How to Detect AI Content (Tools + Manual Methods Explained)

People keep talking about AI content, AI writing, and AI detectors. Many say, “Bro, this looks AI-generated” (Haha, that’s today’s writer struggle). But honestly the funny thing is, Google itself, which takes your content from indexing to ranking, doesn’t bother much about these myths, but people have made a lot of hype around them.

I’ve had many debates with well-known companies, and I’ve always proved one point: no matter if it’s AI or human, if the content answers the reader’s need, it will perform well.

Still, some people believe in AI checks, and some don’t. So in this article, I’ll explain “How to check AI Content By Tools & Manually”. In the manual part, I’ll share my personal tips. In the tools part, I’ll share researched methods based on my experience.

So let’s move forward.

Ways to Detect AI Content 

As you can see from the title as well, the words "manually" and "tools" are mentioned in that, so yes, the truth is also that there are two major ways to detect AI content: 

1. By Tools 
2. By Manually

Now, how to check AI-generated content from these two methods and what comes under these—let's cover all in these next sections.

How Tools Detect AI Content

First, let’s be very clear: no AI detector is 100% accurate. Whether it’s a free tool or a paid one, both can make mistakes. Sometimes they mark human writing as AI, and sometimes they miss AI completely.

That’s why my personal advice is: use these tools only for guidance, not as a final decision.

Now, let’s look at all the main methods and techniques these tools use.

1. Linguistic and Structural Analysis

This is the base of most detectors. They check the text’s structure and flow to see if it looks more like machine writing than human writing.

Perplexity (predictability): Tools measure how “surprising” or “unpredictable” your text is. Human writing: usually more surprising, random, and not easy to predict. AI writing: often smooth, predictable, and follows patterns.

Burstiness (sentence variety): Tools check how much sentence length and style change. Humans: mix short, long, and even broken sentences. AI: usually keeps a steady, uniform length and rhythm.

Repetition check: AI tends to repeat certain words, phrases, or sentence structures. Humans usually mix it up more.

My note: This is the most common detection method. If your text feels too flat or too “perfect,” detectors may highlight it if it is purely human-written or AI-generated.  

2. Machine Learning Models

These tools are trained on huge datasets of human-written and AI-written text. They learn the patterns of both.

When you paste text:

• The detector compares it against the patterns it already knows.
• If your writing matches common AI styles, it gets flagged.

My note: Remember, these tools can only check against what they were trained on. If AI writing style changes, detectors may fail.

3. Statistical Models (Word Frequency & n-grams)

Some detectors use math-based models to look at how words appear together.

• If word combinations look too balanced or too “machine-like,” they may flag it as AI.
• Humans often have more irregular, emotional, or imperfect word choices.

My note: If your text is too “clean” or “balanced,” it often looks suspicious to these models, and they mark that content as AI-generated. 

4. Semantic Meaning Analysis

There are some advanced detectors that don’t just check structure; they try to understand meaning.

• If the sentences sound empty, lack real emotion, or feel too plain, they may be marked as AI.
• Human writing often has depth, personal experience, or small details.

My note: But again, if you add some personal opinions, examples, or emotions, it makes text harder to flag as AI-generated.

5. Pattern & Tone Consistency (AI Trackers)

Some detectors (sometimes called AI trackers) look at tone and rhythm.

• If the tone is too consistent, the same style from start to end, it often looks AI.
• Humans naturally change tone: serious here, casual there, and emotional in between.

My note: This is why I recommend breaking the monotone style in your writing, which includes avoiding the repetition of the same ideas, words, or sentence structures, even when using AI chatbots! 

6. Database Comparisons

Many detectors keep a library of samples of both AI and human writing.

• When you paste your text, they compare it with their stored samples.
• If your content matches AI samples, they flag it.

My note: This is why results can vary between tools because each has a different library.

7. Formatting and Layout Checks

Some detectors also check formatting:

• Equal-sized paragraphs, the same sentence length, and perfect alignment can look suspicious.
• Human writing usually has uneven breaks and a more natural flow.

My note: Don’t format your text to look “too perfect.” Humans write unevenly. And you can do this with AI chatbots too. 

8. Watermarking

One of the most advanced methods is AI watermarking.

• Some AI models secretly add hidden signals (like tiny patterns in word choice).
• Special detectors can later read these signals.

But here’s the catch: not all AI tools use watermarking, so it doesn’t work everywhere.

My note: Rarely reliable, only works for certain AI systems.

9. Probability Scoring (AI Content Detection Score)

Most detectors finally give you a score or percentage — e.g., “80% human, 20% AI”.

• This score is based on all the checks above.
• It’s not a guarantee, just an estimate.

My note: Never panic over one score. Always cross-check with multiple tools and never rely completely, please. 

Some Popular AI Detectors

These are the AI detector tools that caught a lot of hype. But remember: they all work on the same methods I explained above. I’ve tested each one, and honestly, your human brain is smarter than any of them. 

Still, you can use these tools as helpers when you need them. Here’s my updated list with accuracy scores:

1. Turnitin AI Detector: Most trusted in universities. Strong for academic work, but sometimes too strict. Can flag human writing if it looks too “perfect”.
2. CopyLeaks AI Detector: Popular among companies and schools. Accurate for catching ChatGPT-style text, though it can be harsh on formal human writing.
3. Scribbr AI Checker: Great for research and long essays. Gives a detailed report, works better on bigger documents than short notes.
4. Quillbot AI Detector: Mainly a paraphrasing tool, but its AI check is decent for quick scans. Simple and fast, not the deepest.
5. ZeroGPT: Famous for being free and easy. Good for surface-level checks, but weak on edited or mixed content.
6. Quetext AI Detector: Clean design, useful for bloggers. Works okay but is not very sharp in spotting rewrites.
7. Grammarly AI Detection: Handy if you already use Grammarly, but the AI detection is basic. Better for grammar than AI checks.

Manual Methods to Spot AI Writing

When I read a piece of content, I can usually tell pretty quickly if it’s written by a machine. The way I do it is simple: I slow down, read the flow, and ask myself, “Does this sound like a person with real thoughts, or like a machine giving a polished answer?”

For me, the giveaway signs are:

• The tone feels too clean, with no rough edges and no quirks.
• The same words keep popping up again and again (like “significant,” “crucial,” “in addition”).
• I see long, balanced sentences that look like a grammar book instead of natural speech.
• The writer avoids real personal experience; it’s all generic.
• And many times, the text sounds like a school essay intro (“In today’s world… It is important to note that…”).

That’s how I spot it. Now allow me to share the complete sheets I use in my mind whenever I test content.

Mega AI Spotting Sheets

Below is the full catalog of fingerprints, vocabulary, phrases, sentence styles, structures, and patterns that scream “AI wrote this”. 

1. Punctuation Fingerprints

When you read carefully, punctuation often gives away whether the text is written by AI. Below are the most common punctuation fingerprints to watch for:

1. Too many commas (,) → AI often adds extra commas where people wouldn’t pause.
2. Missing commas where needed (,) → Sometimes it skips commas, making run-on sentences.
3. Overuse of semicolons (;) → AI uses semicolons more than humans usually do.
4. Textbook-perfect semicolon use (;) → Always correct, too neat to feel natural.
5. Uses em-dash (—) instead of hyphen (-) → AI puts em-dashes where humans use hyphen.
6. Too many colons (:) → Frequently introduces points or lists with colons.
7. Uniform quotation marks (“ ”) → Always the same style, no mix of ‘ ’ and “ ”.
8. Apostrophes always the same (’ or ') → No curly vs straight variation, always neat.
9. Parentheses overused ( ) → Side notes inside brackets appear more than natural.
10. Perfect spacing after punctuation → Always one space, no slips or extras.
11. No accidental double spaces → Never the human habit of two spaces after a period.
12. Ellipses always three dots (…) → Exactly three, never two or four.
13. No mixed punctuation combos (!?, ?!, etc.) → Avoids playful mixes like “?!” or “!?”.
14. Single exclamation mark only (!) → Never uses “!!” or “!!!” for emotion.
15. Single question mark only (?) → Always one, never “??” or “???”.
16. Choppy sentences with many full stops (.) → Breaks thoughts into too many short lines.
17. Bullet lists perfectly consistent → Every item follows the same punctuation style.
18. Oxford comma use is fixed → Either always used or never, no variation.
19. Quotation punctuation always consistent → Always the same inside/outside rule.
20. No dangling punctuation → Brackets, quotes, and parentheses are always closed.
21. Hyphenation is too consistent → Compound words handled one strict way.
22. No stray spaces before punctuation → Never a space before a comma or period.
23. No accidental punctuation typos → No missing commas, no extra dots, too clean.
24. Perfect numbered lists (1., 2., 3.) → Always uniform and tidy.
25. Dates/times always follow one style → Example: always “May 5, 2025” or always “5 May 2025”.
26. Brackets/square brackets tidy [ ] → Always closed, no slip-ups.
27. No creative punctuation mixes → Avoids unusual combos like “—,;”.
28. Standard ASCII punctuation only → No old-style or quirky Unicode marks.
29. No emoji + punctuation mixing → AI separates emojis from punctuation and feels stiff.
30. Even punctuation rhythm → Sentence endings follow a predictable, steady pattern.

2. Sentence Structure Fingerprints

AI text may look fine, but the way sentences are made often feels different from human writing. Here are some common signs:

1. Same length sentences → AI often writes sentences that are too similar in length, making the flow feel mechanical.
2. Overly balanced sentences → Sentences look perfectly structured with equal parts, like they came from a grammar book.
3. Choppy short sentences → AI sometimes breaks one idea into many tiny, robotic sentences.
4. Long and over-explained sentences → Other times it creates very long sentences stuffed with extra words.
5. Repeated sentence openings → Many lines start with the same pattern like “In addition,” “Furthermore,” or “Overall”.
6. Predictable transitions → AI reuses connectors such as “Moreover,” “Therefore,” “However” too often.
7. Limited variety in structure → Sentences mostly follow Subject-Verb-Object order, with little creativity.
8. Rare use of fragments → Humans sometimes write incomplete thoughts for effect (“Not good.” “So true.”), but AI avoids this.
9. No natural rhythm shifts → Human writing goes fast/slow naturally; AI keeps one steady pace.
10. Too consistent in tone → Each sentence carries the same level of formality, no ups or downs.
11. Lack of broken flow → Humans often break sentences with interruptions (—, parentheses, or pauses), AI rarely does.
12. Repetitive phrasing inside sentences → AI often doubles phrases (“important and significant,” “helpful and useful”).
13. Over-explains obvious things → Sentences may restate what was already clear, wasting space.
14. Rare use of one-liners → Humans drop short, punchy lines for impact; AI rarely dares to.
15. Limited creativity in questions → AI writes plain questions but avoids rhetorical or playful ones.
16. Too many middle-length sentences → AI fills text with medium-length sentences, avoiding extremes.
17. Parallel structures too neat → Sentences like “We need to eat well, to sleep well, and to work well” appear too polished.
18. No sentence “surprises” → Humans sometimes twist or break grammar for style, AI sticks to safe rules.
19. Heavy use of passive voice → AI often writes “It was decided that…” instead of “We decided…”
20. Lack of contractions → AI prefers “it is,” “do not,” instead of “it’s,” “don’t”.
21. Conditional templates (if/then) → AI loves structured conditions like “If you do this, then that will happen.” Feels predictable.
22. Cause-effect patterns everywhere → AI often ties points into “because X, therefore Y” structures, even when not necessary.
23. Predictable list sentences → AI often breaks things into tidy “three reasons” or “five points.” Humans aren’t always so neat.
24. Over-logical flow → AI forces everything to connect step by step, leaving no “loose thoughts,” while human writing allows gaps.

3. Vocabulary Fingerprints

AI often uses words in ways that feel a bit “too perfect” or “too safe.” Here are some common signs in vocabulary:

Adjectives / Adjective Phrases

The list of AI-ish adjectives: 

1. significant → big / major / noticeable
2. crucial → key / a big deal / must-have
3. essential → needed / must / can’t skip
4. vital → really important / life-saving (rarely use)
5. important → main / big / worth noting
6. beneficial → helpful / handy / useful
7. valuable → worth it / super helpful
8. effective → works / gets results / does the job
9. efficient → quick / smooth / saves time
10. optimal → best / just right / ideal
11. robust → strong / solid / reliable
12. innovative → new / fresh / clever
13. dynamic → lively / changing / active
14. sustainable → long-lasting / can keep going
15. reliable → steady / trustable / works every time
16. practical → handy / useful in real life
17. comprehensive → complete / covers everything
18. holistic → whole-picture / all-around
19. granular → detailed / broken down
20. notable → worth mentioning / stands out
21. substantial → a lot / big / major
22. marginal → tiny / minor
23. negligible → barely anything / hardly matters
24. straightforward → simple / easy
25. complex / complicated → tricky / messy
26. ambitious → bold / gutsy / big
27. impactful → makes a difference / strong
28. relevant → useful here / fitting
29. cutting-edge → latest / new / modern
30. groundbreaking → first-of-its-kind / bold idea

Verbs

The list of AI-ish verbs: 

1. utilize → use
2. leverage → use / make the most of
3. facilitate → help / make easier
4. mitigate → reduce / soften / lessen
5. optimize → make better / tweak
6. prioritize → focus on / handle first
7. allocate → give / set aside
8. implement → put in place / do
9. establish → set up / start
10. ascertain → find out / check
11. constitute → make up / are
12. comprise → include / are made of
13. encompass → include / cover
14. demonstrate → show / prove
15. illustrate → show / give an example
16. highlight → point out / call out
17. provide → give / offer
18. ensure → make sure / guarantee
19. promote → push / support / share
20. maintain → keep / continue
21. address → deal with / fix
22. resolve → fix / sort out
23. catalyze → spark / start
24. augment → add to / boost
25. bolster → support / strengthen
26. harness → use / tap into
27. transform → change / turn into
28. accelerate → speed up / make faster
29. deliver → give / bring / send
30. streamline → simplify / make smoother

Buzzword Stacking (AI habit)

AI loves to chain many fancy words together to sound smart.

• AI chains: “innovative, robust, comprehensive, cutting-edge solution.
• Human: “A good, new idea”

Over-Intensifiers

AI often makes things sound too strong with heavy words.

• AI: “Highly effective, extremely beneficial, remarkably significant”
• Human: “Really good, super helpful, pretty big”

Forced Synonyms (AI filler habit)

AI repeats the same meaning with different words to stretch the text.

• AI: “important and significant, helpful and useful”
• Human: picks one word and moves on: “important” OR “helpful.

5. Transition Word Fingerprints

AI often uses too many linking words to make sentences flow “too smoothly.” Humans use them less often and mix them naturally.

1. Moreover → AI uses this too often to add points → humans just say also / plus / or start a new sentence.
2. Furthermore → Sounds formal and over-polished → humans say and / what’s more / plus.
3. In addition → AI stacks this to add details → humans might just start fresh or say on top of that.
4. Therefore → AI loves cause-and-effect links → humans use so / that’s why.
5. Thus → Same as therefore, but stiffer → humans rarely use it in casual writing.
6. Hence → Over-academic → humans say so / because of that.
7. Consequently → AI uses this to sound smart → humans prefer as a result / so.
8. Accordingly → Formal and uncommon → humans simply explain the result.
9. Nevertheless → Too polished for most natural writing → humans say even so / but still.
10. Nonetheless → Same issue as nevertheless → humans use still / even then.
11. However → AI puts this at the start of many sentences → humans break flow with but or rephrase.
12. On the other hand → AI loves perfect comparisons → humans might say but also / then again.
13. Conversely → Textbook style → humans just say but / opposite.
14. In contrast → AI uses this in essays → humans say but / unlike.
15. As a result → AI chains cause-effect too neatly → humans just write so.
16. For instance / For example → AI often repeats these instead of blending examples into the story.
17. In conclusion → Classic AI wrap-up → humans may simply end or use to sum up.
18. To summarize → Same as above → humans just close naturally.
19. Subsequently → Formal sequence marker → humans say later / after that.
20. Thereafter → Very old-school → humans use after that.
21. Meanwhile → AI sometimes overuses to connect scenes → humans just switch without signaling.
22. Additionally → A softer moreover → still used too much by AI.
23. In fact → AI uses it as filler → humans skip it or say actually.
24. Indeed → Formal emphasis → humans rarely use it unless dramatic.
25. As such → AI uses this to conclude → humans say so / because of that.
26. All in all → AI may use this cliché → humans simply wrap up.
27. Overall → AI likes this for summaries → humans often skip.
28. Firstly / Secondly / Lastly → AI lists points too neatly → humans mix order or skip numbering.
29. Likewise → AI mirrors points with this → humans say same here / just like that.
30. Conversely speaking → Overly formal combo → humans rarely use it.
31. Consequently therefore (double link) → AI sometimes stacks two connectors for extra polish.

 6. Phrase Fingerprints

AI often repeats ready-made phrases that sound polished but not natural.

1. “It is important to note that…” → AI filler phrase → humans just say remember this / or skip it.
2. “It should be mentioned that…” → Over-formal → humans write the fact directly.
3. “One of the most important aspects is…” → Stiff → humans say a big part is….
4. “It can be seen that…” → Passive + vague → humans just say you can see… or give the fact.
5. “In today’s fast-paced world…” → Classic AI/essay cliché → humans start naturally with context.
6. “With that being said…” → AI transition filler → humans say but… / still….
7. “As previously mentioned…” → Too neat → humans rarely remind like this.
8. “The following points will highlight…” → Robotic → humans just list without intro.
9. “Another key takeaway is…” → AI loves this → humans say another point is….
10. “It goes without saying that…” → AI filler → humans just state the thing.
11. “In order to…” → AI uses this instead of just to.
12. “For the purpose of…” → Formal filler → humans just say to.
13. “Plays a crucial role…” → Overused → humans say matters a lot / really helps.
14. “Significant impact…” → Common AI phrase → humans say big effect / changed things.
15. “On the other hand…” → Used too often for contrast → humans just say but.
16. “It is worth mentioning that…” → Extra fluff → humans skip or say also.
17. “A wide range of…” → Overused set phrase → humans say many / lots of.
18. “Has become increasingly popular…” → AI default → humans say more people use it now.
19. “Ever-evolving landscape…” → AI essay cliché → humans say things keep changing.
20. “At the end of the day…” → Overused closer → humans say in the end.
21. “In conclusion / To summarize…” → AI sign-off → humans just wrap naturally.
22. “A growing body of research…” → AI loves this → humans say more studies show….
23. “The fact of the matter is…” → Filler → humans skip and just give fact.
24. “Leads to better outcomes…” → AI phrasing → humans say works out better.
25. “Provides valuable insights…” → Common AI → humans say gives useful ideas.
26. “Cutting-edge technology…” → Buzzword → humans say new tech.
27. “Groundbreaking innovation…” → Over-polished → humans say a fresh idea.
28. “Holistic approach…” → Cliché → humans say whole picture / all-around view.
29. “Unlock potential…” → AI buzz → humans say make the most of / help you use better.
30. “Paves the way…” → Too literary → humans say helps start.

7. Repetition & Rhythm Fingerprints

AI doesn’t just write; it falls into patterns. These patterns feel “too tidy” or “too robotic.” Humans break rhythm naturally. Let’s unpack all the fingerprints.

1. “Very + adjective” spam → AI: very effective, very helpful, very important. Human: super useful, crazy big, really good.
2. Neat paragraph wrap-ups → AI: closes every paragraph neatly. Human: paragraphs may end abruptly or trail off naturally.
3. Balanced contrasts → AI: on the one hand… on the other hand… Human: sometimes good, sometimes bad (more casual, less rigid).
4. Predictable sentence rhythm → AI: every sentence is polished and uniform. Human: mixes short fragments, long sentences, and occasional slang.
5. Even paragraph length → AI: all paragraphs around 3–5 sentences. Human: some paragraphs are 1 line, some are long and rambly.
6. Repetitive connectors → AI: keeps using “therefore,” “moreover,” “in addition” in every paragraph. Human: uses few connectors, often skips them.
7. Consistent tone → AI: every sentence sounds formal and even. Human: tone goes up and down, can be casual or emotional.
8. Overly neat lists → AI: points always follow 3–5 neat items. Human: lists vary in length or sometimes merge into sentences.

8. Passive Voice Fingerprints 

AI often prefers the passive voice, which can make text feel distant or overly formal. Humans use it less.

1. “It is decided that…” → AI: “It is decided that the project will start next week”. Human: “We decided to start the project next week”.
2. “It was suggested that…” → AI: formal, indirect → humans usually say: “They suggested…” or “I suggest…”
3. “It has been observed that…” → AI: overused to sound academic → humans: “We observed…” or “People noticed…”
4. “It can be seen that…” → AI: filler phrase → humans: “You can see…” or just state the fact.
5. “It is believed that…” → AI: neutral and vague → humans: “Experts believe…” or “I think…”
6. “It was found that…” → AI: common in research-style writing → humans: “We found…”
7. “It should be noted that…” → AI: filler for emphasis → humans skip it or say: “Remember that…”
8. Overuse of “by” in sentences → AI: “The data was analyzed by the team, and conclusions were drawn by experts”. Human: “The team analyzed the data and drew conclusions”.
9. Overly long passive chains → AI: “The new system was designed by the engineers, tested by the QA team, and implemented by management”. Human: “Engineers designed the system, QA tested it, and management implemented it”.
10. Avoids first-person / active subjects → AI: “Mistakes were made during testing”. Human: “We made mistakes during testing”.

9. Business / Academic Jargon Fingerprints

AI overuses corporate/academic terms. 

1. Stakeholders → People involved / the team / those affected
2. Scalability → Can it grow? / able to expand / handle more
3. KPIs → Results / numbers that matter / performance measures
4. Deliverables → Work / tasks / things to finish
5. Framework → Plan / structure / outline
6. Methodology → Method / way to do it / process
7. Discourse → Talk / discussion / conversation
8. Strategic alignment → Agreement / shared plan / on the same page
9. Value proposition → Main benefit / what’s in it for you / key advantage
10. Holistic approach → Big picture / whole view / all-around approach
11. Best practices → Good tips / proven ways / what works well
12. Leverage → Use / make the most of / apply
13. Synergy → Teamwork / combined effort / working together
14. Paradigm → Model / example / way of thinking
15. Ecosystem → Network / system / environment
16. Optimize → Make better / improve / tweak
17. Benchmark → Standard / example / point of comparison
18. Core competency → Main skill / strength / best ability
19. Thought leadership → Expert advice / guidance / smart ideas
20. Value-added → Extra benefit / something useful / bonus
21. Streamline → Simplify / make easier / smooth process
22. Cross-functional → Different teams working together / multi-team
23. Leverage points → Key areas to use / main opportunities
24. Deliverables roadmap → Task plan / schedule / step plan
25. Actionable insights → Useful info / tips you can use / practical advice
26. End-to-end solution → Complete plan / full setup / covers everything
27. Mission-critical → Really important / essential / must-have
28. Stakeholder engagement → Talking with people involved / team involvement
29. Operational efficiency → How smoothly it works / easy workflow
30. Scalable solution → Something that can grow / expand easily

From My Experience: Who Wins, AI Detectors or Human Eye?

Guys, I want to share my real test with you. I wrote a article myself, fully researched and drafted without AI, and then tested it on a paid AI detector. Shockingly, it flagged 50% of my content as AI. I couldn’t believe it. I tried again on a free detector, and this time it marked 60% as AI. Honestly, I was stunned.

To dig deeper, I asked ChatGPT to generate content on the same topic. Then I made some human edits, changing those solid AI-style phrases and fingerprints I told you about earlier. I kept only natural words and patterns. After running it through the same detectors, the results were eye-opening: one showed just 15% AI, and the other said it was 100% human.

So yes, I literally fooled the detectors just by replacing a few patterns.

That’s why my final takeaway is simple: today, the real winner is AI + Human Effort. If you blend smart AI generation with real human refinements and ensure your content solves the user’s need, then no detector can stand in your way.

Separating Truth from Myths: AI vs Human Content

There’s a common belief that AI detectors can always tell whether something is human-written or AI-generated. That’s a myth. As I tested myself, even original, manually written content often gets flagged as AI. Detectors work on probability, not certainty, so they sometimes misjudge even authentic writing.

Another myth is that AI-generated text can never pass as human. The truth is, with a few smart edits….. like replacing corporate-sounding words, breaking perfect sentence patterns, and adding real human quirks, you can make AI content appear natural enough to fool most tools.

One more misconception is that humans cannot compete with AI’s polish. The reality is, a human reader with writing experience can often spot robotic flow instantly, no matter how advanced the tool or how neat the content looks.

So here’s the bottom line: detectors are useful helpers, but the real test still lies with the human eye and brain. Tools can be tricked, but human instincts are much harder to fool.

Final Note

I hope you all found this article helpful on how to detect AI content by using AI tools and manual methods. I’ve put in my 100% to research and share everything clearly for you. The goal was to make it easy to understand and practical so you can apply it right away. Remember, no tool is perfect, and human judgment still matters the most.

If anything is unclear or you have questions, tips, or thoughts, please drop them in the comment section. I’d love to hear from you and help you out! 

FAQs 

Here are some of the most commonly asked questions related to how AI writing is detected: