AI is speeding up content creation like never before, with 46% of marketers using it to create engaging copies. Earlier, people relied only on tools like ChatGPT, Grammarly, and Gemini for automated content creation, but now platforms like Shopify, Amazon, and eBay have also developed AI-generative solutions to help sellers create engaging product descriptions at scale.
With artificial intelligence making a huge transformation in eCommerce, we are no longer asking: “Who writes better content—AI or humans?” Instead, now the more pressing question is, “Can AI alone be enough for creating product descriptions that stand out and drive sales?” Let’s try to find the answer to this question through this blog.
Why businesses are shifting towards generative AI for product description writing
According to McKinsey Analysis, generative AI can boost operating profits in the apparel, fashion, and luxury industries by as much as $275 billion within three to four years. This makes us question why eCommerce businesses are increasingly adopting AI for tasks such as content creation.
Some of the key driving forces behind it could be:
1. Efficiency and scalability
For businesses managing thousands of SKUs, creating detailed product descriptions quickly can be a monumental task. eCommerce brands often struggle to keep up with content demands, particularly when introducing new products or expanding their offerings. Generative AI tools like Copy.Ai and ChatGPT can solve this problem by generating product descriptions at scale, saving 60-70% of the time typically required for manual writing. Just provide key details about the product and a few prompts, and AI tools will expand on that to provide detailed descriptions that showcase the unique features and USPs of products.
Just provide key details about the product and a few careful prompts, and AI tools will expand on that to provide detailed descriptions that showcase the unique features and USPs of products.
2. Cost-effectiveness
Platforms like Upwork, Quora, and Reddit suggest that copywriters or freelancers usually charge between $20-$30 for creating a single product description, depending upon its complexity. This is still workable when you have fewer SKUs, but it can be extremely expensive for thousands of products if you hire a professional writer. AI tools can be cost-effective in such scenarios with just a small subscription fee (depending on the features), saving you money by automating this process with generative AI.
3. Uniformity in tone
AI tools excel in maintaining consistent structure and tone across thousands of product descriptions, which is challenging with a manual approach. When multiple writers are involved in the process, the variations in tone, writing style, and formatting are undeniable. These inconsistencies can make the product listings appear disjointed or unprofessional, harming your brand’s image. AI-generated product descriptions ensure that every listing aligns perfectly with your brand voice, whether you’re managing a few products or an entire catalogue.
Is generative AI worth the hype?
We know that AI excels at creating content at scale, but what about the quality? Can we say that product descriptions created by automated tools are much more impressive and engaging than those written by humans? Let’s see what people have to say about it.
This survey by Foundation highlights that 63% of participants believe that human-powered product descriptions are better than AI copywriting, while only 11% think the opposite.
Let’s take a look at the perceived shortcomings of utilising AI for eCommerce content creation:
1. Personal touch is missing
Generative AI tools are great at mimicking existing writing styles or tones based on their training data but struggle to incorporate a personal touch or fresh ideas. Creativity, critical thinking, and an authentic writing style are crucial to building a strong brand voice, and human copywriters are still irreplaceable in that context. AI may get the job done, but it’s that personal flair that often turns a product description into a compelling reason to buy.
For example, when describing a handmade leather bag, a human copywriter can highlight the craftsmanship, the unique texture, or the personal care involved in its creation. AI, on the other hand, may produce a generic description that lacks these subtleties, obfuscating the product’s true value and, therefore, underselling it to potential buyers.
2. The possibility of AI generalisation
The web is overloaded with AI content. Thousands of brands in the same niche are using AI to write product descriptions with similar information. In such scenarios, how would these tools be able to produce something that is not generic and repetitive? Would over-reliance on such content lead brands anywhere? Will they be able to resonate with their target audience and offer them something authentic and fresh to read and relate to?
3. Does not always grasp context
While AI tools are making great advancements, their contextual understanding is still limited. Until you provide reference pointers or relevant context in instructions related to the product’s specifications, the description it will generate can be long and generic, with lots of irrelevant information, sounding more like a blog than a listing. The below screenshot is a great example of this.
Instead of highlighting the specific features of the product, the description covers the normal details related to the flying reptile “Haztego Pterosaur.” Such descriptions can easily disappoint customers, as they won’t find actual information related to the product’s unique selling points, usage instructions, or other important information that can influence their buying decisions.
4. Not always spot-on with keyword optimisation
AI tools excel in keyword research and providing suggestions, but they often fall short when it comes to nuanced optimisation. While these tools might insert keywords in product descriptions and bullet points, the flow and relevance can feel forced, detracting from the user experience. Also, when uploading listings on marketplaces like Amazon, you have to be mindful of negative keywords. Amazon has strict guidelines around negative keywords—that is, certain words or phrases that, if included in your product descriptions, can lead to your listings being flagged or even banned. This makes it crucial to manually review AI-generated product descriptions to ensure these negative keywords aren’t mistakenly used, protecting your listings from potential penalties.
5. Depends on well-written prompts for accuracy
Artificial intelligence and machine learning algorithms work on the “Garbage In, Garbage Out” principle. It means that if the prompts entered by human copywriters are not up to the mark, the results generated by generative AI can be inaccurate or vague. And when such inaccurate product descriptions get uploaded on the web without human supervision, something like this happens:
6. Domain expertise is still not AI’s forte
AI-generated product descriptions may sound human-like, but without in-depth subject matter expertise, they struggle to capture the intricacies that make product descriptions resonate. For instance, if you are selling a high-end DSLR camera, AI might generate a product description like this for that product:
“This camera takes great pictures and is easy to use, making it perfect for beginners and professionals alike.”
While it sounds competent, it completely misses the mark for your target audience—serious photographers who are more interested in detailed features like the “24.1 MP APS-C CMOS sensor,” “DIGIC 8 image processor,” or “dual-pixel autofocus system.” These specifics are what professionals look for and can make the difference between a sale and a missed opportunity. However, without a deep understanding of photography or camera technology, AI may struggle to incorporate these details accurately or in the most persuasive way, as it operates on a one-size-fits-all approach.
Balanced approach: Let AI produce content at scale while you add a creative spark
Both AI and human content creation have their limitations and strengths, so it’s not about choosing one over the other. The efficient solution is to utilise the capabilities of both through human-AI collaboration in eCommerce content creation. Generative AI tools can be utilised to create product descriptions at scale, with human experts providing detailed instructions—adding context, specifications, and that all-important brand voice. Additionally, the AI-generated product description can be further fine-tuned or edited by subject matter experts to add relevant details that AI might have missed, ensuring both creativity and uniqueness in the outcome. This way, product listings can not only be created in a short amount of time but also have their authentic brand tone, relevant context, and specifications required for converting browsers into buyers.
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