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The widespread availability of generative artificial intelligence (AI) tools has introduced a new dimension to online content creation, including customer reviews.
This has significant implications for industries where consumer trust is paramount, such as the insurance sector.
In Canada, insurance companies occupy a critical role in the financial well-being and risk management of individuals and businesses alike.
From auto and home to health and life insurance, policyholders often rely on online reviews to make informed decisions about which providers to trust.
However, the increasing presence of AI reviews across a number of platforms, including Canadian ‘Big 5’ Banks, Canadian Online Banks, and Glassdoor, raises important concerns.
This study aims to analyze the impact of AI on consumer reviews for Canadian insurance companies.
This study investigates the prevalence of AI-generated content in consumer reviews of Canadian insurance companies between 2018 and 2025.
By examining these aspects, this study aims to offer new insights into how synthetic content is redefining public perception and digital engagement in the Canadian insurance sector.
Our analysis centers on these guiding questions:
The findings are intended to inform both consumers and regulators about the growing need for transparency, accountability, and trust in online reviews.
This trend suggests a significant shift in communication practices for reviews in the Canadian insurance sector.
The analysis of consumer reviews for Canadian insurance companies shows a clear and sustained increase in AI-generated content over the observed time period.
The overall increase from 2018 to 2025 represents a 988% rise in the prevalence of AI-generated reviews.
This sharp upward trajectory highlights the rapid integration of AI tools in consumer-facing digital platforms and signals a fundamental change in how public perception is shaped online.
The growing presence of AI-generated reviews presents both opportunities and challenges for insurers.
While AI-generated tools may enhance linguistic quality and accessibility, their use in customer feedback introduces questions about authenticity, transparency, and influence on purchasing behaviors.
These findings underscore the need for monitoring tools and content moderation strategies that can help preserve the integrity of online review ecosystems in trust-based industries like insurance.
The significant rise in AI-generated content within consumer reviews of Canadian insurance companies presents a notable shift in how feedback is being produced and consumed online.
In a sector like insurance, where customers rely heavily on reviews (given the complexity and long-term nature of insurance contracts), the presence of synthetic content poses important ethical and regulatory concerns.
If a growing share of reviews are generated by AI rather than real customers, the credibility of review platforms could be undermined, and genuine consumer voices may be diluted.
This raises concerns not only for customers making informed decisions but also for companies attempting to maintain fair competition and transparent reputations.
The findings show a 988% increase from 2018 to 2025 in Likely AI insurance reviews, underscoring a rapid evolution in the digital feedback landscape.
While AI-assisted writing offers benefits such as improved clarity and accessibility, its unchecked presence in consumer review platforms presents risks to transparency and trust.
As generative AI continues to evolve and its use becomes more widespread, it is critical that review platforms, regulators, and businesses implement mechanisms for disclosure, verification, and moderation.
In a trust-dependent industry like insurance, preserving the authenticity of customer experiences must remain a priority.
Wondering 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:
This study analyzed the prevalence of AI-generated reviews in the Canadian insurance sector using data from public review platforms and the Originality.ai AI detection tool. The process had two main phases: (1) data collection via web scraping and (2) AI detection using the Originality.ai API.
Data Collection
Consumer reviews of Canadian insurance companies were scraped from Trustpilot Canada using a Python script.
The script supported resumable scraping and included time delays to avoid server overload, producing a large, timestamped review dataset.
AI Detection
Reviews (50+ words) were scanned with Originality.ai, which returned a binary classification and confidence score. A Python script processed each review, logged the outcome, and saved results in batches of 500 to ensure data progress was retained.
Upon completion, the final output was stored in a CSV file containing the review date, company, review content, AI score, AI classification, and scan status.
This structured, scalable method enabled a comprehensive assessment of AI-generated review content in the Canadian insurance industry.
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
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.
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.
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.
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.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
AI & Plagiarism Detector for Serious Content Publishers
(4.4/5 out of 575 reviews)
Originality.ai
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Collingwood, Ontario
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