Flying Unicorns, Ai and ChatGPT

Flying Unicorns, Ai and ChatGPT

April 27, 2023

By Ingrid Christensen

What we once never dreamed possible seems to be becoming a reality. In this article, I’ll explore some of the facets of Ai and ChatGPT and how they are impacting the language service industry. Unfortunately, I won’t talk about flying unicorns — I put that in here just to catch your attention.

Ai (artificial intelligence) and ChatGPT are a suite of tools designed to solve complex business problems, such as working with a tiny budget, extensive workload, and a short turnaround time (something you never face, right?). Although these issues can leave you feeling overwhelmed, it is essential to consider that there will always be a difference between what you need and what technology can provide. Ai and ChatGPT can fill the gaps, but will not bridge them completely… you need someone who knows how to pull the levers, especially in the translation and interpretation industry. 

What we know is that Ai, ChatGPT, and all the other technologies surrounding the buzzwords floating around us are not going away. Technology is by nature disruptive and always has the potential to change the way we live and work. While scary to many, we have the unique opportunity to lean in and learn to trust that which is new and different.


AI for language translation is beneficial in many ways, especially if you are looking for an enterprise solution but have a limited annual spend. With AI-powered translation, large volumes of content are translated at lower costs and faster speeds. 

Localization vs. real-time translation

When considering the use of AI in language translation, it is always important to understand the difference between localization and real-time translation. 

The use of machine translation in localization does not shut out human interaction and joins forces with translation management systems and workflows designed to be human-centered. 

On the other hand, real-time translation service provides multilingual customer and employee experiences through instances like customer service, internal content, and digital workplace tools, as a few examples. The main focus of real-time translation is speed rather than high-quality work, which is why it’s always combined with software platforms like Salesforce, which typically does not involve any human interaction.

Potential ROI

A thorough understanding of localization and real-time translation’s potential return on investment (ROI) is essential to consider. 

By implementing AI into your localization efforts, you can achieve a zero-size backlog, reduce translation costs, implement changes faster, and reduce costs by sharing MT assets. 

However, some prices are to be expected, such as upfront automation, time to market, output quality, tech team, current resources, ongoing integration (systems frequently update with little notice), and glossary creation and maintenance – which is quite complex.

For translation to be effective, creating and maintaining memory glossaries is required. This effort can include do-not-translate lists for terms like a brand name (for example, “Medicare”), which should remain unchanged when translated. Next, you must accurately assess proper nouns like “Valencia” in English versus “València” in Spanish. Certain abbreviations, such as “AI” in English and “IA” in Spanish, also need special attention during the translation process to ensure a clear understanding. Additionally, common word glossaries like district preferences and expansion glossaries like “IEP” in English and “Programa de Educación Individualizada” in Spanish are necessary factors you must consider to produce effective communication. 

Another point to mention is that there are a few lingering concerns that tag along with AI and localization efforts. Data privacy, data protection and retention, data locality, and security issues such as ISO and state/federal compliance are the most common. 


AI is beginning to delve into live interpreting. Automated Speech Recognition (ASR) and machine translation (MT) technology are able to transcribe and translate live speech (in place of a human interpreter), but this will only provide closed captions on the screen – losing the personal touch of a human voice interpreting. Unfortunately, technology is not there yet – sometimes, it is how a person says something rather than what was actually said. Context, body language, emotions, and sentiment all go into helping us understand a message in its entirety and not just word-for-word. Technology is only as good as what is already saved or learned. If someone is hard to stand or doesn’t pronounce a word correctly, the data is not there for AI to translate correctly.

Fun Fact! Simultaneous live interpreting is the 3rd most stressful job in the world, according to the World Health Organization, right behind a fighter pilot and an air traffic controller. Being able to listen, understand, translate, and then talk while constantly switching between languages takes extreme levels of concentration. AI technology is currently only recommended when human interpreters can’t be used due to accuracy and quality control.

Not to mention, in a world growing more and more “screen-centered” by the day, people crave human connection and interaction – something AI cannot provide. 


Doing anything audiovisual is generally incredibly complex and includes multiple vendors and steps. Now, add multiple languages as an additional layer of complexity. You need content creators, video production, the talent, quality assurance, and now a Language Service Provider (LSP) to translate or interpret during any step necessary. This could be an interpreter in the corner of the screen, closed captions at the bottom of the screen in a different language, voiceovers in multiple languages, or you could be producing multiple versions of your video in multiple languages. 

Currently, as technology stands, the best way AI could assist with an audiovisual project is to transcribe and translate speech and add closed captioning. All of your other options and/or steps for production are better served for humans for quality and budget. 

Final Thoughts

Technology could assist all of these tasks — and more — to a degree. Depending on the languages necessary, the complexity of the content, turnaround time, and other factors, Ai could be your solution. With over 7,000 languages spoken around the world, my company partners with over 200 of those languages with nearly 100% accuracy, whereas with Google Translate, on average, is only 82.5% accurate. So when you need to get it right, it’s best practice to still rely on humans — or flying unicorns, if you can find them.

AI is definitely making its mark in the translation and interpreting industry, but it still has a long way to go. Until then, my team at INGCO International is leaning into this technology advancement, while still having humans involved to ensure accuracy and quality with our clients.

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