2025)
  • 5.1.3 Global Natural Language Processing (NLP) Sales Value by Region (2026-2031)
  • 5.1.4 Global Natural Language Processing (NLP) Sales Value by Region (%), (2020-2031)
• 5.2 North America
  • 5.2.1 North America Natural Language Processing (NLP) Sales Value, 2020-2031
  • 5.2.2 North America Natural Language Processing (NLP) Sales Value by Country (%), 2024 VS 2031
• 5.3 Europe
  • 5.3.1 Europe Natural Language Processing (NLP) Sales Value, 2020-2031
  • 5.3.2 Europe Natural Language Processing (NLP) Sales Value by Country (%), 2024 VS 2031
• 5.4 Asia Pacific
  • 5.4.1 Asia Pacific Natural Language Processing (NLP) Sales Value, 2020-2031
  • 5.4.2 Asia Pacific Natural Language Processing (NLP) Sales Value by Region (%), 2024 VS 2031
• 5.5 South America
  • 5.5.1 South America Natural Language Processing (NLP) Sales Value, 2020-2031
  • 5.5.2 South America Natural Language Processing (NLP) Sales Value by Country (%), 2024 VS 2031
• 5.6 Middle East & Africa
  • 5.6.1 Middle East & Africa Natural Language Processing (NLP) Sales Value, 2020-2031
  • 5.6.2 Middle East & Africa Natural Language Processing (NLP) Sales Value by Country (%), 2024 VS 2031

6 Segmentation by Key Countries/Regions

• 6.1 Key Countries/Regions Natural Language Processing (NLP) Sales Value Growth Trends, 2020 VS 2024 VS 2031
• 6.2 Key Countries/Regions Natural Language Processing (NLP) Sales Value, 2020-2031
• 6.3 United States
  • 6.3.1 United States Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.3.2 United States Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.3.3 United States Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.4 Europe
  • 6.4.1 Europe Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.4.2 Europe Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.4.3 Europe Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.5 China
  • 6.5.1 China Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.5.2 China Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.5.3 China Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.6 Japan
  • 6.6.1 Japan Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.6.2 Japan Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.6.3 Japan Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.7 South Korea
  • 6.7.1 South Korea Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.7.2 South Korea Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.7.3 South Korea Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.8 Southeast Asia
  • 6.8.1 Southeast Asia Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.8.2 Southeast Asia Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.8.3 Southeast Asia Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031
• 6.9 India
  • 6.9.1 India Natural Language Processing (NLP) Sales Value, 2020-2031
  • 6.9.2 India Natural Language Processing (NLP) Sales Value by Type (%), 2024 VS 2031
  • 6.9.3 India Natural Language Processing (NLP) Sales Value by End User, 2024 VS 2031

7 Company Profiles

• 7.1 Microsoft
  • 7.1.1 Microsoft Profile
  • 7.1.2 Microsoft Main Business
  • 7.1.3 Microsoft Natural Language Processing (NLP) Products, Services and Solutions
  • 7.1.4 Microsoft Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.1.5 Microsoft Recent Developments
• 7.2 IBM
  • 7.2.1 IBM Profile
  • 7.2.2 IBM Main Business
  • 7.2.3 IBM Natural Language Processing (NLP) Products, Services and Solutions
  • 7.2.4 IBM Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.2.5 IBM Recent Developments
• 7.3 Solventum
  • 7.3.1 Solventum Profile
  • 7.3.2 Solventum Main Business
  • 7.3.3 Solventum Natural Language Processing (NLP) Products, Services and Solutions
  • 7.3.4 Solventum Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.3.5 Solventum Recent Developments
• 7.4 Amazon AWS
  • 7.4.1 Amazon AWS Profile
  • 7.4.2 Amazon AWS Main Business
  • 7.4.3 Amazon AWS Natural Language Processing (NLP) Products, Services and Solutions
  • 7.4.4 Amazon AWS Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.4.5 Amazon AWS Recent Developments
• 7.5 SAS
  • 7.5.1 SAS Profile
  • 7.5.2 SAS Main Business
  • 7.5.3 SAS Natural Language Processing (NLP) Products, Services and Solutions
  • 7.5.4 SAS Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.5.5 SAS Recent Developments
• 7.6 Google
  • 7.6.1 Google Profile
  • 7.6.2 Google Main Business
  • 7.6.3 Google Natural Language Processing (NLP) Products, Services and Solutions
  • 7.6.4 Google Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.6.5 Google Recent Developments
• 7.7 Appen
  • 7.7.1 Appen Profile
  • 7.7.2 Appen Main Business
  • 7.7.3 Appen Natural Language Processing (NLP) Products, Services and Solutions
  • 7.7.4 Appen Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.7.5 Appen Recent Developments
• 7.8 Dolbey Systems
  • 7.8.1 Dolbey Systems Profile
  • 7.8.2 Dolbey Systems Main Business
  • 7.8.3 Dolbey Systems Natural Language Processing (NLP) Products, Services and Solutions
  • 7.8.4 Dolbey Systems Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.8.5 Dolbey Systems Recent Developments
• 7.9 Linguamatics
  • 7.9.1 Linguamatics Profile
  • 7.9.2 Linguamatics Main Business
  • 7.9.3 Linguamatics Natural Language Processing (NLP) Products, Services and Solutions
  • 7.9.4 Linguamatics Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.9.5 Linguamatics Recent Developments
• 7.10 Verint Systems
  • 7.10.1 Verint Systems Profile
  • 7.10.2 Verint Systems Main Business
  • 7.10.3 Verint Systems Natural Language Processing (NLP) Products, Services and Solutions
  • 7.10.4 Verint Systems Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.10.5 Verint Systems Recent Developments
• 7.11 Quid
  • 7.11.1 Quid Profile
  • 7.11.2 Quid Main Business
  • 7.11.3 Quid Natural Language Processing (NLP) Products, Services and Solutions
  • 7.11.4 Quid Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.11.5 Quid Recent Developments
• 7.12 HPE
  • 7.12.1 HPE Profile
  • 7.12.2 HPE Main Business
  • 7.12.3 HPE Natural Language Processing (NLP) Products, Services and Solutions
  • 7.12.4 HPE Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.12.5 HPE Recent Developments
• 7.13 Baidu
  • 7.13.1 Baidu Profile
  • 7.13.2 Baidu Main Business
  • 7.13.3 Baidu Natural Language Processing (NLP) Products, Services and Solutions
  • 7.13.4 Baidu Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.13.5 Baidu Recent Developments
• 7.14 Huawei
  • 7.14.1 Huawei Profile
  • 7.14.2 Huawei Main Business
  • 7.14.3 Huawei Natural Language Processing (NLP) Products, Services and Solutions
  • 7.14.4 Huawei Natural Language Processing (NLP) Revenue (US$ Million) & (2020-2025)
  • 7.14.5 Huawei Recent Developments

8 Industry Chain Analysis

• 8.1 Natural Language Processing (NLP) Industrial Chain
• 8.2 Natural Language Processing (NLP) Upstream Analysis
  • 8.2.1 Key Raw Materials
  • 8.2.2 Raw Materials Key Suppliers
  • 8.2.3 Manufacturing Cost Structure
• 8.3 Midstream Analysis
• 8.4 Downstream Analysis (Customers Analysis)
• 8.5 Sales Model and Sales Channels
  • 8.5.1 Natural Language Processing (NLP) Sales Model
  • 8.5.2 Sales Channel
  • 8.5.3 Natural Language Processing (NLP) Distributors

9 Research Findings and Conclusion

10 Appendix

• 10.1 Research Methodology
  • 10.1.1 Methodology/Research Approach
    • 10.1.1.1 Research Programs/Design
    • 10.1.1.2 Market Size Estimation
    • 10.1.1.3 Market Breakdown and Data Triangulation
  • 10.1.2 Data Source
    • 10.1.2.1 Secondary Sources
    • 10.1.2.2 Primary Sources
• 10.2 Author Details
• 10.3 Disclaimer