• Written by Muhammed Abdulla NC, CEO

One common objection to the adoption of AI in e-commerce and retail is that it will replace human workers, particularly in roles that involve manual labour or physical work. However, this objection is misplaced, as AI has actually landed mostly in the functions whose output is text, not the ones that handle physical work. According to the US Census Bureau's Business Trends and Outlook Survey, 12.6% of US retailers reported using AI in the previous two weeks, and this is largely in areas such as sales and marketing, where text-based outputs are more prevalent.

Where AI has actually landed in e-commerce and retail so far

AI has been most effective in e-commerce and retail in areas such as customer service, where chatbots can provide automated responses to customer inquiries, and in sales and marketing, where AI can help analyze customer data and provide personalized recommendations. This is because these areas involve a high volume of text-based data, which is well-suited to AI's strengths in natural language processing. In contrast, areas such as warehouse management and logistics, which involve more physical work, have been slower to adopt AI.

For example, a category manager can use AI to analyze sales data and customer feedback to inform decisions about product assortment and pricing. This can help the category manager to make more informed decisions, and to respond more quickly to changes in the market. As noted by the US Census Bureau's Business Trends and Outlook Survey, 14.3% of US businesses used AI in sales and marketing in the previous six months, which is a significant proportion of all AI adoption.

Assortment decisions

One area where AI has had a significant impact in e-commerce and retail is in assortment decisions. When the people dealing with assortment can ask the data in the order management system, product information management, WMS and marketing platforms a direct question, instead of waiting for a report, they can make more informed decisions about which products to stock and how to price them. This can help to improve profitability and reduce waste.

For instance, a buyer can use AI to analyze sales data and customer feedback to identify which products are most popular, and to inform decisions about which products to stock and how to price them. This can help the buyer to make more informed decisions, and to respond more quickly to changes in the market. To learn more about how AI can support sales teams, visit our sales teams page.

Returns and their root causes

Another area where AI has had a significant impact in e-commerce and retail is in returns and their root causes. When a customer returns a product, it can be difficult to identify the root cause of the return, and to make changes to prevent similar returns in the future. AI can help to analyze data from multiple systems, such as the order management system and the customer service platform, to identify the root cause of returns and to inform decisions about how to prevent them.

For example, a customer service representative can use AI to analyze data from the order management system and the customer service platform to identify the root cause of a return, and to inform decisions about how to respond to the customer and prevent similar returns in the future. This can help to improve customer satisfaction and reduce waste.

Promotion effectiveness

Promotion effectiveness is another area where AI has been touted as a solution, but it is harder than it looks. To effectively measure promotion effectiveness, a business needs to have a clear understanding of its goals and objectives, and to have the right data and systems in place to support analysis. AI can help to analyze data from multiple systems, such as the marketing platform and the sales platform, to identify which promotions are most effective and to inform decisions about how to optimize them.

However, this requires a significant amount of data and analytical capability, and it can be difficult to get right. For instance, a business may need to have data on sales, customer feedback, and marketing spend, as well as the ability to analyze this data and identify patterns and trends. To learn more about how AI can support IT investment in e-commerce, visit our blog.

Why most adopters have not changed anything underneath

Despite the potential benefits of AI in e-commerce and retail, many businesses have not changed anything underneath to support its adoption. According to the US Census Bureau's Business Trends and Outlook Survey, 64.3% of US businesses that have adopted AI made no change of any kind to adopt it, and only 6.8% changed how they collect or manage data. This can limit the benefits of AI, as it is only as good as the data and systems that support it.

For example, a business may adopt AI to analyze customer data, but if the data is not accurate or up-to-date, the insights provided by the AI will not be reliable. To get the most out of AI, businesses need to be willing to make changes to their underlying systems and processes, such as investing in data quality and analytics capability. To get in touch with us and learn more about how we can support your business, visit our contact page.

What a sensible first quarter looks like for a e-commerce and retail business

A sensible first quarter for a e-commerce and retail business that is adopting AI might involve focusing on one question, one system, and one team. For instance, a business might focus on using AI to analyze sales data from the order management system, and to inform decisions about product assortment and pricing. This can help to build momentum and to demonstrate the value of AI, while also minimizing the risk of disruption to the business.

By starting small and focusing on a specific area of the business, a e-commerce and retail business can begin to realize the benefits of AI, while also building the capabilities and expertise needed to support its adoption. As noted by the US Census Bureau's Business Trends and Outlook Survey, 22.4% of US businesses reported using AI in the two weeks to July 2026, which is a significant proportion of all businesses, and this number is likely to grow as more businesses begin to adopt AI.

What this does not do, or when it is the wrong choice

While AI has the potential to bring significant benefits to e-commerce and retail businesses, it is not a solution to every problem. In some cases, the costs and complexity of implementing AI may outweigh the benefits, or the business may not have the right data and systems in place to support its adoption. In these cases, it may be better to focus on other areas of the business, such as improving operational efficiency or enhancing the customer experience.

For example, a small business with limited resources and a simple product offering may not need to adopt AI to analyze sales data, as the benefits may not be significant enough to justify the costs. In this case, the business may be better off focusing on other areas, such as improving customer service or optimizing its supply chain. By understanding the limitations of AI and when it is the wrong choice, businesses can make more informed decisions about how to invest their time and resources.