It's 2026: Are You Still Typing Product Descriptions One by One? Where AI Helps Online Sellers

Online sellers no longer need to type product details SKU by SKU in 2026, because AI such as Claude or ChatGPT can write product descriptions, answer customer chats, analyse reviews, produce ad copy and translate listings in a few minutes per task. What you need is complete product data and prompts written the right way, not people typing item after item as before.

The UOB Business Outlook Study 2026 found that more than 70% of Thai SME owners already use AI in their business [1]. This is consistent with a study published in Science, which found that using ChatGPT for professional writing tasks cut working time by about 40% and raised the quality of the work by about 18% [2]. Stores that still type everything by hand are now clearly slower than competitors that have switched to AI.

How much can AI really help with product descriptions and images?

AI can write descriptions for all 100 SKUs in a single pass if you put the raw data (product name, material, size, selling points) into a spreadsheet and tell it to write every row from the same template. For product photos, AI can handle both white-background cutouts and lifestyle images generated from a plain product shot.

Research on generative AI in e-commerce reports that using AI to write product descriptions cuts the time it takes to list each new product by 60-70% compared with writing everything yourself [3]. For stores with tens to hundreds of SKUs, this is one of the biggest time savings available, because work that used to take a content team days is reduced to checking accuracy before posting.

How can AI answer repeat chats and read reviews to find why customers hesitate?

Repeat questions such as "How many days for delivery?", "What colours do you have?" and "Is it genuine?" can be loaded as a set of standard answers that AI replies with immediately. To read reviews for the reasons customers hesitate, collect all customer chat messages into one file and ask AI to summarise the questions or complaints that keep recurring.

The practical steps are to collect the last 1-3 months of customer chats into a CSV or text file, then tell the AI: "From this set of customer chats, group the 5 most frequent questions or concerns and give real example sentences for each group." The result tells you plainly whether customers hesitate over price, trustworthiness or delivery time, and you can use it to fix your product pages right away.

What else can AI do for marketing and back-office work?

Beyond front-of-store tasks, AI can handle marketing work and data summaries that repeat every week. That includes writing several versions of ad copy to test, translating product pages into English and Chinese for cross-border sales, summarising weekly sales and writing scripts for product review videos.

For ad copy, ask AI to write 15-20 versions from different angles (price, quality, reviews), then run them as parallel ad tests. For translation, don't translate word for word. Instead, ask AI to rewrite the page so it reads naturally for English or Chinese readers directly, because the search terms English and Chinese speakers actually type are not the same as literal translations from Thai. For the weekly sales report, export the sales file from your store system and ask AI to summarise it in a short text, pointing out where sales rose or fell unusually.

Can AI help analyse competitors and find keywords on Shopee/Lazada?

AI can help at the stage of summarising and analysing data you have already collected. For example, it can summarise how a competitor has changed prices or content from storefront screenshots saved over time, or group search terms from a keyword report exported from the platform so you can see which terms people search for most.

One point needs to be clear: a chat AI cannot go into a competitor's live Shopee or Lazada storefront and pull the data itself. That part needs a data-collection tool (a scraping tool or a report from the platform) first. You then give the raw data to AI to summarise the patterns and write recommendations. Splitting the work this way saves a lot of time on the analysis step, even though data collection still has to be done separately.

A real example from a Custocare client

[Pending: a Custocare case from the e-commerce / online store sector. No case with a name that can be disclosed was available when this article was written. We recommend adding it later, with a link to the full case study page.]

While waiting for a direct e-commerce case, the Custocare team ran an "AI Content Creator" training for the marketing staff of Pisona Group in Phuket, in May and June 2026, with 40 people per session. It focused on getting the team to write content with AI themselves instead of writing each piece by hand as before. This is the same skill set online stores use to write product descriptions and ad copy, as described in this article.

Frequently Asked Questions

Do I need technical knowledge before using AI to write product descriptions? No. A general-purpose AI chat is enough. Prepare your product data as a table (name, material, size, selling points) and tell the AI to write every row from the same template, and you get usable results straight away. You don't need to write code or use complicated tools.

Can AI answer customer chats 100% on its own? It works well only for repeat questions with fixed answers, such as delivery time or colours. For questions that need a case-by-case decision, such as price negotiation or damaged goods, a staff member should check before the real reply goes out.

Can I use AI to translate product pages and sell across borders right away? Yes, and it saves a lot of time, but a native speaker or someone familiar with that market should review it once more before publishing, especially for technical terms or units of measurement that differ between countries.

Is it safe to give AI customer data to analyse reviews? Remove personally identifiable information, such as phone numbers or addresses, before giving the chat file to AI to analyse, and choose an AI tool with a clear privacy policy.

Which task should I start with to see results fastest? We recommend starting with the task you repeat most often and that costs the most time. For most stores that is writing product descriptions and answering repeat chat questions, because the time saved is clear from the first week.

Author: Tanyalak Techapeompol Managing Director of Custocare, a consultancy for AI and Digital Transformation, with 17 years of IT experience Former CIO of Oasis Spa Group, running IT across 14 branches in 4 provinces · Speaker and guest lecturer on AI for Chiang Mai University and private-sector organisations Profile · LinkedIn

Published: 04/09/2026 | Last updated: 04/09/2026

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