Marketing and Translation: The Limits of AI versus the Nuances of Language
Achieving results amidst constant change is the new major challenge for marketers worldwide. Hence, the use of Artificial Intelligence (AI) in the field of marketing is becoming increasingly common. This technology allows them to scale creative work, optimize campaigns, and create personalized ad experiences.
But when it comes to translating these contents, can artificial intelligence understand cultural context?
The Rise of Data Packages
The adoption of AI has more than doubled since 2017, according to a recent McKinsey study. The specific areas where companies see value in AI have evolved: in 2018, manufacturing and risk control were the two functions where the highest proportion of respondents reported seeing value in using AI.
Currently, according to the same study, the greatest reported revenue impacts are found in marketing and sales, product and service development, and corporate strategy and finances, with the greatest cost benefits of AI in supply chain management.
It is estimated that 80% of marketing professionals already use at least one AI-powered product to improve their business results, as per information from the specialized site Think with Google.
The global AI market revenue in marketing is expected to grow from USD 27.4 billion in 2023 to USD 107.4 billion in 2028.
Source: Statista
Among other benefits, the experimentation enabled by artificial intelligence is revolutionary for marketing specialists, who also find predicting consumers’ next steps crucial in their strategies. In this sense, the key to success in a changing scenario is the ability to analyze vast amounts of data and make real-time decisions.
However, when these contents need to be translated, relying solely on artificial intelligence without the essential input of human professionals can lead to irreversible consequences.
The Importance of Nuances
Artificial intelligence encounters limitations when dealing with context, linguistic distinctions, expressions and jargon. In this regard, ‘teaching AI to analyze all possible meanings of a sentence and understand which one a person intends in a given context is one of the major challenges in NLP research,’ says scientist Richard Socher.
‘The greatest challenge lies in the nuances of languages. I have long argued that, while AI will certainly catalyze productivity with generated content, it’s always a first draft that solves the blank canvas problem. Humans must always curate from there because, after all, communication is a craft,” adds Sam Bobo, Product Manager of Artificial Intelligence.
In that sense, Bobo lists some of the issues that pose major challenges for artificial intelligence:
- Connotation and denotation
- Tone and register
- Idioms and figurative language
- Dialects and accents
- Homonyms and homophones
- Slang and jargon
- Euphemisms and dysphemisms
- Hyperboles
- Irony and sarcasm
A hybrid approach and multidisciplinary work with professionals with proven expertise in linguistic services are the best way to ensure effective translations of marketing content. Every translated word and phrase must pass through the sieve of experts who truly understand the values and worldviews of each audience. Thus, messages will not be misinterpreted (or offensive) and will respect every socio-cultural context.
