There are roughly six thousand languages spoken around the world. Even focusing on the most commercially relevant 250 creates staggering complexity for any brand trying to operate globally. Simon Hodgkins, Chief Marketing Officer at Vistatec, has watched this challenge evolve over the company's 30 year history, from the early days of expensive manual translation through machine translation and neural networks to today's generative AI boom. The technology has transformed dramatically, but one truth remains constant: poorly translated or localized content can devastate a brand's reputation in seconds.
The Content Explosion Is Real
The sheer volume of content that global brands produce today defies easy comprehension. Vistatec works with some of the world's largest companies in airlines, retail, manufacturing, sportswear, and countless other industries. For organizations of this scale, processing tens of thousands of localization jobs per week is not unusual. That includes not just written documents but video, audio, technical manuals, patient information, training materials, transportation documentation, and everything else a multinational enterprise touches.
Hodgkins does not use the term content explosion lightly. Generative AI has accelerated content creation to what he calls a ferocious scale, but this creates new problems alongside the obvious benefits. When many companies use the same underlying models, content starts to sound generic. Governance and compliance risks multiply. And when you add the complexity of different languages, cultures, and regulatory jurisdictions, things get very complicated very quickly.
A product launch in the UK market requires different approaches than the same launch in Germany, France, or Spain. Selling into New York means considering Spanish speaking communities. According to the Common Sense Advisory, companies that localize content are 1.8 times more likely to achieve year over year revenue growth than those that do not (https://csa-research.com/). But achieving that growth requires getting localization right, not just getting it done.
From Translation Provider to Service Integrator
The relationship between brands and localization vendors has fundamentally changed. In the past, a company would send documents to a translation provider and receive completed translations back. Thousands of linguistic experts around the world worked on various accounts, and that model still exists for heavily regulated industries like finance and life sciences where human involvement is legally required.
But AI has shifted the dynamic toward collaboration rather than simple service delivery. Brands may now have their own large language models or preferred tools. They need partners who can work within their existing technology stack while adding expertise in prompt engineering, LLM management, and quality verification. The vendor becomes an integrator, orchestrating a complex ecosystem rather than just providing translations.
Vistatec built several proprietary tools to address this shift. Vistatec Speech handles AI dubbing, enabling brands to create multilingual voiceovers for 8, 16, or 24 countries from a single recording rather than booking studio time repeatedly. Vistatec Verifier checks AI outputs for linguistic errors, ensuring precision, consistency, and quality even when no human touched the first pass translation. Vistatec AIM orchestrates humans and machines working together, allocating tasks, resources, time, and budgets across what can be thousands of daily jobs.
Why AI Alone Cannot Maintain Brand Trust
Hodgkins watched many companies rush to add AI to everything after the generative boom began, but Vistatec took a more cautious approach. After three decades building reputation, they would not introduce technology that did not work properly or produced inconsistent results. Consistency remains one of AI's persistent challenges, and for brands that have invested years building customer trust, a poorly localized document can have dramatic consequences.
The problem manifests in multiple ways. Technical debt accumulates when systems are built hastily. Drift occurs when models update or expand and no longer react the same way. Just because something works today does not mean it will work identically after the next model update gets pushed. These issues require ongoing management that most brands are not equipped to handle internally.
Hodgkins points out that AI training data skews heavily toward English, particularly US and British English. Move beyond the major European languages and the models are not well trained on cultural nuances at all. Indigenous languages and underserved markets present even greater challenges. Companies that assume AI handles everything discover significant shortfalls when they try to resonate with audiences outside the primary training data.
The Human Expertise That Still Matters
One of the biggest mistakes companies make is assuming that someone who speaks a language understands the culture well enough to oversee localization. Vistatec maintains a network of 15,000 to 20,000 linguistic experts around the world, and the distinction between language speakers and linguistic experts matters enormously. For major brand work in a particular country, the company might assign 30 people who live, breathe, and understand the local culture as their mother tongue, working from within that specific market.
This human expertise integrates with AI rather than competing against it. The technology handles scale and speed while humans provide cultural nuance, brand voice consistency, and quality verification. Hodgkins describes the relationship as agentic, with AI and humans working in real time as an ecosystem rather than sequential handoffs. Content can be checked three or four times using AI against style guides, terminology databases, and brand guidelines, then routed to specific linguistic expert teams when manual review is required.
The framework addresses multiple dimensions simultaneously: ethical compliance, data security, legal requirements, regulatory standards, brand protection, and bias prevention. Building intelligent workflows that utilize translation memories alongside new AI tools requires significant skill, expertise, and trial and error. What Vistatec puts into the market must be scientifically validated, not rushed out because AI makes things feel easy.
Unlocking Markets That Were Previously Too Complex
For brands willing to invest in proper localization infrastructure, AI enables expansion into markets that were previously too difficult to serve. Vistatec helps customers unlock new countries and languages every day. A medium sized company might consider 5 to 12 languages, but major global brands operate across 50 to 150 languages routinely.
The opportunity extends beyond obvious language boundaries. Within the United States alone, Spanish and Hispanic communities represent significant markets that resonate better when addressed in their mother tongue. Multilingual communities exist in every country. Indigenous language support serves both commercial and social purposes for brands operating in regions where these languages matter.
Hodgkins sees this as completing the promise of the internet. The web made the world one place where business could happen, but content was still predominantly in major languages. AI localization now enables that content to actually resonate with individual customers regardless of their language or culture. The work is never truly done until content makes a difference for the company, not just when the translation is delivered.
The companies that will win, according to Hodgkins, are those willing to collaborate with service integrators who can manage the complexity of rapidly evolving AI tools while maintaining brand trust and quality standards. Every week brings new developments, and staying current while meeting the specific requirements of each brand demands dedicated expertise that most companies cannot build internally.
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