| Real-world cases showing how AI affects the translation industry and language schools | May 5 |
The overall trend in 2025 is a growing divide: while some sectors adapt, many language professionals face layoffs or exit the industry because of AI’s rapid adoption.
- Some language schools and training centers have downsized staff or closed due to declining enrollment, as AI-powered language learning apps and translation tools replace traditional instruction. In particular, Duolingo terminated agreements with 10% of its contractor workforce in 2025, citing a pivot to AI fo
... See more The overall trend in 2025 is a growing divide: while some sectors adapt, many language professionals face layoffs or exit the industry because of AI’s rapid adoption.
- Some language schools and training centers have downsized staff or closed due to declining enrollment, as AI-powered language learning apps and translation tools replace traditional instruction. In particular, Duolingo terminated agreements with 10% of its contractor workforce in 2025, citing a pivot to AI for content translation, reducing reliance on human translators.
- Over 50% of translation jobs in language service companies now involve machine translation, leading to fewer projects and lower rates for human translators, as reported in the ELIS 2025 survey.
- 23% of freelance translators are considering leaving the industry entirely due to declining fees and reduced demand, a trend linked directly to the rise of AI-driven translation tools (ELIS 2025 survey).
- AI-driven translation solutions have cut per-word translation costs by up to 40%, prompting enterprise clients to reduce or eliminate human translation teams.
- The traditional bread-and-butter translation work is diminishing. Service providers that rely on subcontracts in long supply chains and on traditional translation services struggle to maintain their value proposition. In addition, many small and medium enterprises lack the data, understanding, and maturity to embrace human-in-the-loop localization in the much hyped AI world. This will lead to many small founder-led LSPs’ struggle in the new AI era and the sell or close of their business (2025 Nimdzi 100 report).
- Good enough is just good. Enough. The highest language quality is less and less relevant for buyers for most content types. The acceptance bar is being lowered for non-business critical multilingual communications, partly thanks to LLMs’ deceptively fluent output. However, most organizations still struggle with identifying the right content quality tiers.
- AI data services are growing – and so does the need for AI model training. Data collection, annotation, validation are offered by practically all tech-savvy LSPs, sometimes even under a specific brand name – RWS TrainAI, Welo Data, Uber Scaled Solutions, or Centific Flow, just to mention a few options.
- Demand for generic translation at premium rates has collapsed. Some LSCs now focus only on value-added or niche services, laying off staff who previously handled high-volume, low-specialization projects.
- Audiovisual translation and subtitling roles have also been affected, as AI tools automate much of the process, resulting in layoffs among subtitlers and captioners
- The rise of AI has led to layoffs in language assessment and testing centers, as automated tools now handle placement, grading, and feedback tasks once managed by staff
On the other hand, the rapid rise of generative AI and adaptive neural machine translation (NMT) technologies also creates a wave of new, hybrid roles that blend linguistic, technical, and strategic skills.
- AI Integration Specialist / Machine Learning Engineer
These professionals oversee the implementation and optimization of AI-powered translation tools, ensuring seamless integration with existing workflows and maximizing efficiency and accuracy
- AI Solution Architect
Responsible for designing and customizing AI-driven translation solutions tailored to specific organizational needs, balancing automation with human oversight for quality and compliance.
- AI Ethics Officer
As AI systems handle sensitive multilingual data, these specialists ensure ethical use, data privacy, and regulatory compliance throughout translation processes.
- Localization Consultant / Content Personalization Manager
Experts who combine linguistic and cultural knowledge with AI proficiency to fine-tune machine-generated translations, ensuring they are contextually accurate, culturally relevant, and aligned with brand voice.
- Quality Assurance Manager (AI-Enhanced)
Tasked with reviewing and refining AI-generated translations, these managers set standards, develop evaluation metrics, and oversee continuous improvement of translation quality.
- Data Analyst (Language Services)
Analyzes translation data to identify trends, optimize workflows, and inform strategic decisions, leveraging insights from AI-generated content for business growth.
- Remote Interpreting Coordinator
Manages logistics and technology for virtual interpreting services, ensuring smooth delivery in remote and hybrid environments--a trend accelerated by AI-driven real-time translation.
- Cultural Intelligence Consultant
Advises organizations on adapting content for diverse markets, using AI tools to analyze cultural nuances and enhance localization strategies.
- Healthcare/Legal Localization Specialist
With AI enabling more specialized translation, experts in fields like healthcare and law are in demand to ensure terminology and context are accurate for regulated industries.
- Client Integration Manager
Facilitates onboarding and ongoing support for clients using AI-powered translation solutions, bridging the gap between technology and customer needs
So, once again: you either adapt by acquiring new skills, or leave the profession eventually, because the traditional translation work is rapidly diminishing. ▲ Collapse
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