Localization Today

By Claudio Fantinuoli

Generalist AI models are absorbing specialized technologies, reducing products like language tech to mere features. To survive, specialized companies must pursue a combination of meaningful quality advantages, deep niche applications, and careful diversification.

The 2026 NIMDZI 100 report offers one of the clearest snapshots of where the language industry stands today — and where it may be heading next. In this episode of MultiLingual Media’s Localization Today, we speak with Marjolein Groot Nibbelink, lead researcher behind the report, about the major shifts shaping the market.

The conversation explores the sharp rise in productivity driven by AI, the growing pressure on mid-market language service providers, changing staffing patterns, and why demand for experienced linguists remains stronger than many assume. They also discuss the expansion of the report into the NIMDZI 350, the role of collective intelligence in the industry, and how technology investment is reshaping localization business models across regions and company sizes.

Welocalize has been a powerhouse in the language industry for decades, but what happens when the word "localization" no longer describes everything you do? In this episode, Eddie Arrieta sits down with Paul Carr, CEO of Welo Global, to discuss leading a massive organization through a once-in-a-generation technological shift.

Paul discusses the reality of agentic systems like Opal replacing traditional CAT tools, why the industry is shifting from an artisanal model to high-volume information processing, and how enterprise demand is changing.

Interview by Cameron Rasmusson

Translated co-founder Isabelle Andrieu discusses the company’s origins, its preparations for the AI era, and the future it envisions for its many clients and translators. She also offers advice to language service professionals — build your ability to adapt — and leads by example.

By Rishi Anand

The booming language services market benefits from operational automation to assist with complex manual workflows. Translation business management systems (TBMSs) provide the intelligent infrastructure to automate client, vendor, and finance management, enabling efficient scaling and meeting enterprise compliance needs.

By Pham Hoa Hiep

AI is supposed to be a productivity accelerator, enabling linguists to do more work more quickly. But what happens when AI-driven workflows cost more time and frustration than human-driven translation?

By Christine Clay

The author discusses the “pilot-to-production gap” in adopting AI to support multilingual content. Scaling AI requires integrating it into existing translation infrastructure, maintaining human oversight, and consistently applying terminology and translation memory to ensure quality and trust.

By Josevi Abad

As a company focused on improving wellbeing in the business world, we asked the question: Could AI do the same for us? Thanks to intelligent automation, we were able to do just that.

By Maurizia Gregorio

The language industry’s future depends on recognizing that AI requires a human architecture of trained professionals. Linguists and governance experts provide essential accountability, nuance, and oversight that AI cannot replace, and eliminating these roles would destabilize the system.

By Giovanna Patruno

Despite being technically and grammatically correct, AI-generated text reads as empty because it performs only one of six functions of communication. The author examines AI content’s lack of substance from a translator’s perspective and suggests ways reclaim communication as an act of thought and relationship.