Updated on: Friday, January 02, 2026
AI generated content has brought about significant advancements in various fields. However, recently, separating human written text from AI generated text has become increasingly challenging. In this article, you will get to know how you can understand AI generated content.
Overused Transitional Words
AI tools often rely on certain transitional words to create narratives. While these words are useful, their overuse can signal that the content has been generated by AI. Here are some common examples:
Accordingly
Additionally
Arguably
Certainly
Consequently
Hence
However
Indeed
Moreover
Nevertheless
Nonetheless
Notwithstanding
Thus
Undoubtedly

Frequently Used Adjectives
Adjectives level up any description, but AI sometimes spams the same polished vibes over and over. That repetition makes the writing feel low key mechanical instead of human. Linguists point out that AI text often leans on overly positive or “corporate” adjectives because they are statistically safe choices that fit many contexts (Grammarly, April 9 2025, Decoding AI Language: Common Words and Phrases in AI-Generated Content)
Some of the commonly used adjectives that AI uses are:
Adept
Commendable
Dynamic
Efficient
Ever-evolving
Exciting
Exemplary
Innovative
Invaluable
Robust
Seamless
Synergistic
Thought-provoking
Transformative
Utmost
Vibrant
Vital

Commonly Used Nouns
AI writing often leans on broad, abstract nouns that make the text feel formal but strangely empty. Linguistic research shows that AI generated text tends to use more nouns than human writing, which creates a stiff and impersonal flow compared to natural language (Terčon and Dobrovoljc, October 1 2025, Linguistic Characteristics of AI-Generated Text: A Survey)
Here are some nouns that AI uses frequently:
Efficiency
Innovation
Institution
Integration
Implementation
Landscape
Optimization
Realm
Tapestry
Transformation

Overused Verbs
AI written text often leans on a narrow set of verbs that promise action but end up feeling repetitive. One detailed study found that around two thirds of the “style” words are over used by generative text models were verbs. These increases are far above what normal writing evolution would suggest (Frank Landymore, July 2, 2024, Research Shows That AI-Generated Slop Overuses Specific Words).
Certain verbs are frequently used by AI tools to convey action and engagement. Here are a few of those:
Aligns
Augment
Delve
Embark
Facilitate
Maximize
Underscores
Utilize

Common Phrases Indicative of AI Generated Text
AI generated text often includes specific phrases that can make the content seem robotic. These phrases include:
A testament to…
In conclusion…
In summary…
It’s important to note/consider…
It’s worth noting that…
On the contrary…

Examples of AI Generated Text Indicators
The following indicators help you catch the robotic flow before it slips by:
a. Recommendation Letter
When AI generates a recommendation letter, it often results in vague and verbose text without concrete examples. Signs include:
Lack of specific instances of achievements or contributions.
Overuse of adverbs such as “enthusiastically,” “closely,” “consistently,” “flawlessly,” and “efficiently.”
Usage of uncommon phrases in human written texts like “professionalism,” “furthermore,” and “meticulous attention to detail.”

b. Data Analyst Cover Letter
An AI generated cover letter for a data analyst position may exhibit the following traits:
Vague, meaningless phrases such as “I am confident in my ability to contribute effectively to your team and drive insightful data-driven decisions.”
Absence of specific examples of data projects.
Excessive use of adverbs like “effectively,” “efficiently,” “successfully,” and “cross functionally.”

c. LinkedIn Outreach Note
AI generated LinkedIn notes often sound unnaturally formal and lack specificity:
Formal subject lines like “Inquiry about Data Analyst Position at UVA.”
Usage of infrequent words in human written text like “keen,” “dynamic,” “inquiry,” “deriving.”
Vague phrases such as “exciting work being done at your institution,” “passion for deriving insights from data,” and “dynamic team like yours.”

d. Email about Data Analysis Findings
Emails drafted by AI on data analysis findings often contain:
Overuse of adverbs like “additionally,” “consistently,” “effectively,” and “strategically.”
Unnatural greetings and sign offs, e.g., starting with “Dear Stakeholders” and ending with “Best regards.”
Long, vague sentences such as “highlights the importance of concise and focused messaging,” “present valuable opportunities for optimizing…”

e. Resume Summary
AI generated resume summaries often feature:
Vague phrases like “results driven,” “solid foundation,” “actionable insights,” “innovative solutions,” and “strong collaborator.”
Lack of specific examples or certifications.
Unusual phrasing like “University of Virginia ecosystem,” “leveraging 4 years experience.”

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Frequently Asked Questions (FAQ)
Look for patterns like overuse of certain words, flawless grammar and a lack of real world depth. AI often sounds “polished” but strangely empty.
They work fairly well but are not 100% accurate. Always use them as a supporting tool, not the final judge.
It often feels repetitive, generic or oddly “too formal.” Real human writing usually shows personal tone or errors.
Sometimes yes, but smart detectors still catch it. Adding your own examples, opinions or unique details makes it far harder to flag.
Because AI lacks lived experience. It can mimic structure but not true emotions or originality.
They skim for vague statements, generic transitions and lack of concrete evidence. Humans usually cite specifics; AI tends to stay broad.
Conclusion
To successfully identify AI generated text, you must develop a keen eye for specific overused words, phrases and writing patterns. When you understand these indicators, you can better distinguish between human and AI generated content.
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