AI and eCommerce: What the Future Holds [2025 & Beyond]

The eCommerce industry faces challenges like shifting consumer expectations, supply chain disruptions, and increasing fraud risks. AI offers solutions to address these complexities by driving efficiency, personalization, and predictive capabilities across operations. AI-powered product recommendation engines enhance customer satisfaction by analyzing behavioral data to meet evolving demands. Platforms like Spresso’s Pricing Intelligence optimize real-time pricing decisions based on SKU performance and market trends. AI-driven automation in customer service improves interactions by managing inquiries and improving response times.

Advanced inventory management systems leverage AI to forecast demand and mitigate supply chain uncertainties. Visual search tools, such as Renovai’s Renée virtual stylist, improve product discovery with personalized shopping experiences. From detecting fraudulent activities to refining marketing strategies, AI strengthens operational resilience. It enables businesses to adapt to shifting consumer behavior and logistical challenges. As AI and eCommerce become intertwined, stakeholders must embrace these innovations to thrive in a transforming marketplace.

Why should you read this report?

• Gain in-depth insights into the top 10 applications of AI in eCommerce
• Learn about practical use cases for each application, showcasing various AI in eCommerce examples
• Meet 10 innovative startups advancing these applications

Key Takeaways

1. Personalized Product Recommendations
   • Startup to Watch: Rep AI
2. Customer Service Automation
   • Startup to Watch: Octocom
3. Dynamic Pricing
   • Startup to Watch: Spresso
4. Inventory Management
   • Startup to Watch: storePredictor
5. Visual Search and Personalized Discovery
   • Startup to Watch: renovai
6. Supply Chain Optimization
   • Startup to Watch: DeepLogica
7. Fraud Detection and Prevention
   • Startup to Watch: Spotrisk
8. Customer Analytics
   • Startup to Watch: Commune
9. Marketing Optimization
   • Startup to Watch: Apollo
10. Returns and Refunds Management
    • Startup to Watch: Frate

Applications of AI and eCommerce FAQs

How is AI used in eCommerce?

AI improves personalization, operational efficiency, and customer engagement in eCommerce. It analyzes customer behavior and purchase history to suggest relevant products to increase satisfaction and sales. Chatbots and virtual assistants provide 24/7 support and handle routine queries, guide shoppers, and facilitate transactions. Dynamic pricing tools use AI to adjust prices based on supply, demand, competitor activity, and customer behavior to optimize profitability in real time.

AI also forecasts demand through historical sales data analysis and manages stock levels with automated replenishment systems. AI models monitor transactions to detect anomalies and prevent fraudulent activities. Smart logistics systems optimize shipping routes and reduce delivery times through predictive analytics to ensure efficient operations across the supply chain.

What is the future of generative AI in eCommerce?

Generative AI will change eCommerce by creating dynamic, personalized experiences. It generates unique product descriptions, marketing content, and images tailored to different audiences for automating content creation while maintaining brand consistency.

Future applications include virtual fitting rooms and guided selling tools to enable customers to visualize products and receive recommendations based on their preferences and body types. This will reduce returns and improve conversion rates. Businesses must address challenges like data privacy, bias in AI outputs, and regulatory compliance. Balancing AI automation with human oversight is essential to building customer trust and maintaining high-quality outputs.

Where is this Data from?

StartUs Insights provides data through its comprehensive Discovery Platform, which covers 4.7+ million startups, scaleups, and tech companies globally, as well as 20K+ emerging technologies & trends. The platform excels in startup and technology scouting, trend intelligence, and patent searches, offering a detailed view of the innovation landscape. For this report, we analyzed technologies within specific industries using the trend intelligence feature. During this research, we identified patterns and trends, pinpointing relevant use cases and the startups developing solutions for each. More capabilities and details are available at StartUs Insights Discovery Platform.

10 Top Applications of Artificial Intelligence in eCommerce [2025 & Beyond]

1. Personalized Product Recommendations

In e-commerce, AI enhances personalized product recommendations through various technologies. Collaborative filtering analyzes user interactions to identify patterns and suggest products based on similarities among users. Content-based filtering recommends products based on their attributes and a user’s past interactions. Meanwhile, contextual targeting considers the current browsing context for relevant suggestions, and behavioral targeting uses historical data to predict future actions.

These AI-driven approaches improve customer experience by making shopping intuitive, increasing conversion rates with suggestions, and fostering loyalty by understanding preferences. Further, they enhance average order values through strategic upselling and cross-selling that make AI-powered recommendation systems essential for eCommerce businesses to remain competitive.

Startup to Watch: Rep AI

US startup Rep AI develops an AI-powered concierge platform for eCommerce that offers personalized assistance to online shoppers through automated chat interactions. The platform integrates with Shopify and other tools to provide real-time support and sales engagement. It uses a proprietary Rescue Algorithm to detect when customers are likely to leave the site and initiates targeted conversations to guide users back to completing purchases.

This proactive engagement improves customer retention and drives higher conversion rates. The platform offers 24/7 customer assistance, automated product recommendations, and dynamic responses to FAQs to ensure smooth user experiences without overwhelming support teams. Rep AI enhances eCommerce sales by reducing cart abandonment, increasing average order value (AOV), and streamlining customer service.

2. Customer Service Automation

AI chatbots use natural language processing and machine learning to provide 24/7 support by handling routine inquiries and tasks like order processing. This automation reduces the workload on human agents and ensures prompt responses to meet rising customer expectations for immediate service. Voice-activated shopping assistants, like Amazon Alexa and Google Assistant, enhance the shopping experience by allowing customers to make purchases using voice commands. This offers convenience and speed, which enables hands-free shopping and increases engagement.

Further, multilingual support systems powered by AI are essential for global e-commerce to provide communication across different languages and ensure consistent service quality worldwide. These technologies improve customer satisfaction by delivering timely and personalized assistance while creating a more inclusive shopping environment. Also, AI applications in sentiment analysis and order tracking enhance customer service by providing insights into preferences and ensuring transparency throughout the purchasing process.

Startup to Watch: Octocom

UK startup Octocom provides an AI-powered customer support solution for e-commerce to automate inquiries across channels like email, social media, and web-based chats. It integrates with tools like Zendesk and Gorgias to ensure businesses manage customer interactions within familiar platforms. The AI handles routine tasks such as order tracking, returns, and product inquiries while escalating complex issues to human agents with contextual details for handoffs.

The startup offers multilingual support, aligns responses with each brand’s personality, and offers personalized product recommendations and upselling strategies to enhance the shopping experience. Octocom advances support processes and increases average order value, aiding businesses in operating efficiently, improving customer satisfaction, and reducing operational costs through automated, conversational service delivery.

3. Dynamic Pricing

AI is transforming dynamic pricing in eCommerce through real-time price optimization, personalized pricing, and price elasticity analysis. Real-time price optimization analyzes competitor pricing, market trends, and inventory levels to enable dynamic price adjustments to maximize revenue. Personalized pricing uses customer data to tailor pricing strategies to offer individualized discounts that enhance satisfaction and improve conversion rates.

Moreover, AI-driven price elasticity analysis allows businesses to understand how price changes affect demand and optimize pricing models that balance sales volume and profit margins. This approach ensures e-commerce platforms remain competitive, responsive to consumer needs, and profitable in a fluctuating market.

Startup to Watch: Spresso

US startup Spresso builds Pricing Intelligence, an AI-powered platform that optimizes pricing decisions by analyzing first-party SKU performance in real-time. The platform uses dynamic price optimization techniques, which employ a multi-armed bandit algorithm to identify effective price points continuously. This allows businesses to maximize profitability while maintaining competitive conversion rates and adjust prices based on market trends and customer behavior.

Its features include real-time SKU-level insights, promotion management, and integration with eCommerce systems like Shopify and BigCommerce. Spresso’s solution offers a fast return on investment by automating price setting and enabling merchants to balance margins and sales growth.

4. Inventory Management

Predictive demand forecasting uses machine learning to analyze historical sales data, market trends, and external factors to predict future product demand. This allows businesses to optimize stock levels, which reduces overstocking or stockouts and ensures product availability. Automated reordering systems use AI to set reorder triggers based on demand forecasts and inventory policies for streamlining replenishment and minimizing manual intervention.

Further, AI-powered simulations for warehouses determine the most efficient layout for storing items to minimize retrieval times and reduce labor costs. This enhances picking accuracy and speeds up order fulfillment. In addition, real-time inventory tracking and automated inventory categorization improve decision-making and operational performance by providing accurate insights into stock levels and optimizing inventory management across locations.

Startup to Watch: storePredictor

Slovakian startup storePredictor develops an AI-powered inventory management solution that optimizes stock levels through predictive analytics. It leverages historical sales data, seasonal trends, and real-time demand patterns to forecast inventory needs. This reduces overstock and prevents stockouts to ensure efficient supply chain management. The startup’s system includes automated replenishment alerts and dynamic demand modeling. It integrates with popular eCommerce platforms to enable real-time data synchronization for accurate tracking of product availability and sales trends. storePredictor enables businesses to streamline inventory management, minimize waste, and improve profitability.

5. Visual Search and Personalized Discovery

Leveraging AI in e-commerce improves product discovery, increases conversion rates, and integrates online and offline shopping. Image recognition allows users to find products by uploading or snapping a photo to bypass text-based searches. It uses computer vision and deep learning to analyze shape, color, and texture, provides matches, and makes shopping more intuitive and efficient. AI-powered AR lets customers virtually place items in their environment, like furniture in a living room to offer a realistic preview to aid purchasing decisions. Moreover, virtual fitting rooms and showrooms let users try on clothes or visualize products in a digital space to reduce returns and increase satisfaction.

Startup to Watch: renovai

Israeli startup renovai builds Renée, an AI-powered virtual stylist that enhances product discovery and delivers personalized shopping experiences. The startup’s correlated deep tagging technology provides precise search results by contextualizing product attributes to improve discovery accuracy and reduce irrelevant choices. The platform uses algorithms and computer vision to align products with users’ tastes, considering style, material, color, and spatial context.

Through real-time recommendations and interactive Q&A sessions, Renée enables shoppers to find items suited to their preferences and ensures compatibility with existing room designs. renovai also supports complementary item matching to suggest curated combinations that complete looks or enhance interior designs.

6. Supply Chain Optimization

For delivery route optimization, AI algorithms analyze real-time data, such as traffic patterns, weather conditions, and delivery windows, to determine efficient routes. This reduces transportation costs, improves delivery times, and minimizes environmental impact by optimizing fuel consumption and reducing emissions. AI is used in logistics planning to forecast demand and potential disruptions by analyzing historical data and external factors.

This allows businesses to adjust logistics strategies proactively to ensure resilience against challenges and maintain optimal inventory levels. Further, AI assesses data points such as delivery times, product quality, and pricing trends to evaluate supplier reliability. This lets businesses make informed decisions about supplier relationships and mitigate risks associated with supply chain disruptions. AI also enhances supply chain visibility through real-time tracking of goods and predictive maintenance of equipment to streamline operations and improve efficiency.

Startup to Watch: DeepLogica

US startup DeepLogica offers AI-driven solutions to enhance e-commerce delivery accuracy and efficiency. Its platform uses machine learning models to predict delivery dates by analyzing logistics data and external factors like weather and carrier performance. These insights enable businesses to align customer expectations with real-world delivery timelines to address supply chain complexities. The startup’s technology supports real-time monitoring, proactive issue management, and network analytics. DeepLogica provides recommendations that allow businesses to make informed decisions on staffing, inventory placement, and distribution strategies for improved customer experience.

7. Fraud Detection and Prevention

AI’s capabilities in fraud detection enhance security measures and improve operational efficiency by reducing false positives and enabling proactive threat management. For instance, machine learning analyzes transaction data to identify deviations from normal patterns that suggest fraud. This real-time analysis enables businesses to detect and address potential threats, which reduces financial losses and protects customer data. AI also monitors user behavior for signs of unauthorized access attempts, such as unusual login locations or device changes.

By catching these anomalies early, AI systems prevent fraudsters from accessing user accounts, protecting personal information, and maintaining trust. Further, AI-driven bot detection systems examine web traffic to differentiate between legitimate users and malicious bots used for data scraping, fake account creation, and automated attacks. These systems use behavioral analytics and device fingerprinting to identify and block harmful bot activities without disrupting genuine user interactions.

Startup to Watch: Spotrisk

New Zealand startup Spotrisk offers a fraud prevention platform for e-commerce needs, including Ecommerce Risk, SaaS Risk, and Location Risk API products. These solutions use machine learning to detect fraudulent orders, assess buyer behavior, and block suspicious transactions in real-time. The Ecommerce Risk product safeguards online stores from chargebacks and fraudulent purchases by analyzing data points per transaction.

SaaS Risk ensures fraud detection throughout the funnel, from leads to users, while Location Risk API verifies buyer addresses and prevents delivery fraud using geolocation data. The startup offers features like real-time buyer verification and smart block to prevent account takeovers and payment fraud by allowing merchants to confirm identities or block high-risk buyers. Spotrisk automates fraud management and supports escalation services for businesses to protect revenue, maintain customer trust, and reduce operational friction.

8. Customer Analytics

AI-driven customer analytics lets e-commerce businesses make informed decisions, improve customer retention, and drive growth by understanding and anticipating customer needs. Behavioral segmentation analysis involves AI that categorizes customers based on actions and preferences. This allows them to tailor marketing strategies and improve engagement. This approach enables companies to create personalized experiences for specific customer segments to enhance satisfaction and loyalty.

Moreover, predictive customer lifetime value (CLV) modeling uses machine learning to forecast the long-term value of customers by analyzing purchasing behavior and engagement patterns. This enables businesses to allocate resources effectively and focus on high-value customers to maximize profitability. Also, churn prediction models use AI to identify customers at risk of leaving by analyzing behavioral indicators and engagement levels. By predicting churn early, businesses implement targeted retention strategies to maintain their customer base and protect revenue streams.

Startup to Watch: Commune

Singaporean startup Commune offers a product analytics platform that enables teams to use qualitative data like customer feedback for decision-making. The platform processes feedback by extracting recurring themes, assigning relevant tags, and conducting sentiment analysis, following the extract, transform, load (ETL) framework. This structured data is visualized using customizable dashboards, which allows product teams to explore key trends and generate insights.

Its AI-generated reports summarize user feedback into insights, including hypothetical user journeys and key behavioral patterns. The real-time analytics provide teams with dynamic dashboards for up-to-the-minute insights into customer sentiment. Its automated tagging feature categorizes incoming data from multiple sources to ensure teams manage and interpret their qualitative inputs. Commune integrates with tools like Slack, Zapier, and Teams to fit within existing workflows and ensure easy collaboration.

9. Marketing Optimization

Machine learning analyzes consumer data that enables businesses to deliver targeted ads that align with individual preferences and behaviors. This targeting enhances ad effectiveness, improves conversion rates, and maximizes ROI by reaching the right audience. For, email and content personalization, AI tailors marketing messages based on customer data, such as purchase history and browsing behavior.

Personalized content increases engagement, fosters loyalty, and drives sales. Further, AI-powered social media analytics provide insights into customer interactions and trends across platforms, which allows companies to refine their marketing strategies and improve brand visibility. AI also has applications in predictive analytics for campaign optimization and automated A/B testing to determine effective marketing approaches.

Startup to Watch: Apollo

Chinese startup Apollo provides a platform that allows businesses to optimize Amazon ads and enhance influencer marketing. Its algorithm, ARGUS, predicts market trends and calculates optimal keyword bids and budgets to maximize returns. The automated bid adjustments reduce advertising costs while maintaining sales, with transparency into changes. Its tag management feature organizes campaigns by allowing filtering and sorting through customizable tags.

The startup’s campaign creator tool enables businesses to launch high-ROI campaigns using suggested bids and proven structures. It also streamlines collaborations with TikTok shop creators through automated email sequences for businesses to reach new audiences. Apollo provides brands with new growth opportunities by eliminating wasted spend and improving ad efficiency.

10. Returns and Refunds Management

Businesses use AI to evaluate patterns in return reason data, understand why products are returned, and find ways to address issues. This allows to reduce return rates and improve product offerings. AI system identifies suspicious return activities, such as repeated or high-value item returns, by analyzing customer behavior and transaction history to prevent revenue loss from fraudulent activities. Further, in reverse logistics, AI streamlines the process of managing returned goods by assessing product condition and resale value to ensure efficient routing and processing. It reduces costs associated with handling returns and improves recovery rates.

Startup to Watch: Frate

Canadian startup Frate offers an e-commerce returns automation platform to reduce returns volume. It offers features such as one-click exchanges, peer-to-peer returns, and AI-powered virtual condition assessments. The platform automates the returns process, from requests and label generation to refunds that allows customers to delay returns in exchange for sustainability incentives.

AI-based image verification checks item conditions before shipping, where non-perfect items are resold on branded marketplaces to capture upsell opportunities with instant exchanges. The perfect items are resold as new with full refunds, used items receive partial refunds, and damaged ones are recycled. Frate’s approach converts returns into new sales to offer customers discounts on eco-friendly products and aligns merchants with sustainable practices.

Act Now to Take Advantage of Top AI and eCommerce Technologies

Investors like Y Combinator, Techstars, Antler, Google for Startups, and 500 Global support startups focusing on AI applications in eCommerce. They provide crucial funding that drives innovation. This funding spans seed funding, early-stage VC/series A, pre-seed, angel investments, and venture rounds. This diverse funding landscape encourages the creation of tools that improve personalization, inventory management, and customer engagement and support the future of AI in e-commerce.

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