This study provides a comprehensive analysis of artificial intelligence (AI) contribution to translation industry (ACTI) research, synthesizing it over forty-one years from 1980-2024. 13220 articles were retrieved from three sources, namely WoS, Scopus, and Lens. We provided two types of analysis, viz., scientometric and thematic, focusing on cluster, subject categories, keywords, burstness, centrality and research centers as for the former. For the latter, we thematically review 18 articles, selected purposefully from the articles involved, centering on purpose, approach, findings, and contribution to ACTI future directions. The findings reveal that in the past AI contribution to translation industry was not rigorous, resulting in rule-based machine translation and statistical machine translation whose output was not satisfactory. However, the more AI develops, the more machine translation develops, incorporating Neural Networking Algorithms and (Deep) Language Learning Models like ChatGPT whose translation output has developed considerably. However, much rigorous research is still needed to overcome several problems encountering translation industry, specifically concerning low-source languages, multi-dialectical and free word order languages, and cultural and religious registers.

The language industry is having a moment. The ongoing global health crisis has forced organizations to break down borders and support a global remote workforce, requiring more cross-language interactions and coordination than ever before. At the same time, technological innovations in the language translation industry are at an all time high. We've never before had access to such sophisticated technology tools to manage translation processes. I predict it's going to be an exciting year in the industry, with an unprecedented level of innovation.

Do you know that a full-time working translator can translate approximately 520,000 words per year? There would be no wrong in saying that the translation industry has existed for centuries and will progress in double digits in the upcoming years. Because digital realms continuously push for more shared and globalized experiences, the current worth of the global translation industry is $56.1 billion, and the figure is expected to increase at a swift pace in upcoming years. The number is projected to surpass $70 billion by the year 2023. It's been more than 10 years since the launch of Google translate by utilizing phase-based machine translation algorithms.

Language is perhaps the most defining factor of humankind. What makes humans different from other animals on the planet is our ability to speak out and communicate via framed words and sentences. The language of a population is one of the most defining factors across countries and nationalities, regions, and cultures. It can define the history, sociocultural situation, and even geographic diversity. From ancient times, there has been a trend for people to understand the language of one another. History traces back to Greeks and Romans traveling all across the world to discover, decipher and translate languages to find out the cultural, political, and social situations from one era to another.

AI and Languages. As high-tech tools for translation purposes became more accessible to the general population, the language translation process …

In the year 2020, it may seem natural to receive a meaningful translation from Google Translator, when some of us can still remember the times when it required correction every time you tried to translate more than three words altogether. This is the example of changes we tend to overlook as unpretentious users, but there is a lot of hard work behind them. While processing data, the neural network doesn't just follow some algorithm but finds ways of solving the problems and, in fact, learns to solve them. And the more tasks it solves, the better it copes with them. This similarity with a principle of human brain functioning is the reason to name neural networks an artificial intelligence (AI).

Artificial intelligence (AI) has had a major and positive impact on a range of industries already, with the potential to give much more in the future. We sat down with Ofer Tirosh, CEO of Tomedes, to find out how the translation industry has changed as a result of advances in technology over the past 10 years and what the future might hold in store for it. Translation services have felt the impact of technology in various positive ways during recent years. For individual translators, the range and quality of computer-assisted translation (CAT) tools have increased massively. A CAT tool is a piece of software that supports the translation process.

Artificial intelligence (AI) has infiltrated numerous aspects of our lives in recent years, thanks to improvements in the field of machine learning, where computers ostensibly program themselves. This drive towards digital self-learning has led to major breakthroughs in our day-to-day interactions with machines, most notably the rise of digital home assistants such as Amazon Echo, and the recently launched Google Lens, which identifies objects based on visual cues from your phone's camera. One of the most widely-discussed advances has been the use of AI in translation. Not unlike the Babel Fish from The Hitchhiker's Guide to the Galaxy, with AI translation, "you can instantly understand anything said to you in any form of language." The technology works by recognizing words individually and then, as MIT Technology Review puts it, "takes advantage of the fact that relationships between certain words…are similar across languages" to create its translations. It has already found its way into a number of our most commonly used websites and platforms, with even grander plans in the pipeline – but just how reliable is the technology?

Natural Language Processing; it's Artificial Intelligence that learns words and patterns of words so that it can respond to human searches and questions. Siri and Alexa are examples of this technology. And this technology is continually improving. As more and more conversations are held with these machines, they continue to learn and respond more accurately. Machines are also in use for translations.