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AI Studies

Good News: 95%+ Home Depot & Lowe’s Reviews are Human-Written in 2025

Are home improvement retailer reviews real or AI-fabricated? Explore the impact of AI on retail reviews for Home Depot and Lowe’s.

Trusted By Industry Leaders
Trusted By Industry Leaders

Customer reviews are playing an increasingly critical role in shaping consumer decisions in e-commerce and retail.

For retailers operating in the renovation and home improvement sector, such as Home Depot and Lowe’s, online reviews serve not only as testimonials but also as powerful tools for attracting new clients and establishing trust. 

However, the increasing accessibility of generative artificial intelligence (AI) tools (like ChatGPT) has begun to blur the line between authentic customer feedback and synthetic content.

As AI-generated text becomes more sophisticated and widespread, it raises important questions about the authenticity and reliability of online reviews in consumer-facing industries.

This study investigates the impact of AI in reviews for Home Depot and Lowe’s (two of the largest home improvement retailers in North America) on Trustpilot from 2018 to 2025. 

Objectives of the Study

This study examines the emergence and growth of AI content in publicly available customer feedback (collected from Trustpilot) for Home Depot and Lowe’s (2018 to 2025).

This analysis focuses on these key questions:

  • What percentage of reviews for Home Depot and Lowe’s are likely AI-generated versus human-written?
  • How has the presence of AI-generated reviews evolved between 2018 and 2025?

Key Takeaways (TL;DR):

  • In 2025, 95.4% of Home Depot and Lowe’s reviews are human-written. 
    • This means that just 4.6% are Likely AI.
  • From 2018 to 2022, AI levels in Home Depot and Lowe’s reviews on Trustpilot remained very low, with rates staying consistently below 2%
  • From 2018 to 2025, the percentage of AI reviews did increase:
    • From just 1.36% in 2018 
    • To 4.6% in 2025 (a 400% rise)
    • Yet, overall AI levels remained low.

This suggests that customers are continuing to contribute human-written reviews about Home Depot and Lowe’s or that steps are being taken to moderate AI content, such as through AI detection.

Note: The levels of AI content found in this study were in line with false positive rates in AI detection. At Originality.ai, our Lite 1.0.1 model has a 0.5% false positive rate, and our Turbo model has an under 3% false positive rate. Find out which AI detection model is best for your use case and read more about AI detection accuracy.

In 2025, Home Depot & Lowe’s Reviews are 95%+ Human-Written

The analysis of customer reviews from renovation retailers, specifically Home Depot and Lowe’s, reveals consistently low levels of AI-generated content in customer reviews.

From 2018 to 2022, AI Home Depot and Lowe’s reviews on Trustpilot remained very low, with rates staying consistently below 2%. 

By 2025, the AI reviews for Home Depot and Lowe’s have increased to 4.6%. Comparatively, from 2018 (when 1.36% of reviews were Likely AI) to 2025, this represents an increase of more than 400%. 

However, in 2025, at 4.6% the percentage of AI reviews is still low, and 95%+ Home Depot and Lowe’s reviews are still human-written.

The findings from this study indicate that while AI-generated content is increasing in Home Depot and Lowe’s reviews, it’s lower than other platforms we’ve studied, such as Snapdeal (22.86% Likely AI in 2024) and Daraz (8.67% Likely AI in 2024). 

How Does This Impact Consumers?

Understanding the extent to which AI-generated reviews are present in this industry is essential for both consumers and businesses. 

For consumers, the presence of fabricated or artificially polished feedback can skew perceptions and lead to misguided purchasing decisions. 

For businesses, the rise of synthetic reviews may distort competitive benchmarks and challenge the integrity of customer engagement metrics. 

So, it’s great to see that there is still a high percentage of human-written content in both Home Depot and Lowe’s reviews.

This suggests that customers are continuing to contribute human-written reviews about the platforms or that steps are being implemented to moderate AI content, such as through AI detection.

Final Thoughts

The findings of this study indicate that overall, Home Depot and Lowe’s reviews are still primarily human-written, which is great news.

For retailers and brands who are looking to tackle an influx of AI-generated reviews, moderation tools such as the most accurate Originality.ai AI Checker can help maintain transparency.

Do you have concerns over whether a post or review you’re reading might be AI-generated? Use the Originality.ai AI detector to find out.

Read more about the impact of AI:

Methodology

Data Collection

This study analyzed customer reviews from Trustpilot Canada for Home Depot and Lowe’s to assess the prevalence of AI-generated feedback in the renovation sector. A Python web scraper using requests and BeautifulSoup extracted review text and timestamps, saving them to a CSV file. The script included polite scraping practices (e.g., one-second delays) and could resume from the last saved page.

AI Detection Procedure

Collected reviews (50+ words) were scanned using the Originality.ai API to detect AI-generated content. An automated Python script handled API calls, retries, and saved results (including confidence scores and AI classification) to the dataset. Progress was saved every 500 rows.

The final dataset included metadata such as company, date, and AI likelihood, supporting year-over-year and cross-company analysis of AI-generated reviews.

Madeleine Lambert

Madeleine Lambert

Madeleine Lambert is the Director of Marketing and Sales at Originality.ai, with over a decade of experience in SEO and content creation. She previously owned and operated a successful content marketing agency, which she scaled and exited. Madeleine specializes in digital PR—contact her for media inquiries and story collaborations.

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Frequently Asked Questions

Why is it important to check for plagiarism?

Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.

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Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.

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Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.

String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.

The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.

Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.

String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.

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Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.

The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.

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