24 Apr AI in Localization: How It’s Reshaping Language Services
AI in localization is no longer a concept of the future. It’s already transforming how language service providers work—streamlining workflows, improving quality, and speeding up delivery. According to the GALA Business Barometer 2025, 85% of organizations now use AI tools to support or automate localization processes. Whether through machine translation or smart project management systems, AI is changing the game.
But this shift isn’t just about cost-cutting. It’s about staying competitive in a digital world where speed and consistency matter more than ever. If your business still relies on traditional localization methods, it’s time to explore how AI can offer a smarter, scalable solution.
Adoption and Use: A Tale of Two Sectors
AI in localization has seen rapid uptake, especially among end-clients who are 15% more likely than LSPs to adopt AI tools. They’re not just translating—they’re automating customer service, operations, and project creation too.
From neural machine translation (NMT) to large language model (LLM) integrations, AI helps smaller companies focus on core tasks and allows larger players to extend automation across departments.
Still, trust and security are key concerns. Only 20% use free AI tools, while most favor enterprise-level options to keep data protected.
“AI is not just about technology—it’s also about trust, alignment, and strategy,” the GALA report says.
Automation and Data: Building Smart Workflows
Many organizations automate workflows, but full automation is still rare. 58% of respondents automate at least one workflow per month. LSPs lead in automating admin tasks like invoicing, while end-clients prioritize AI-powered translation and project setup.
Still, only 30% of data is considered AI-ready, meaning the industry has a long way to go. Companies are making progress with annotation and governance, but many still overlook key steps like data cleaning.
Data services and internal AI model training are becoming more common, especially among high-revenue companies. However, 68% of LSCs still don’t perform data cleaning, a critical gap that could impact AI accuracy and trust.
“AI-powered outcomes are only as good as the data that fuels them,” the report emphasizes.
Business Impact and Challenges: ROI, Ethics, and People
AI in localization is delivering strong returns. 70% of companies believe AI investment is worth it, and reported ROIs range from 4% to as high as 25%. The primary benefits? Speed, efficiency, and quality—with client feedback largely positive and zero dissatisfaction reported.
However, the path isn’t without challenges. Organizations cite barriers such as:
- Lack of in-house AI expertise
- Integration issues with legacy systems
- Concerns about data security, privacy, and brand alignment
- Skepticism or resistance from staff and clients
On the workforce side, 80% of companies plan to retrain staff rather than replace them, indicating AI is seen as a productivity enhancer, not a job killer.
Ethical use of AI is gaining attention, but formal policy adoption remains low—only 35% of companies have documented AI ethics guidelines. Still, 60% have someone responsible for oversight, and human review remains the most common safeguard.
Conclusion: Toward a Smarter, Safer Future
The localization industry is entering an AI-powered era, marked by automation, new service models, and evolving workforce roles. Yet challenges persist—particularly around data, integration, and trust. For organizations willing to invest in AI training, ethics, and infrastructure, the payoff can be substantial.
Looking ahead, the industry anticipates fully automated translation workflows, custom LLM development, and expanded multimodal content services. AI isn’t just a tool—it’s becoming a cornerstone of how the language services ecosystem delivers value in a globalized world.
As one respondent put it: “AI can handle 90%+ of translations. Humans will be needed only for specialized, high-stakes work.”
Looking for a better way to manage multilingual content? Check out how we help clients integrate AI in localization: read our case study.
