We created this series for business professionals who are exploring AI translation but are unsure where to begin. We plan to publish one article each week in the following order.

This series is built around the real questions companies face when considering AI translation adoption. Based on hands-on field experience, it offers practical and candid answers. We hope it will serve as a useful guide.

Part 1. Where Should You Start with AI Translation? (Now Available)

This article offers a practical starting point for the five questions companies ask most often when they are interested in AI translation but still have concerns: quality, terminology, security, cost, and differences between vendors. It also speaks honestly about the fact that AI translation is not effective for every project.

Part 2. Why Do Results Differ So Much If Everyone Uses AI Translation? (Coming Next Week)

Many translation providers say they use AI, but the quality of their output can vary widely. This article explains five criteria that many companies overlook when comparing vendors. It also provides practical questions you can use immediately in vendor meetings.

Part 3. How to Go Beyond the Limits of General-Purpose AI Models (Coming Soon)

General-purpose AI such as ChatGPT performs impressively in everyday translation, but its performance often becomes unstable in specialized fields. This article explores how domain-specific AI is built, how customer data security is protected, and why customer-dedicated models may become an important new possibility.

Part 4. Is AI Translation Effective for Every Project? (Coming Soon)

Some projects benefit dramatically from AI translation, while others become more inefficient because of it. This article explains, in straightforward terms, how workflows change depending on whether translation memory (TM) already exists, based on the actual processes used in translation operations.

Part 5. Where Do AI Translation Quality Failures Happen, and How Can You Prevent Them? (Coming Soon)

This article examines four common points where AI translation quality problems tend to occur—source content quality, fluent mistranslations, terminology inconsistency, and broken feedback loops—and explains how each of them can be prevented.

Part 6. What You Must Check Before Adopting AI Translation (Coming Soon)

Before making a final decision on an AI translation vendor, there are critical points that must be confirmed in the contract. This article provides a checklist organized into three areas: security, quality, and terminology management. It is designed as a practical tool you can take into vendor meetings.

This series is based on Hansem Global’s real-world experience in AI translation operations. For questions about any article or to discuss AI translation for your business, please contact Hansem Global.