Rewriting AI-Generated Text into Business Japanese: Common Problem Expressions and Substitution Patterns
Introduction
When trying to use AI-generated Japanese text directly in business materials or web content, it is common to feel that something is off — the text feels difficult to read or is not suitable to share as an internal document. This article categorizes four common problem patterns in AI-generated text and provides concrete rewriting examples for each.
Why Revision into Business Japanese Is Necessary
AI-generated Japanese is influenced by the training data it has seen, which includes blog posts, social media, and personal writing. Even though these expressions may be natural in those genres, they often require adjustment before being used in internal reports, technical specifications, or web content.
A useful criterion is to ask: “Could I write this in an internal technical report or a business proposal?” This makes it easier to identify what needs to be revised.
Pattern 1: Exaggerated Expressions
AI tends to use expressions such as “revolutionary,” “overwhelming,” or “like magic” to emphasize effect or value. These are difficult to use in business documents and can feel out of place to readers.
Revision examples
- “Improve operational efficiency through a revolutionary approach” → “An approach that improves operational efficiency”
- “Processes at overwhelming speed” → “Processes in a short amount of time”
- “Solves complex problems like magic” → “Solves complex problems in few steps”
By writing factually about what changes and how, the content can be conveyed accurately without excessive praise.
Pattern 2: Colloquial Adverbs
Adverbs such as “sakkuto” (casually), “zakkuri” (roughly), and “gattsuri” (thoroughly) are natural in casual conversation but are not appropriate for business documents. They often find their way into AI-generated text.
Revision examples
- “Can be set up casually” → “Can be set up easily”
- “To explain roughly” → “As an overview”
- “Verified thoroughly” → “Verified in detail”
When substituting an adverb, it helps to think about what is being conveyed — speed, simplicity, or depth — to choose the right replacement.
Pattern 3: Figurative Expressions of Danger
Expressions such as “pitfalls,” “landmines,” and “quicksand” attempt to convey problems in a vivid way, but in business documents they tend to lack specificity and create an unnecessarily negative impression.
Revision examples
- “Watch out for configuration pitfalls” → “Points to note during configuration”
- “This choice can easily become a landmine” → “This choice carries risks that should be confirmed”
- “Got stuck in a configuration quagmire” → “A problem occurred that required more time than expected for configuration”
Writing directly about what the problem is and how it can be avoided provides more concrete and useful information for readers.
Pattern 4: Personal Blog-Style Expressions
Headings and phrases such as “I tried using X,” “I got hooked on X,” and “A story about trying out a new tool” are well established in personal blogs, but as headings for technical documents or web content, they tend to convey little information.
Revision examples
- “I tried using Astro” → “The process and results of building a site with Astro”
- “A story about getting hooked on Claude” → “Problems that arose while using Claude and how I handled them”
- “I tried a new tool” → “The evaluation procedure and selection criteria for the tool”
Including “what,” “how I confirmed it,” and “what the result was” in a heading increases the information a reader gets before reading the article.
How to Approach Revisions
When actually revising AI-generated text, the following procedure tends to be efficient.
- Read through the entire text once and mark any parts that feel off
- Classify which of the four patterns each marked part falls into
- Ask “Could I write this in an internal report?” before rewriting
- Read through again after rewriting to confirm that the text reads naturally in polite style
When asking AI to make revisions, providing the instruction “Please revise this into Japanese suitable for business documents. Avoid exaggerated expressions, colloquial adverbs, figurative danger expressions, and personal blog-style phrasing” helps align the direction of revision.
Summary
Problem expressions in AI-generated Japanese can be categorized into four patterns: exaggeration, colloquial adverbs, figurative danger expressions, and personal blog-style phrasing. Using the criterion “Could I write this in an internal technical report or a business proposal?” speeds up the judgment process. Rather than using generated text as-is, developing the habit of checking against these patterns helps maintain consistent quality for business use.