Latest trends in using artificial intelligence in e-commerce in 2025

No one can deny the developments that artificial intelligence technologies and machine learning applications have brought about in various fields, especially in the field of e-commerce. According to the latest reports issued by McKinsey & Company, which discussed the uses of AI tools in developing markets such as Arab countries, the Middle East, and North Africa:

• 9% of people usually use these tools for work-related purposes,

• while 11% use them for work and normal daily life,

• while approximately 20% rely on them completely in their daily lives, shopping, and purchasing.

• The report also mentioned that 34% of people have used AI tools at least once to help complete a specific task.

All these statistics prove the power and importance of AI tools and that they are an influential and effective factor contributing to the success of various commercial activities.

Let us review the various uses of artificial intelligence in the field of e-commerce in 2025, and how to take advantage of them for your store.

8 of the latest trends in using artificial intelligence in e-commerce in 2025

Before talking about the modern trends of artificial intelligence and machine learning in the field of e-commerce, it is necessary to review this important indicator from the McKinsey report, which stated that:

• 7% of retailers rely on various AI tools to complete different work tasks,

• while 11% use them in parallel in work and daily life,

• while 40% have used these tools at least once for multiple purposes.

Based on this important statistic, which confirms the importance of relying on artificial intelligence, we will talk about the most prominent trends.

First: Recommendation systems to help personalize the customer shopping experience

Recommendation systems or Recommendation Engines are advanced systems built on artificial intelligence technologies and machine learning applications that work to collect, process, and filter data according to machine learning algorithms that provide predictions of the products and services shoppers are looking for, and then display them to them while browsing e-commerce sites based on their previous purchasing journeys.

Most recommendation systems use two types of data filtering processes or a combination of both:

• The first type is known as Collaborative Filtering: In this, the AI-based recommendation system creates recommendations by comparing the behavior of some customers with others who have similar preferences.

• The second type is called Content-Based Filtering: In this, the recommendation engine provides recommendations based on a specific customer's data, such as previous purchases or searches.

All of this contributes effectively to improving and personalizing the shopping experience for customers according to their needs and preferences, which contributes to their enjoyment during their purchasing journeys and enhances sales on your online store.

The best user of recommendation engines is Amazon, which offers more than 5 different recommendations as soon as you place a product in your shopping cart.

Here are some tips you can use to exploit the capabilities of recommendation systems for your business:

• Utilize AI-based recommendation systems to display related products based on customer interests and purchasing behavior. For example, if a customer buys a shoe, you can recommend other products such as socks or related accessories.

• Use recommendation systems to guide customers to the right products for them while browsing your online store, for example, you can display a list of (other customers also bought) or (best-selling products) to encourage exploration and increase purchase opportunities.

• Rely on advanced technologies such as Clustering and Deep Learning to improve the accuracy of recommendation engines and enhance the customer shopping and purchasing experience.

Second: Chatbots

They are an interactive interface that allows users to communicate with the business for the purpose of assistance in solving a problem or obtaining information about the products or services provided.

Chatbots rely on advanced technology in machine learning and natural language processing to achieve interactive and smart responses to inquiries and requests from users, which makes them useful for online stores in many matters, including:

• Improving the shopping experience for consumers by providing the necessary assistance and guidance to complete the purchase efficiently.

• Helping to speed up customers' purchasing decisions by obtaining immediate and comprehensive answers to their inquiries about products, thereby increasing sales.

• Saving costs related to hiring a large number of customer service representatives to answer inquiries and questions and provide necessary support to shoppers.

One of the most prominent examples of the effectiveness of chatbots for online stores is Sephora's Virtual Artist, which allows customers to virtually try different makeup products, providing a personalized and interactive shopping experience.

Sephora's Virtual Artist analyzes customer preferences and facial features, then provides product recommendations, as well as immediate assistance with selected products. For example, this chatbot can enable shoppers to try a variety of makeup products without having to go to a physical store, then see how they would look on their faces, and provide instructions on how to use them correctly.

It can also provide recommendations for suitable products based on customer preferences and facial features. For example, if a customer states that they have dry skin, it immediately advises them to purchase moisturizing makeup products. All of this contributed to boosting sales for the Sephora brand and giving it a competitive advantage.

Third: Visual search engines and voice search:

Not everyone is good at expressing what they want through writing, so visual search engines based on artificial intelligence technologies, as well as voice search, are among the latest emerging uses in e-commerce.

Visual search engines that can be integrated into e-commerce websites rely on image recognition technologies according to complex algorithms to enable users to search for products using images. For example, a shopper can take a picture of a product they like and use it as an input for the search, and then the engine analyzes the image and provides results related to similar products or available offers.

While voice search allows users to conduct searches and shopping using voice commands, relying on natural language processing technologies and converting sound to text to understand and execute the shopper's request. For example, consumers can ask about a specific product, request recommendations for products, or request to make purchases based on voice commands.

You can make the most of these technologies for your store, attract different segments of the audience, and improve the shopping experience, making it more enjoyable and easy by using these tips:

• Focus on improving the quality of images used in your store so that they are displayed from multiple angles, thereby helping visual search engines to better recognize products and present them to users with similar interests.

• Use a clear and comprehensive description of your products and use appropriate keywords to help increase the chances of your products appearing in relevant search results.

• Be keen on developing your store to provide a distinguished user experience by integrating visual search engines and voice search to make the process smooth for shoppers to search for products and make purchases using images or voice commands.

Fourth: Predictive analytics for inventory management:

The same study conducted by McKinsey & Company mentioned that commercial activities that invest in artificial intelligence technologies and machine learning applications can achieve demand forecasting accuracy of up to about 90% compared to only 60% for traditional demand forecasting.

Effective inventory management is crucial in the field of e-commerce, so artificial intelligence in 2024 will play a pivotal role in improving this process and making it more efficient and effective by relying on AI-powered predictive analytics to help retailers forecast demand with high accuracy, reduce overstocking and stockouts, and improve supply chain efficiency, which will contribute to saving costs for stores and improving the shopping experiences for customers. To keep pace with this great development, it is necessary to:

• Focus on investing in artificial intelligence and machine learning technologies and building predictive models to analyze data and predict future consumer demand for products.

• Develop a clear inventory management strategy based on artificial intelligence according to the different factors that affect supply and demand.

• Seek external resources to develop machine learning models to maximize their benefit for the business activity.

Fifth: Fraud detection and risk reduction:

E-commerce websites are always vulnerable to fraud, but with the application of advanced artificial intelligence technologies, such operations can be detected and their danger reduced. How is that?

Advanced machine learning algorithms work to analyze transaction data in real time to identify and block fraudulent activities, by analyzing a variety of factors, including:

• Customer data: such as IP address, email address, date of birth, and credit card data.

• Financial transaction data: represented by transaction value, product type, payment method, and time of purchase.

• Location data: which is represented by the customer's location and the devices used for browsing.

Based on these factors, algorithms can identify abnormal patterns that may indicate fraudulent operations such as:

• Using a stolen credit card.

• Making a large purchase by a new customer.

• Making a purchase from an unfamiliar location.

This not only protects companies from financial losses, but also contributes to strengthening customer trust in the store and thus eliminating the fear of making purchases. Here are some expert tips for fully benefiting from these technologies and reassuring customers to shop and purchase from your store:

• Train AI algorithms on customized data from your store to help improve analysis accuracy and detect more fraudulent operations.

• Review fraud rules and controls periodically, and be keen to review modern fraud methods to develop the technologies used.

• Provide transparent reports to customers about the fraudulent operations that have been discovered to help build trust with them, reassure them, and enhance their loyalty to the brand.

Sixth: Supply chain automation:

Artificial intelligence technologies play a pivotal role in improving operational efficiency in supply chains and reducing costs. This technology relies on machine learning algorithms and predictive analytics to monitor the flow of goods and manage inventory accurately, which helps companies make quick decisions based on real-time data. For example, AI systems can predict demand for products based on seasonal purchase patterns and customer behavior, allowing companies to optimize storage operations and avoid stockouts or overstocking. These systems also help improve supplier management by providing recommendations based on previous performance and quality, which enhances the efficiency of supply operations and reduces potential risks. In addition to improving planning, supply chain automation contributes to enhancing the customer experience by reducing delivery times through automating operational processes within warehouses and ensuring the availability of required products in stock, as well as tracking shipments in real-time, which allows companies to predict any potential delays and inform customers in advance, which increases the level of transparency and reliability.

To achieve the maximum benefit from supply chain automation in e-commerce, a set of strategies and technologies must be followed that ensure seamless integration and high efficiency in logistics operations, such as:

• Investing in advanced AI systems capable of analyzing big data and using predictive analytics to forecast demand and manage inventory efficiently, which allows for reducing waste, improving resource utilization, and avoiding problems associated with stockouts or overstocking.

• Relying on the Internet of Things (IoT) to enhance process transparency, as smart sensors and tracking devices allow knowing the location of shipments and the status of products in real-time, which contributes to making more accurate and faster decisions.

• Connecting automation systems with other supply chain management solutions, such as Enterprise Resource Planning (ERP) systems and Order Management Systems (OMS), to ensure a smooth flow of information between all departments of the company.

• Employing robots and automated systems in warehouses and distribution centers, as these technologies contribute to improving the speed of order processing and reducing human errors, which enhances the customer experience and increases the efficiency of logistics operations.

Seventh: Improving online payment processes:

This aspect is witnessing great development thanks to artificial intelligence technologies, as payment systems have become safer, faster, and more flexible to meet the needs of consumers and retailers alike, thereby contributing to enhancing the efficiency of payment processes, increasing conversion rates, and improving the user experience.

Modern payment systems in e-commerce rely on smart algorithms that analyze the behavioral and financial data of users, which allows for offering customized payment options according to purchasing patterns and customer preferences. For example, AI systems can predict the most suitable methods for the consumer based on their previous transactions, which reduces the time spent entering payment data and limits cart abandonment rates. Deep learning technologies are also used to develop more flexible payment mechanisms, such as one-click payment or automatic pre-payment, which contributes to facilitating the completion of financial transactions quickly and efficiently. Artificial intelligence has also contributed to developing dynamic payment solutions capable of adapting to customer needs, such as smart installment payment systems, which rely on analyzing users' creditworthiness in real-time. Also, the integration between payment systems and smart assistants, such as voice assistants and Natural Language Processing (NLP) technologies, has become a key factor in simplifying payment processes, as users can make purchases and execute payments via voice commands without having to navigate through traditional payment pages.

You can use these tips to benefit from artificial intelligence technologies in developing your payment systems:

• Use AI algorithms to analyze customer payment patterns and suggest customized payment methods for each user, which contributes to reducing friction during the purchase process and increasing transaction completion rates.

• Apply machine learning techniques to monitor customer behavior during purchases, and provide immediate recommendations such as automatic pre-payment or one-click payment, which contributes to accelerating the payment process and improving the user experience.

• Invest in voice assistant technologies and Natural Language Processing (NLP) technologies to enable users to complete payments using voice commands or text messaging, which makes the payment process easier and smoother.

• Rely on advanced data analytics to improve the flow of financial operations, such as providing instant notifications about payment status and retry notifications when transactions fail, which enhances the user experience.

• Employ deep learning technologies to speed up payment processing operations and reduce response time, which allows users to complete payments in the shortest possible time without delay.

• Make sure to seamlessly integrate AI-based payment systems with your e-commerce platforms, so that they provide a smooth and consistent experience for users without the need to exit the platform to complete the payment.

Eighth: Order orchestration and fulfillment optimization:

In light of the complexity of supply chains and increasing customer expectations regarding the speed and efficiency of delivery, order orchestration and fulfillment optimization has become one of the latest trends in the use of artificial intelligence in e-commerce. This trend relies on smart algorithms and big data analytics to align order fulfillment processes based on a set of factors, such as inventory availability, proximity of delivery location, shipping costs, and customer preferences, which helps in providing more efficient and flexible solutions.

AI systems use predictive analytics and machine learning to select the best distribution centers or warehouses to fulfill the order based on the customer's geographical location and inventory level, which reduces delivery times and logistical costs. These systems also help dynamically re-route orders, so that products are sent from the closest available location when unexpected changes occur, such as stock depletion or shipping delays, in addition to using them to optimize shipping routes and prioritize deliveries, which allows companies to achieve higher operational efficiency, reduce carbon emissions, and enhance environmental sustainability by choosing more environmentally friendly shipping methods.

Order orchestration and fulfillment optimization using artificial intelligence requires working on several strategic and technical aspects to ensure maximum efficiency and flexibility, including:

• Connecting AI systems with Enterprise Resource Planning, order management, and inventory systems to ensure smooth data flow, which enables AI to make accurate decisions regarding determining optimal fulfillment locations and re-routing orders when necessary.

• Analyzing data and improving demand forecasting, as you need to develop big data analysis algorithms to understand seasonal demand patterns and changes in customer behavior, which helps predict required inventory levels and plan fulfillment processes more accurately.

• Improving distribution networks and increasing supply chain flexibility, as it is necessary to strengthen the logistics infrastructure by increasing the number of smart distribution centers and utilizing warehouses close to target markets, which allows for reducing delivery times and improving shipping efficiency.

• Employing smart routing and machine learning technologies, as you need to use smart routing algorithms that take into account distances, costs, traffic congestion, and customer requirements to determine the best delivery routes, which helps reduce costs and increase fulfillment speed.

So, how can the full potential of artificial intelligence be utilized to increase sales?

According to the latest reports, the most common uses of artificial intelligence tools revolve around marketing and sales at an estimated rate of 13%, as well as product and service development at 14%, which demonstrates the power of these tools and the importance of using their capabilities to boost sales and increase profits. Given the lack of scope to detail this matter, we have collected some tips that may help you:

• 33% of retailers rely on AI tools for e-commerce to improve conversion rates, revenue, product marketing, and optimize offers, so you should link your advertising campaigns and offers to models based on machine learning to analyze data and extract valuable insights to benefit from them in developing more effective offers to encourage customers to make purchases.

• Use artificial intelligence capabilities to analyze the available data to understand trends and patterns and discover new opportunities in the market to boost sales.

• Create predictive models to identify potential customers interested in your products or services to personalize your marketing efforts and contribute to converting them, thereby increasing revenue.

• Improve the shopping experience on your store by providing personalized content and product recommendations compatible with their preferences.

• Benefit from artificial intelligence technologies to analyze data and determine dynamic pricing policies based on demand rates and market variables.

• Rely on smart chat systems supported by artificial intelligence to provide immediate and effective support to customers and help them complete purchases efficiently.

• Use artificial intelligence technology to improve your store's product pages by providing high-quality images and accurate descriptions that encourage shoppers to buy.

• Rely on smart systems to improve shipping processes and track orders to provide customers with accurate and immediate information about the status of their orders and ensure they are delivered as quickly as possible.

For example, you can rely on Oto, the leading shipping gateway in the Arab world, designed with the latest unique and innovative technologies to benefit from the capabilities of artificial intelligence and machine learning applications to automatically route shipments according to your own rules. By creating a free account on Oto, you will be able to improve the process of shipping, managing, tracking, and retrieving your orders, as well as analyzing them and connecting with more than 200 local and international shipping companies, thereby making a qualitative leap in your store and enhancing competitive value.

A final word:

In recent years, we have witnessed the emergence of many new trends in artificial intelligence in the field of e-commerce, which contributed to a major change in the way of online shopping.

We have also witnessed a remarkable development in the use of augmented reality and virtual reality to provide a more interactive and adventurous shopping experience. For example, customers can shop through voice commands, try products before buying them, and visit virtual stores without having to leave their homes.

With this enormous technological development, you should work to rearrange your papers to keep pace with these dynamic changes in pursuit of growth, sustainability, and achieving the maximum possible returns on investment.