Insights on AI-driven localization, hyperautomation, and content strategies shaping global brand growth.
Georg, could you share a brief overview of your professional journey and how it led you to become the CEO of Phrase?
I’ve been CEO of Phrase for three years. Before joining Phrase, I was CEO of Smoothwall, a UK child-safety business we scaled and sold. I remain on the board of the acquiring company, publicly listed in Australia (ASX:QOR). Before that, I held leadership roles at Tesla, launching and scaling operations in the UK and Western Europe, and at Yammer, where I helped grow the European team from three people in a pub to 85 in under 18 months. My early experience was at Microsoft, where I sold what would later become Office 365 in its earliest form.
Phrase brought together everything I was looking for: a truly international team and customer base, deep and evolving technology, and an ambitious growth trajectory. I’m half Dutch, half German, born in Switzerland, and based in the UK, with most of my professional experience working transatlantically, so the global nature of the business felt like a perfect match both professionally and personally.
As a leader in AI-driven localization, how do you envision the evolving role of AI in content strategy, and what potential do you see for it to empower global brands to achieve scalable and personalized experiences?
Marketers have always aimed to be relevant and memorable. AI takes this further by enabling a level of hyper-personalization at scale that was previously unimaginable. Done right, AI makes it possible to tailor content not just by market or language but by context, demographic, and real-time need.
At its best, AI empowers brands to engage global audiences with relevant, resonant, and immediate content. It means moving beyond slogans into intelligent experiences that adapt to current events, user behavior, or sentiment. That’s not the future. That’s the new standard and the expectation of consumers.
The near-term consequence of this is that absolute volumes of content will explode—not that individual consumers will consume 1000x more, but since every consumer will receive individually targeted and real-time content, the amount of content produced will explode. This is already starting, and AI makes it possible.
How can businesses effectively scale hyper-personalized content across diverse global markets while maintaining cultural sensitivity and brand consistency?
AI enables personalization on a scale previously unimaginable—tailoring content to individuals, not just regions. Brands can now adjust tone, imagery, and messaging dynamically based on cultural and contextual factors.
Businesses need structured brand assets, approved language databases, and strong AI integrations to scale effectively. It’s also about rethinking content creation. Are you preparing for 100 times more content? A billion times? That scale level requires automation, robust workflows, and a deep understanding of local audience expectations.
In what ways can businesses implement AI-driven hyper-automation with traditional content creation processes to streamline workflows, reduce resource strain, and ensure high-quality outcomes?
When we talk about hyperautomation, we don’t mean just replacing tasks. At Phrase, we are rethinking the entire content lifecycle. We apply AI throughout: assessing content for translation readiness, scoring quality, routing content based on confidence thresholds, and enabling post-editing and feedback loops.
When AI and humans collaborate, content creation becomes more efficient, higher-quality, and agile. It frees creative teams from mundane operational tasks and gives them the tools to move faster and smarter.
This isn’t about replacing humans entirely; it’s about giving humans the control to confidently leverage their companies’ full asset arsenal to achieve new levels of customer relevance at scale humans alone cannot achieve or manage.
At Phrase, how do you manage the AI technologies that enable businesses to scale their global communication efforts, ensuring quality and consistency as they expand into diverse regions?
Phrase is built for complex, high-scale global businesses. We manage AI with a guardrail-first approach. Large language models are used in controlled workflows, informed by enterprise-specific assets like translation memories, termbases, and brand guidelines.
We help teams customize AI outputs using proprietary data and automate intelligent routing, so content can move directly into production or get flagged for review. This balance of flexibility and control lets our customers scale confidently without sacrificing quality or consistency.
As AI handles repetitive tasks, what kind of opportunities emerge for creative and strategic teams to focus on higher-value initiatives?
It’s easy to think of AI as a tool for efficiency, but its true potential lies in enhancing creativity. I often use AI to draft memos, pull insights from transcripts, or iterate on ideas. It helps me produce better work, faster.
This applies across creative fields—writing, design, and brand strategy. AI acts as a collaborator, allowing teams to iterate faster and focus on high-value work rather than manual processes.
As AI becomes more integral to global business strategies, what are the key implications for the localization industry, and how can businesses modify their content strategies to remain relevant?
The localization industry is at a turning point. We’re moving from a world where only a small fraction of content is translated to one where localization must scale with business ambition. That means embracing AI rather than resisting it. It means understanding and embracing that technology budgets and services budgets relate to one another more directly than before – services remain important, but the mix is shifting to more tech, and services must add value; the technology has moved beyond being a workbench for humans, to being where the work gets done.
This shift requires a mindset change. It’s not just about quality anymore. It’s about risk management. As content volumes grow and AI gets better, the industry will need to measure success not only in linguistic accuracy but also in how well it manages risk, turnaround time, and operational impact. Businesses will need new models and mindsets to keep up, moving from an artisanal service model to an AI-augmented strategy.
How can businesses leverage linguistic data and other proprietary assets to enhance localization automation and create a competitive edge in global content strategies?
Anyone can access a generic AI model, but true differentiation comes from training AI with proprietary linguistic data. Linguistic data is one of the most undervalued strategic assets. Companies have spent decades building approved terminology databases and translation assets—these are invaluable for ensuring AI-generated content reflects brand voice and industry expertise. Without this data, AI outputs risk sounding generic. Businesses that fine-tune AI with proprietary assets gain a distinct competitive edge in localization, making their global content strategy more accurate, authentic, consistent, and impactful.
What are the advantages that organizations have gained by adopting sophisticated localization approaches, and how do these benefits contribute to global business expansion?
Localization should be seen as a growth driver, not just a cost center. Historically, it was treated as the final step in content production, but it’s key to audience engagement, brand adoption, and market expansion. We’ve seen clients unlock new markets by translating technical documentation or field service content, allowing them to hire locally and reduce onboarding costs. Others launch products faster, effectively support customers, and drive deeper engagement. Localization supports every part of the business—marketing, HR, support, and product.
When done right, localization becomes a growth engine. Companies leveraging AI-driven localization can reach new audiences faster, improve engagement with multilingual customers, and create personalized experiences at scale. Brands that invest in AI-powered localization will outpace competitors that fail to adapt.
To wrap up, what advice would you give to businesses to best position themselves and leverage these advancements for continued success in global markets?
First, use your imagination—the pace of AI development is so rapid that if you’re only planning six months ahead, you’re already behind. Bring in technologists and strategists who can help you anticipate what’s next.
Second, start now—your proprietary data is the key to AI success. The black gold of the AI era is your proprietary data sets. Are they in good shape? Are your content assets structured, clean, and accessible? Companies that invest in making their digital assets AI-available will gain a massive advantage in the coming years.
Finally, distribute AI tools across your organization. Don’t hide them in a center of excellence. Give teams access, let them experiment, and watch productivity soar.
Georg Ell
Chief Executive Officer at Phrase
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 over 17 years of leadership 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.