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In the digital age, online reviews have become a critical component of consumer decision-making, especially as e-commerce platforms, like Myntra, have gained popularity.
Crunchbase notes that Myntra received 59.7 million monthly visits last month (as of May 2025), and further, on the Google Play Store, the app has 100 million+ downloads.
As the popularity of shopping apps has grown, so too has the volume and influence of user-generated content, considering that consumers often rely on product reviews to assess quality and usability before making a purchase.
However, with advancements in artificial intelligence (AI), a new phenomenon has emerged: the generation of product reviews using AI models.
This study investigates the prevalence of AI-generated reviews on the Myntra shopping app. Through this analysis, we hope to provide insights into how AI-generated reviews are shaping the shopping experience on Myntra.
By analyzing review data over time and using our proprietary Originality.ai AI-detection tool, we aim to:
We also aim to contribute to the broader conversation on the ethical use of AI in e-commerce and the need for clearer guidelines to ensure that consumers can distinguish between authentic and machine-generated feedback.
In comparison with other shopping platforms, Myntra and Walmart appear to be monitoring AI in reviews, even while it's rising in others, like Flipkart.
This is particularly interesting to note, as Walmart acquired Flipkart in 2018, following Flipkart’s acquisition of Myntra in 2014.
Let’s dive a little deeper into the rate of AI content year on year to track the volume of AI content on Myntra from 2018 up to 2024.
The analysis of reviews on the Myntra shopping app reveals a clear upward trend in the prevalence of AI-generated content during that time, but not one that has become high overall — indicating that Myntra may be taking steps to moderate AI content.
Let’s take a closer look:
In 2018, the rate of AI-generated reviews was relatively low, at approximately 0.86%.
Over the following years, the rates fluctuated slightly but remained modest, with 0.55% in 2019, 0.79% in 2020, 0.61% in 2021, and 0.65% in 2022.
These small variations suggest that AI-generated content remained a minor component of the overall review landscape during the earlier years of the study period.
However, a notable increase began in 2023. That year, the rate of AI-generated reviews rose to 2.56%, indicating a significant shift compared to prior years.
This trend accelerated further in 2024, with AI-generated reviews making up 5.98% of all reviews analyzed.
This growth suggests a potential broader adoption of AI technologies for content creation by users, sellers, or automated systems supporting the platform.
Looking across the entire study period, that represents a 597% increase over the six-year period. Yet, overall AI content levels in Myntra reviews remained low.
The key takeaway for Myntra? While the rate of AI reviews on Myntra is rising, the majority of reviews as of 2024 are still human-written.
A note on false positives: False positives in AI detection occur when human-written content is identified as AI. False positive rates can vary by AI detection model and company. At Originality.ai our Lite model has an under 1% false positive rate, and our Turbo model has an under 3% false positive rate. So, the rates of AI content in Myntra reviews in this study are in-line with or slightly above AI detection false positive rates.
After looking at the percentage of AI reviews on Myntra across recent years, the results are a pleasant surprise.
While our findings and research on Myntra indicate that AI review content is rising (by over 597% during the period studied, 2018 to 2024), just over 94% of the reviews in 2024 are still human-written.
This is further emphasized in a comparison with other shopping apps.
According to our research:
In 2024, Likely AI reviews sat at just 5.98% for Myntra, which is lower than our findings for Flipkart and Walmart.
In comparison, our Flipkart Study found that in 2024, 19.83% of reviews were Likely AI, emphasizing a notable increase in AI content.
Then, our Walmart Study found that although in 2024, 7.75% of reviews were Likely AI, there was a stall in the growth of AI content in Walmart reviews from 2023 to 2024 (when levels hovered around 7.8%) after surging by 80.8% from 2019 to 2023.
Aside from being shopping apps, Myntra, Flipkart, and Walmart are connected by acquisitions.
According to Crunchbase, Myntra was founded in 2007 and was then acquired by Flipkart in 2014 for $300 million.
Just a few years later, in 2018, Crunchbase notes that Flipkart was acquired by Walmart for $16 billion.
In the context of our study, this indicates that some shopping platforms appear to be monitoring AI usage (such as Myntra and Walmart) — even while it's rising in others (Flipkart).
Further, AI moderation decisions may be conducted on a platform-by-platform basis even when the companies are connected via acquisitions (in this case, by Walmart’s acquisition of Flipkart and Flipkart’s previous acquisition of Myntra).
This study demonstrates that while AI-generated reviews are becoming an increasingly visible component of the Myntra shopping app experience, as of 2024, 5.98% of Myntra reviews are likely AI, meaning that just over 94% of reviews are human-written.
Whilst the platform has experienced a rise in AI reviews from 2018 (especially since the launch of ChatGPT in 2022), the overall percentage remains low, showing that Myntra is still prioritizing the importance of genuine customer reviews as a signal of trust and authenticity.
However, Myntra will need to ensure it remains on top of generative AI reviews, especially as the tools continue to improve and become more mainstream.
The rise from 2018 to 2024 suggests that Myntra must begin to seriously consider policies and detection mechanisms for AI-generated content to ensure that this figure remains low and customer trust remains high.
To help with this, Myntra should offer transparency about review origins, add clear labels, and incorporate AI detection tools to moderate content.
In conclusion, this study into Myntra AI reviews shows that although the percentage of AI reviews has risen in recent years, the brand also shows signs that it is managing to handle the volume of AI-generated content.
As we have touched on before, the importance of real user reviews and authentic experiences could not be more important in the era of AI. Not only is it a positive sign that the levels of AI content remain low at Myntra, but it is also rapidly becoming a competitive edge.
For brands that are seeking ways to tackle and identify AI reviews, moderation tools such as the Originality.ai AI Checker can help maintain transparency.
To maintain authenticity with users and clients, businesses must consider:
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 on online platforms:
This study systematically analyzed the prevalence of AI-generated reviews on the Myntra shopping app. The dataset, in CSV format, included review text, date, ID, score, and user interactions.
Initially, Unix timestamp data in the 'at' column was converted to a readable datetime format using Python's pandas library for time-based analysis. The processed data was saved separately for consistency.
To detect AI-generated reviews, a custom Python script used the Originality.ai API to scan reviews with at least 50 words, returning an AI-likelihood score and a binary AI classification. Reviews that were too short or encountered API issues were excluded. Retry mechanisms and periodic saving ensured reliability during the scan.
After scanning, results were aggregated yearly to measure trends in AI-generated content. Only successfully scanned reviews with valid dates were analyzed. Visualizations, including line and pie charts, were created to highlight trends and the 2024 AI vs. human-generated review distribution.
This methodology ensured accurate, reproducible results through robust preprocessing, external AI detection, and careful data management.
We tested Originality.ai using the same dataset and methods of the “ESPERANTO: Evaluating Synthesized Phrases to Enhance Robustness in AI Detection for Text Origination" study accessible via Cornell University. Here's how it stands out as a leader in the domain.
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