AI localization, AI translation and other AI-compound words currently overflow the localization industry. This comes as no surprise since technological advancements reshape various industries. The localization industry is not an exception. Before, localization used to be just about translating languages, but now it’s a complex field shaped by AI, cultural differences, and global consumer habits.
A decade ago, terms like “Large Language Models” were foreign. Today, buzzwords such as “hyper-localization”, “NLP”, and “AI” dominate the localization market. This linguistic shift mirrors the industry’s evolution, driven by technological breakthroughs.
Understanding Localization Buzzwords
The localization industry is abuzz with new terms that signify a departure from traditional localization practices. Let’s take a closer look at these emerging terms:
Hyper-localization: Beyond traditional localization, hyper-localization focuses on tailoring content to specific regions or even individual demographics. This requires a deep understanding of local cultures, dialects, and preferences.
Example:
In China, Coca-Cola uses a local name on its packaging to attract consumers. Their advertising strategy also leverages modern Chinese culture. For instance, a few years back, Coca-Cola found out that Chinese teenagers often use codes made up of numbers, emojis, and graphics to communicate. As a result, they included some of these codes on their labels.
NLP (Natural Language Processing): This technology underpins many localization advancements. With NLP, computers can comprehend, interpret, and generate human language. Its applications range from machine translation to sentiment analysis, allowing for more nuanced and accurate localization.
Post-localization: This emerging concept suggests a future where localization is seamlessly integrated into content creation. It refers to the need for stirring away from traditional localization and rethinking localization services. This is to keep up with the market trends and explosion of content.
Scalability: As content volume continues to grow exponentially, localization processes must be able to handle increasing workloads without compromising quality or speed.
Localization automation: Using technology to make localization processes more efficient and cost-effective is crucial. Automation can help with many tasks, like managing translation memories and quality assurance.
Global ready: This term refers to content or products designed to fit in different markets. This involves creating flexible content and products with cultural differences, language variations, and legal requirements in mind.
Glocalization: This buzzword is coined from two words – globalization and localization. It refers to balancing global consistency with local adaptation to create products that resonate with specific markets.
The Rise of AI in the Localization Industry
AI has transformed localization processes across various dimensions, enhancing accuracy and efficiency. Artificial intelligence models, especially those using machine learning and LLMs, have significantly improved translation accuracy by understanding context, slang, and industry-specific jargon better than traditional methods.
AI also handles repetitive and time-consuming tasks like first drafts of translations and consistency checks. This cuts down the time and cost of manual localization, allowing for quicker project completion and better management of bulky content.
The localization industry is now actively leveraging the following AI technologies:
Machine learning: ML algorithms analyze vast amounts of multilingual data to continuously enhance translation models. They learn from corrections and human inputs, providing more accurate translations.
Adaptive learning: Adaptive learning systems tailor the translation models based on user behaviour and feedback. They dynamically adjust translations to better match specific industry terminology, regional dialects, and user preferences, improving personalization and context relevance.
LLMs and GenAI: Large language models (LLMs) and Generative AI (GenAI) such as GPT-4 generate high-quality translations by understanding context, idiomatic expressions, and nuanced meanings. They can also create localized content from scratch, helping with content creation in addition to translation.
Chatbots: AI-powered chatbots incorporate instant translation services in real-time customer interactions. They can handle multiple languages, ensuring consistent communication with a global audience and improving customer support efficiency.
CRM: Using AI in CRM systems enhances customer interactions by offering real-time translation and localization to facilitate communication for users who speak different languages.
Speech-to-text: AI-driven speech-to-text technology accurately converts spoken language into written text in multiple languages. This is crucial for real-time transcription and translation services in international conferences, meetings, and multimedia content (for more information about this, check our article on audio translation technologies).
Source: Khoros.com
Emerging Trends and Their Implications
Social media, streaming services, e-commerce, and mobile apps generate vast amounts of text, audio, and video content that need to be localized for global audiences. Such a “content explosion” presents significant challenges and opportunities for the localization industry.
The rise of hyper-localization reflects the increasing demand for tailored content. Consumers expect content to resonate with their specific cultural and linguistic preferences. This trend requires a deep understanding of local markets and the appropriate adaptation of content.
The concept of post-localization hints at a future where localization is no longer a separate process but an integral part of content creation. Advances in AI, augmented reality, and virtual reality could make it possible to adjust the content in real-time based on user preferences and context.
These emerging trends have a profound impact on the localization industry. Localization teams must become more agile, data-driven, and technologically savvy. They should embrace AI and automation while becoming aware of cultural nuances and consumer behavior.
AI plays a key role in this transformation, enabling new levels of automation, accuracy, and speed. As AI continues to develop, we can expect even more innovative solutions to emerge, shaping the future of localization.
