Translation and SEO: Cloud Traffic and Data

2024/2025 Market Update

The landscape of translation and SEO has evolved dramatically since the early predictions of the 2010s, when we drafted the article below. While earlier forecasts painted an optimistic picture of machine translation capabilities, the reality in 2024/2025 presents a more nuanced scenario where human expertise and artificial intelligence continue to coexist and complement each other. Undoubtedly, the advent of AI Translation is changing profoundly the way companies are consuming translation services, particularly for SEO, and how language services are producing language versions. LLMs are quite capable of producing human-fluency translations, whilst the challenge to do so at scale remains because of their "generative" nature.

Current Market Dynamics

The translation services market has expanded well beyond the initial projections, reaching approximately $76.5 billion in 2024, with expectations to surpass $80 billion by 2025. Several key factors have driven this growth:

a) Cloud Infrastructure and Data Processing

The acceleration of cloud computing has far exceeded Cisco's early estimates. The global cloud computing market now processes exabytes of multilingual content daily, with AI-powered translation services handling an unprecedented volume of data. Edge computing and 5G technologies have enabled real-time translation capabilities that were barely imaginable a decade ago.

b) The Evolution of Machine Translation

While Kurzweil's prediction about human-quality translation by 2029 remains to be fully realized, significant strides have been made in neural machine translation (NMT) technology and its modern version, LLM translation. Modern systems like GPT-4o, Gemini or PaLM demonstrate near-human quality in certain language pairs and contexts, though they struggle with nuanced content and cultural adaptation and with less-resourced languages.

The Human-AI Symbiosis

The translation industry has evolved into a sophisticated ecosystem where human translators and AI tools work in tandem:

Post-Editing and Quality Assurance

Professional translators now spend less time on initial translation and more on high-value tasks such as:

Cultural adaptation and localization
Creative content translation
Technical and legal document verification
Training and fine-tuning AI models

SEO and Multilingual Content Strategy

The integration of translation and SEO has become more sophisticated, with considerations for:

Multilingual keyword research using AI-powered tools
Cultural search intent analysis
Voice search optimization across languages
Regional search engine compliance

Market Trends and Future Outlook

Several key trends are shaping the industry's future:

Hybrid Translation Workflows Companies are adopting hybrid approaches that combine AI translation for high-volume, time-sensitive content with human translation for brand-critical materials.
Real-Time Translation Services The demand for instantaneous translation in virtual meetings and live events has created a new market segment, with advanced AI-powered solutions offering increasingly accurate results.
Data Security and Privacy With stricter global privacy regulations, there's growing emphasis on secure translation solutions that protect sensitive information while maintaining translation quality.

Investment and Growth

The machine translation market has grown substantially, now valued at approximately $800 million in 2024, with projected growth rates of 22% annually. This growth is driven by:

Increased adoption in emerging markets
Integration with content management systems
Development of industry-specific translation models
Rising demand for multilingual e-commerce solutions

Cisco estimates that global cloud traffic will grow 45% annually until 2016, with translation services growing at around 15% to 20% per year. According to Ian Henderson, CTO of Rubic, a translation and location company, many new machine translators must enter the industry each year to handle the content. On the other hand, Raymond Kurzweil, one of the brightest minds in the world, director of technology at Google, and a futurist known for his predictions about artificial intelligence predicts that machines will match human intelligence and perform several feats that seem to be science fiction nowadays, including human-quality translation, by the year 2029. Current happenings also suggest a strong role for non-human translation, with machine translation (MT) advancing rapidly. Three simultaneous-translation devices have been announced since June 2012, including one by Microsoft that renders live audio translations from the spoken word, respecting the tones and inflections of the speaker.

Perfect is hard

But perfecting translation machine engines remains one of the toughest challenges in artificial intelligence. For several decades, computer scientists with the help of armies of linguists, tried rule-based approaches, i.e. teaching machine translation systems the linguistic rules or similarities between two languages (sometimes not related languages, like English and Japanese) and including the necessary dictionaries. Progress was extremely slow and suffered several setbacks, like the ALPAC report in 1966. Technology did not cease to advance until statistical systems, using vast amounts of data, have made it possible to train translation engines quickly and efficiently for several domains. Click below to see our presentation in Budapest, which includes a short history of machine translation. Undoubtedly, ever-growing content and the demand for translating online data into multiple languages is growing fast. Exponentially.

Pangeanic launched its Pangeanic machine translation project in 2008, reporting real-life implementations in many events, and it is now a thriving, customizable software capable of re-training itself and creating engines on the fly. The project won an international name, and is part of EU-funded projects. “Human and machine translation are kind of like ‘frenemies,’” translation expert Nataly Kelly said. “They live alongside each other, but not without a lot of tension.” Sometimes, machine translations are so atrocious that human translators prefer to start from scratch. Machine Translation companies and their output are becoming increasingly ubiquitous daily. As experts, we know that technology aims not to replace multilingual humans. Machines (rather automatic translation software) cannot fully replace human translators...yet. Human translators often clean up machine translation (post-editing). Thus, the technology becomes an enhancer rather than a replacement. This need for accuracy keeps the (human translation) business growing. It is one of the few industries growing during the worldwide recession. It is approximately a $34 billion market. Machine translation’s market is around $200 million with growth forecasts of around 18,65%. “Demand for translation is booming because content creation is exploding,” says Kelly. “And since much of that content is created and demanded in multiple languages, human translators alone can’t keep up. They need machine translations to improve–and fast.”