Global Machine Translation Market Size, Share, Opportunities, And Trends By Technology (Statistical Machine Translation, Rule-Based Machine Learning, Hybrid Machine Translation, Neural Machine Translation), By End-User (Automotive & Transportation, Electrical & Electronics, Military & Defense, Healthcare, Information Technology, Others), And By Geography - Forecasts From 2025 To 2030

The global machine translation market is projected to grow at a CAGR of 18.77% between 2025 to 2030.

Machine translation (MT) is an automated translation process in which computer software is used to translate a text from one natural language, text, and image to another without human intervention. As it is constantly evolving, especially in terms of accuracy levels in its output, it is being increasingly employed in more areas of business, introducing new applications and improved machine-learning models. The uses of Machine Translation can be broadly divided into two categories- business use (government, software & technologies, healthcare, e-commerce, etc) and consumer use (text-to-speech, text-to-text, speech-to-text, etc).

The machine translation market is witnessing massive growth due to the increasing use of computer-assisted tools. This continuous increase can be ascribed to the rise of economies and the internationalization of businesses that provides their content, products, and services in as many languages as possible. This prompted translation companies to rely increasingly on machine translation as a tool. 

By technology, Neural Machine Translation is relatively newer but promises a strong growth rate. The neural technology has been employed by companies like Google Inc and IBM Corporations. Statistical Translations, Rule-based Translation, and Hybrid-translations are the pioneer technologies. They are constantly evolving and retain a significant share.  By end-user, healthcare and education are the newly emerging sector while all other sectors continue to grow.  Geographically, North America accounts for the largest market share, with the Asia-Pacific region growing at a very fast pace, especially in China and South Korea.  

Growth Factors.

• Multi-faceted uses.

The use of machine translation ranges from automotive, military, defence, healthcare, and education to e-commerce. They are some of the primary end-user of the industry. As thousands of languages are used across the world, the military and defense segment demands the quick translation of high-volume content, to communicate with multilingual populations on a real-time basis making it a useful tool. The automotive industry uses it for technical manuals, training manuals, and human-machine interfaces. It is one of the most widely used technology in artificial intelligence (AI)- based vehicles. AI and machine translation often go hand in hand. The education sector uses MT for the analytical and customizable imparting of knowledge. The increasing abundance of online learning platforms like Coursera, Byjus, etc imparts various types of courses which include several language options.

The learner can choose one based on their ease. Healthcare professionals make use of machine translation to interact with patients across the globe. It can be used to clarify patient histories, review a clinical diagnosis, or restate the recommended treatment plan and follow-up to facilitate comprehension. It is a powerful enabler for assistive technology, for people with visual, speech, hearing, motor, or cognitive disabilities. The e-commerce giants like Amazon, and Alibaba uses this technology to ease consumer experiences wherein they can buy in their native languages. The e-commerce sector is also using image-to-text translation extensively where the user can buy an item based on a photograph. Machine translation has also seeped its way into the OTT platforms which provide streaming services in a variety of languages. Thus, the uses of machine translation are eternally rising. This has led to a massive market for the technology.

• Cost-effective and high-speed translation.

The growing need for cost-effective and high-speed translation is another key factor augmenting the growth of the machine translation market. Companies expect translation services to become more affordable. These cost reductions will enable companies to increase the number of markets they target and help them get products to these markets faster. It also helps save translators time, therefore providing quick, accurate translations. These efficient solutions are employed by several industries at a minimal cost which boosts the translation market.

Impact of COVID-19 on the Machine Translation Market

With the outbreak of the Covid-19 pandemic, the government has imposed several restrictions and lockdowns. This has led to a negative impact on the production, distribution, and consumption of several sectors. However, certain sectors realized positive market growth and machine translation is one of them. The application of machine translation in education, healthcare, and e-commerce industries has increased manifold. As educational institutes remain close in several nations, there is increasing adoption of digital learning approaches. The translation facilities are used for both course-based and co-curricular learning activities. There has also been a sudden surge in the e-commerce and healthcare sector due to the pandemic. These two sectors employ machine translation extensively in their services which has led to further improvement and precision of the translating services. The machine translation market is one of the very few industries to witness an expansion in the market despite the pessimistic impacts.

Competitive Insights.

The market leaders for the Global Machine Translation Market are Google Inc., IBM Corporation, Microsoft Corporation, RWS Holdings PLC, Omniscien Technologies, Pangeanic, SDL PLC, and CSLi.  The key players in the market implement growth strategies such as product launches, mergers, and acquisitions, etc. to gain a competitive advantage over their competitors. For Instance,

• Google Inc has incorporated several developments in Google Translate in 2020 like the inclusion of new languages, better algorithms, and more accuracy.
• Microsoft Corporation's Translator has included two features wherein users can pre-set conversion patterns called translate.it and a full document translator called Document Translation in 2021. However, the Microsoft Translator app for Windows desktop will no longer be available for download, from April 8, 2021.
• RWS Holdings PLC in 2021 announced the return of Language Weaver, a pioneering brand in automatic language translation. Language Weaver combines RWS’s linguistic expertise with SDL’s and Iconic’s technologies.
• In 2021, Pangeanic has upgraded its NLP ECO Platform to version 2, featuring multilingual anonymization services in English, Spanish, French, German, Italian, Japanese, and Brazilian Portuguese.
• Again in 2021, SDL PLC has been acquired by RWS Holdings PLC.

Segmentation:

• By Technology
  • Statistical Machine Translation
  • Rule-Based Machine Learning
  • Hybrid Machine Translation
  • Neural Machine Translation
• By End-User
  • Automotive & Transportation
  • Electrical & Electronics
  • Military & Defense
  • Healthcare
  • Information Technology
  • Others
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Israel
    • Others
  • Asia Pacific
    • China
    • India
    • South Korea
    • Taiwan
    • Thailand
    • Indonesia
    • Japan
    • Others

1. Introduction
1.1. Market Definition
1.2.  Market Segmentation

2. Research Methodology
2.1.  Research Data
2.2.  Assumptions

3. EXECUTIVE SUMMARY
3.1. Research Highlights

4. MARKET DYNAMICS
4.1. Market Drivers
4.2. Market Restraints
4.3. Porters Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Powers of Buyers
4.3.3. Threat of Substitutes
4.3.4. The Threat of New Entrants
4.3.5. Competitive Rivalry in Industry
4.4. Industry Value Chain Analysis

5. GLOBAL MACHINE TRANSLATION MARKET BY TECHNOLOGY
5.1.  Statistical Machine Translation
5.2.  Rule-Based Machine Translation
5.3.  Hybrid Machine Translation
5.4.  Neural Machine Translation

6. GLOBAL MACHINE TRANSLATION MARKET BY END-USER
6.1.  Automotive & Transportation
6.2.  Electrical & Electronic
6.3.  Military & Defense
6.4.  Healthcare
6.5.  Information Technology
6.6.  Others

7. GLOBAL MACHINE TRANSLATION MARKET BY GEOGRAPHY
7.1. Introduction
7.2. North America
7.2.1. United States
7.2.2. Canada
7.2.3. Mexico
7.3. South America
7.3.1. Brazil
7.3.2. Argentina
7.3.3. Others
7.4. Europe
7.4.1. Germany
7.4.2. France
7.4.3. United Kingdom 
7.4.4. Spain 
7.4.5. Others
7.5. Middle East and Africa
7.5.1. Saudi Arabia
7.5.2. UAE
7.5.3. Israel
7.5.4. Others
7.6. Asia Pacific
7.6.1. China
7.6.2. India
7.6.3. South Korea
7.6.4. Taiwan
7.6.5. Thailand
7.6.6. Indonesia 
7.6.7. Japan
7.6.8. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS
8.1. Major Players and Strategy Analysis
8.2. Emerging Players and Market Lucrative
8.3. Mergers, Acquisition, Agreements, and Collaborations
8.4. Vendor Competitiveness Matrix

9. COMPANY PROFILES
9.1.  RWS Holdings PLC
9.2.  CSLi
9.3. MICROSOFT CORPORATION
9.4.  IBM CORPORATION
9.5.  SDL PLC
9.6.  Omniscien Technologies 
9.7.  GOOGLE INC.

Google Inc.

IBM Corporation

Microsoft Corporation

RWS Holdings PLC

Omniscien Technologies

Pangeanic

SDL PLC

CSLi