Forrester reports: why you need AI-powered localization now

What you need to know about the Forrester report on AI localization:

• 70% of translations are now machine assisted, with AI translation surging 533% in 2024
• AI quality is reaching unprecedented quality, and businesses are already shifting
• Without a localization plan, your global business is at risk. The smartest teams now combine human expertise with AI efficiency

AI is transforming how businesses reach global audiences, with machine-assisted translation now driving speed, scale, and efficiency. And traditional approaches aren’t keeping up.

Forrester’s recent report, Rethinking Localization in the Age of AI, explores what this shift means for businesses today. We’ve summarized the key insights from this complimentary report to help you navigate what’s next—and how to make smarter choices for your localization strategy.

AI-powered translation is scaling, and quality is catching up

AI translation is no longer experimental; it's enterprise-ready. Large Language Models (LLM) and Neural Machine Translation (NMT) systems are improving so fast that many businesses are already using them to support their localization efforts at scale. In fact, 88% of content decision-makers say their organizations are using GenAI for translation in some form. According to Forrester, LLM translation quality could approach human-level output in 3-5 years.

AI is helping teams move faster, handle more volume, and focus their expert attention where it matters most. That means faster launches, broader reach, and more time for humans to do what they do best: shape context, tone, and brand voice.

More and more companies are also turning to Translation as a Feature (TaaF)—embedding AI translation directly into their products and platforms. It’s a faster, more scalable way to deliver multilingual experiences, right where users need them.

Localization is becoming centralized and strategic

With this shift in technology comes a shift in responsibility. Leading organizations are moving localization out of fragmented teams and into centralized, cross-functional ownership.

Where localization was once a service function run by mid-level managers, it’s now a strategic capability led by VP- and director-level experts. These leaders own both the budget and the tech stack, and underpin everything from marketing to product to customer support.

And it’s not just about translation anymore. Today’s localization leaders are driving business impact: measuring outcomes like engagement, conversion, and sales, not just quality and turnaround time.

As we explored in an earlier blog by Weglot co-founder Augustin Prot: “72% of consumers would be more likely to buy a product with information in their own language, and 56% feel that obtaining information in their own language is more important than price.” That makes localization not just a nice-to-have for your business, but a clear necessity for revenue growth.

Governance is key in AI localization

As powerful as they are, LLMs aren’t plug-and-play. Forrester makes it clear: without strong oversight, AI-generated translations can introduce hallucinations, bias, or errors. This is especially tricky in low-resource languages or regulated industries.

That’s why governance matters. Enterprises need workflows that combine AI with context, quality scoring, human verification, and enterprise-grade security. The goal isn’t just scale; it’s accuracy, brand consistency, and trust.

DeepL is one way for organizations to employ AI localization at scale, while mitigating those risks and ensuring content is accurate, high-quality, and brand-appropriate. DeepL Translator provides secure infrastructure, customizable glossaries, and translations that sound natural, human, and brand-aligned.

Managing AI localization with a TMS

Today’s Translation Management Systems (TMS) are no longer just workflow tools. They’re becoming the operational backbone of modern localization strategies. Forrester’s report highlights how these platforms are evolving into centralized control hubs, integrating AI platforms like DeepL to handle everything from content routing to quality evaluation.

By embedding AI directly into their TMS, companies can dramatically accelerate localization without compromising on quality or consistency. The result is a faster content lifecycle, where projects are automatically triggered, routed to the appropriate translation method (whether LLM, NMT, or human) and delivered in a fraction of the time. Quality assurance isn’t an afterthought, but built in from the start.

Crucially, this approach unlocks the scale needed for global operations. Businesses can support more languages, markets, and touchpoints, all while maintaining a high bar for accuracy and brand voice. And because systems like DeepL are engineered for enterprise-grade privacy and integration, teams can move fast without cutting corners.

Make the shift to smarter localization

Forrester’s report is a wakeup call. Businesses that treat localization as a static service will fall behind. Those who invest in AI, infrastructure, and leadership will unlock faster growth and global impact. If your organization is navigating this shift (or preparing to), this complimentary report is essential reading.