The Strategic Opportunity Hiding in Your Content Pipeline

 By Georg Ell, CEO of Phrase

For years, localization has been seen as the final “translation” step in a content pipeline. It was the last mile converting words from one language to another, often under tight deadlines and limited budgets. It wasn’t seen as strategic, but as an overhead, a necessary but cumbersome task, a cost centre. But as AI, machine learning, and automation reshape how content is created and delivered, this narrow view has become not just outdated, but counterproductive. It limits the potential of the very teams driving global business forward. It’s time we stop thinking in terms of translation and localization and start talking about multilingual content automation.

Multilingual Content Is a Strategy, Not a Step.

What used to be a technical task confined to a single department – or outsourced to local team members or professional agencies – has become a strategic capability that spans the entire enterprise. The work of localizing content is no longer about translation alone. It is also no longer a “step” at the end of a linear content production process, but the concept of being multilingual and highly personalized now infuses campaign concept ideation and production at every step. It’s about launching products into global markets on day one. It’s about scaling creative campaigns to resonate across demographics, regions, and generations. It’s about enabling businesses to connect with every customer, everywhere, in the most contextually relevant way possible.

Today, the amount of content created and distributed across markets has grown exponentially. Teams are expected to launch in 15 or 20 languages at once. They are adapting video, apps, web experiences, and marketing assets in real time. They are using AI, content profiles, and integrated platforms to do it. This is no longer a translation problem. It is a competitive business opportunity, to engage and convert more customers.

So, it’s important that we stop talking about localization and start talking instead about multilingual content automation.

Multilingual content automation better reflects reality. It is about building systems that adapt content for different audiences automatically, intelligently, and at scale. It is about removing silos, integrating workflows, and treating language as a strategic enabler, not a postscript.

AI Has Made Multilingual Content Operations More CreativeThan Ever

Ironically, AI and automation haven’t made the human side of content irrelevant. They’ve made human guidance more important, just at a different point in the process than was once the case. The work of “doing the translating” will be done by machines. Modern multilingual content platforms can go significantly beyond literal translation; they help shape messaging that is hyper-personalized, and lands emotionally, culturally, and contextually. But they can only do so with the right kind of human guidance. 

These days, we’re seeing businesses use AI to adapt the same message for audiences as diverse as Gen Z Australians and older British professionals. The vocabulary, tone, and references change entirely, even if the brand message remains consistent. The changes even in a single language are so profound that at that point, the line between translation and original creation gets blurry. That’s not a shortcoming of the process, it’s the entire point.

AI introduces a kind of creative fluency that was never possible at scale before. Multilingual content is no longer about generating a linguistic equivalent; it’s about generating an equivalent impact, no matter the audience. Rather than bringing people into the mix for artisanal editing, it’s about leaning into human minds for artisanal content origination. The technology can take it from there. 

Multilingual Content Automation Breaks Down Silos

When companies start thinking in terms of multilingual content automation vs. localization, the conversation shifts from language to logic. Instead of simply translating finished assets, enterprises can now build automated workflows that integrate content creation, personalization, and adaptation into one intelligent pipeline.

This reimagining brings marketing, product, engineering, and customer success teams into tighter alignment. It allows for faster time to market, broader audience reach, and consistent quality across every channel. In practice, it removes the traditional handoff model that slows down projects and creates disconnects between departments.  Instead, they operate on a shared platform with a unified continuous workflow. This model enables faster launches, fewer handoffs, and better alignment across functions.

It also sends a clear message to leadership: This is not a one-department job. It is a company-wide capability that impacts growth, customer experience, and operational efficiency.

Technology Infrastructure, Not Translation Technology

For a long time, translation management systems have been positioned as the heart of localization. But that center can no longer hold. Translation is just one part of a much larger equation. True multilingual content automation platforms are infrastructure, akin to cloud computing platforms like Azure or AWS. They are the foundation on which scalable, adaptive, cross-functional content workflows are built.

Multilingual content automation isn’t about selecting a generative model and training it. It’s about knowing when and how to use the right model for the right outcome. That means moving toward systems that select from a range of fit-for-purpose models based on the task at hand, the audience, and the business objective. 

But the bigger shift isn’t technological. It’s cultural. Adopting multilingual content automation means redefining where humans create the most value. Not in repetitive workflows or pixel-pushing edits, but in shaping context, training systems, and orchestrating outcomes. That shift changes how businesses think about automation. It encourages every function to reexamine what should be automated, where human intelligence belongs, and how both can be directed toward measurable business results. When done right, this shift supports global scale while simultaneously future-proofing the organization.

A Blueprint for the Modern Enterprise

Let’s not mourn the evolution of “localization.” Let’s celebrate it. Let’s seize the opportunities that the new technologies open up. The future belongs to companies that integrate multilingual content automation into every facet of their operations, from marketing and product to support and sales.

Multilingual content automation is not just a new term. It is a new way of working. It is a blueprint for companies that want to scale content globally, embrace AI responsibly, and keep human insight at the core of their strategy.

For teams who have long operated in the background, this is a moment of transformation. For companies looking to compete globally, it is a moment of opportunity.

Georg Ell Biography

Georg Ell is the CEO of Phrase, a global leader in localization technology with over 300 employees and prestigious clients such as Uber, Shopify, Zendesk, and Deliveroo. Backed by The Carlyle Group, a global private equity firm, Phrase thrives under Georg’s extensive experience in the tech industry. With 2 decades of experience, Georg has held significant roles, including CEO of Smoothwall, an education safety-tech business that gained recognition as a Top 100 UK employer under his tenure. He also served as Director for Western Europe at Tesla, leading a team of over 330 people to promote sustainable energy adoption. 

Before Tesla, Georg was General Manager for EMEA at Yammer, where he facilitated substantial growth and the company’s acquisition by Microsoft for $1.2 billion. Georg’s career began at Microsoft, where he was a pioneering salesperson for the company’s enterprise cloud business in Europe. In addition to his role at Phrase, Georg is a Venture Partner at LocalGlobe and Craft Ventures, and an Advisory Board Member at EQL. He holds a degree in Political Science and Management Studies from St. John’s College, Cambridge.