Every new tool invites new oversight, and AI is no exception. AI tools like ChatGPT and Claude are everywhere, and thus, AI detection tools are too.
A 2025 McKinsey survey revealed that 71% of organizations regularly use generative AI in at least one department. Unsurprisingly, sales and marketing, product and service, and operations take the lead.
The same survey showed that how brands monitor generative AI outputs varies widely. Some do, some don’t at all. Overall, generative AI adoption is early. We, as a collective, have much to learn about using these tools daily.
With that in mind, marketers, editors, and educators use AI detection tools to verify originality and flag potentially AI-generated work. But those tools don’t necessarily yield crystal-clear results. Content writer Francesca Baker-Brooker states she “can write stuff on quill and parchment and will still tell me it’s AI.”
This viral TikTok video does a good job of capturing that frustration: A student complained that “AI is ruining my college experience” after her original essay was flagged by detection software. That moment captures the growing tension between human creativity and machine judgment.
@cyclebreakingclub AI detectors and technology are failing hard working students more than they’re catching cheaters. #AI #college #student #FYP #relatable ♬ original sound – cyclebreakingclub
This blog unpacks the accuracy of AI detection tools and the consequences of overreliance on them. We’ll also hear from industry experts on their personal experiences (and struggles) with AI detection tools.
TL;DR: The Accuracy of AI Detection Tools
- Results remain inconsistent across tools.
- Detectors often flag human-generated content and miss AI-generated content.
- Inaccurate scores can damage brand trust.
- Editorial judgment and context remain essential.
- Build clear, transparent policies for AI-assisted work.
AI Detection Tools Are Everywhere, But Accuracy Isn’t Consistent
Tools like Grammarly Premium, Copyleaks, and ZeroGPT have become part of content workflows across industries. But there’s a huge question of accuracy and whether they’re actually helping brands stay on top of original content creation.
Backlinker AI founder Bennet Heyn frankly shares that “they’re hit or miss. Someone on our team would spend an hour writing a great email, and the detector would flag it as 95% AI-generated. It’s wild.”
AI detection tools are marketed as accurate, trustworthy safeguards, but their results are mixed at best. Most AI detectors rely on probability models trained on limited datasets, so they mistake style and structure for signals of machine authorship.
Jennifer Phillips April told us, “If you try three different ‘AI’ detectors, you get three different results. At least one will say 100% human-written and another will say 97% AI.”
Research backs up these experiences. A 2024 study in the International Journal of Educational Technology in Higher Education tested seven popular detectors. Results showed they correctly identified non-manipulated AI-generated text only 39.5% of the time, and correctly classified human-written samples 67% of the time, well below the near-perfect accuracy many tools claim.
AI detection tools are good at spotting patterns and data sets. However, Andrew Franks of Reclaim247 notes, “they also end up giving many human-written articles ‘AI written’ labels.”
That inaccuracy isn’t just inconvenient; it’s consequential. Freelancers, students, and professionals have lost credibility or opportunities because a flawed algorithm questioned their integrity.
False Positives: Why Clean Writing Gets Flagged
Writing experts find that polished, confident, structured work is most commonly flagged as AI-generated. This pattern is especially true for technical writing, data-driven writing, social media captions, and product descriptions. All of these writing styles often include structured, clear sentences with heavy industry language.
International SEO consultant Milosz Krasinski says that “Grammarly’s AI detector overreacts to structure and tone.” He adds that their team posted a Bible passage into ZeroGPT, and it was flagged as 100% AI-generated.
On data-driven SaaS marketing copy, ShipTheDeal, CEO Cyrus Partow says work is flagged “even when our own team wrote it.” He adds that “It happens enough now that we double-check everything.”
False Negatives: AI-Heavy Content That Slips Through
On the other hand, some AI-generated content simply isn’t caught at all.
David Cornado of the French Teachers Association of Hong Kong struggles with the “all over the place” nature of AI detection tools. “I’ll use a little AI help on a post, and it gets flagged. Then a completely robot-written article sails right through.”
Krasinski adds that “these tools don’t spot intelligence…they spot predictability.”
How False Positives in AI Detection Tools Undermine Teams and Brand Trust
When AI detection tools produce either a false positive or a false negative, the consequences go beyond workflow friction. Partners can become uneasy in freelance relationships. Partner and freelancer relationships and team morale are the main casualties.
Damaged Partnerships and Distrust
Yarden Morgan of Lusha has had this exact experience: “When a creator’s authentic work gets flagged, it instantly makes our partners nervous.” He adds that when something is flagged as AI, it creates a massive headache. “You’re stuck in a long email chain just to prove the content is original.”
Inaccurate flags mean teams spend time defending real work when they could be focusing on more important tasks. It creates doubt with stakeholders who can be more prone to taking the tool at face value.
At Magic Hour, CEO Runbo Li had a similar experience. For his team, Copyleaks flagged social media captions as AI. He says this had a big impact on partner relationships. “The team has seen this mess with how partners see us, which is a problem in sports where being real matters.” He adds that after that, he takes those scores with “a big grain of salt.”
Internal Bottlenecks and Team Fatigue
Taking every flag seriously will quickly erode writer relationships and your approval cycles. You’ll then use extra time for manual review, which Or Moshe of Tevello has firsthand experience with.
He shares that his team has tried “a bunch” of AI detectors, and says they’re unreliable. “We’ve had our own original descriptions, stuff we spent weeks writing, [be] flagged as AI-generated. It just created more work for us.” He says his team decided to use the detectors as “a quick first pass” and “a person always makes the final call.”
With technical documentation, false positives are common. Alvin Poh, chairman of CLDY.com Pte Ltd, says that as a cloud company, they use AI detectors like ZeroGPT and Grammarly. Yet, the flagging is an annoyance that slows their team down. His advice is “to treat them at a glance, but always have someone review the final copy. The tools miss the point more often than you’d think.”
Why AI Detection Tools Shouldn’t Be the Final Word
In high-stakes workflows, editorial judgment still matters more than a computer-generated score. There’s a risk of not only jeopardizing important creator and partner relationships but of giving away your own editorial say.
Combine Tools and Trust Human Editors
The marketing team at Zentro Internet takes a balanced approach. Vice President Andrew Dunn finds Grammarly hit or miss, so they “use it as a quick check, but I never fully trust the reading. You still need a person to actually look things over.”
Human review can catch what machines miss or misinterpret and bring context and purpose into the final decision.
There are several scenarios in which formulaic messaging, such as product descriptions or industry-specific language requirements, is necessary. Iryna Balaban of Sunlight Cleaning NY has implemented the Copyleaks AI Detector into their workflow as only part of a quality control process. “While the tool generally seems quite useful for an initial scan, it is not infallible,” she said.
“We’ve run into a good number of false positives where even our own clearly human-written content, especially short service descriptions and checklists in standard industry language, are being mistaken for AI-generated.” She adds that this occurs about 30% of the time.
Detection Should Encourage Discussion Instead of Discipline
As with LLMs like ChatGPT and Claude, AI detection tools should be used only as tools. Use flagged content as a reason to investigate with an open mind, not to punish.
If content is flagged as AI-generated and you know it is not, take it as a checkpoint. It might be the perfect opportunity to re-evaluate whether your brand’s tone, structure, or clarity is truly hitting the mark.
What Teams Can Do Instead: Smarter AI Use Policies
Instead of relying solely on fallible detection tools, build clear workflows for content approval and AI use. You may allow light AI-assisted content within reason, as long as it supports originality.
Always include human editors to review the final output with the context and accountability that detection tools can’t offer.
Let’s use Local SEO as an example. This style of writing can occasionally be a trigger for AI-written content. Managing Director at SEO Gold Coast, Sean Clancy, takes it as a warning and not a verdict. He adds, “We then look at those flagged items manually, for a false positive could be a major deterrent in search ranking if we over-edit.”
AI Detection Tools Help, But Human Judgment Matters More
AI detection tools are not the final gatekeeper for whether content is original. Humans are.
False positives, inconsistent scoring, and unpredictable behavior mean they should never be your only source of truth. Use them as a part of an established workflow, but always follow up with human insight.
Treat AI detection tools as a compass, not a judge. Context and conversation will always be the best detectors of originality.
About the Author
Katie Major is a versatile marketing professional with a passion for content creation and strategic storytelling, and she leads creative initiatives as Founder at Major Marketing. To learn more about Katie — and to have her write for your brand — be sure to check out her nDash profile page.