Advancements in Machine Translation Render It an Indispensable Business Tool

Capitalize on Machine Translation’s ability to process large amounts of content quickly and cost-effectively to scale your translation initiatives, enhance your multilingual customer experience, and grow your business globally.   

Machine Translation for Success in a Digital World

Use Machine Translation software as part of your content workflow to help offset the expense and lengthy translation turnaround times associated with professional translation by humans.

When the public first encountered Machine Translation (MT), they considered it a novelty that did not have wide-reaching applications for most businesses. 

Now that the technology has matured, it supports more use cases. Today, MT is a business-grade technology that can boost your business.  

While the technology is still far from perfect, Machine Translation experts can help companies capitalize on the software’s strengths while overcoming its limitations, which can result in undesirable errors. When executed correctly, MT permits companies to solve real business problems and grow their global customer base.    

The COVID-19 pandemic accelerated digital transformation, catapulting us into a digital-centric world. Companies must effectively communicate with global audiences to succeed. They face pressure to translate more material than ever — faster — within existing or lower budgets.

When companies use the best MT engines as an efficiency tool for all their content with varying levels of human intervention to meet just-right quality requirements, they can translate unlimited content at a fraction of the cost of traditional human translation methods with predictable quality.

Machine Translation

The Benefits of Using Machine Translation Technology

Thinking about implementing Machine Translation? Learn how easy it is to use the technology and how it will transform your business. 

On average, our customers achieve the following results when using Machine Translation as part of their workflow.

Greater Translation Efficiency

Up to 40% cost savings.

Faster Turnaround Times

Up to 60% shorter delivery times.

Enhanced Customer Experience

Speak to your customers in their native language everywhere.

How Lionbridge’s Automated Solution Enabled the Le Monde Newspaper To Boost Its Subscriber Count

When iconic French news group Le Monde released their English service, Le Monde in English, they needed a translation solution that could handle the complexities of the 24-hour news cycle. Using Lionbridge’s Machine Translation solution Smart MT™, Le Monde was able to slash translation turnaround time, cover the French presidential election, and attract thousands of new subscribers to their service. Learn more about Le Monde’s use of Smart MT™ in our case study.

Learn more about Lionbridge’s automated solution, Smart MT, to Localize everything™

What is the Best Machine Translation?

Learn which Machine Translation engine will be most effective for your use case with Lionbridge’s Machine Translation Tracker. 

Selecting the right MT engine to best meet your needs is not easy. The quality of your source content, your source language, and your target languages are among the factors that can influence MT engine performance. If only there was data to help you make these decisions. Now there is. Lionbridge’s Machine Translation Tracker is the longest-standing measurement of the major MT engines. It measures the overall performance of a growing array of MT engines, as well as outcomes specific to language pairs and various topic domains. See the Machine Translation quality scores of the top engines during the past year.

How MT Meets the Needs of Major Verticals

No matter what vertical you operate in, Machine Translation can help you overcome your business challenges. Here’s how MT supports legal, life sciences, and e-commerce professionals.


Global legal cases can generate thousands of multilingual legal documents during the eDiscovery process. Legal industry professionals need to translate these documents fast.  

Learn how Machine Translation can be leveraged to help the legal sector to reduce its data set and translate foreign language documents efficiently. 

Life Sciences

Although pharma has been slower to adopt automated technologies, that situation is changing. Artificial Intelligence (AI) is projected to favorably impact patient outcomes by handling more data and identifying adverse events faster than humans. Learn more in this Pharmacy Times piece, “Artificial Intelligence is Changing the Face of Pharmacovigilance.


When retailers were forced to close their brick-and-mortar stores during COVID-19, e-commerce became their lifeline. They quickly learned their customer base was no longer limited to foot traffic and geographic constraints. Their potential customers consisted of anyone in the world with an internet connection. Now that stores have reopened, there’s no turning back.  

Learn how retailers are shaping customers’ experiences through localization and Machine Translation’s role.

Dig Deeper Into Content About Machine Translation

Language Ranking Based on Machine Translatability for More Effective MT

Consider language complexity before deploying Machine Translation. Our machine-translatability ranking will help support your business decisions.

Machine Translation vs. Machine Translation Plus Post-Editing

When is it best to rely on Machine Translation? When should you consider a hybrid model that incorporates traditional, human translation? We go through the scenarios. 

Neural Machine Translation: How Artificial Intelligence Works When Translating Language

Delve into what Neural Machine Translation is and why it is considered a game changer for the language industry. 

Machine Translation in Translation

This handy cheat sheet will bring you up to speed on the most important terms associated with Machine Translation. 

Meet Our Machine Translation Experts

Rafa Moral

Vice President, Innovation 

Rafa oversees R&D activities related to language and translation. This includes initiatives pertaining to Machine Translation, Content Profiling and Analysis, Terminology Mining, and Linguistic Quality Assurance and Control. 

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Vincent Henderson

Head of Product Language Services

Vincent leads the product and development teams at Lionbridge. He focuses on ways to use technology and AI to analyze, evaluate, process, and generate global content. He is especially attentive to the disruption of content products and services brought about by Large Language Models.

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A Brief History of Machine Translation

1954 - Georgetown researchers perform the first-ever public demonstration of an early MT system.

1962 - The Association for Machine Translation and Computational Linguistics is formed in the U.S.

1964 - National Academy of Sciences forms a committee (ALPAC) to study MT.

1970 - The French Textile Institute begins to translate abstracts using an MT system.

1978 - Systran begins to translate technical manuals.

1989 - Trados is the first to develop and market translation memory technology.

1991 - The first commercial MT system between Russian, English, and German-Ukrainian is developed at Kharkov State University.

1996 - Systran and Babelfish offer free translation of small texts on the web.

2002 - Lionbridge executes its first commercial MT project using its rule-based MT engine.

Mid 2000s - Statistical MT systems launch to the public. Google Translate launches in 2006 and Microsoft Live Translator launches in 2007.

2012 - Google announces that Google Translate translates enough text to fill 1 million books every day.

2016 – Both Google and Microsoft enable Neural Machine Translation (NMT), slashing word order mistakes and significantly improving lexicon and grammar.

2020 - As of October, Google Neural Machine Translation (GNMT) supports 109 languages.

Selecting the Right Real-Time Translation Technology

Discover the differences between Lionbridge’s real-time translation technology and public Machine Translation engines in this guide. 

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