The Real Role of AI in Ecommerce: It’s Not Just Product Recs Anymore

Beyond the Rec Engine

Most e-commerce brands still associate AI with one thing: product recommendations.

But the smartest companies know that AI isn’t just a marketing gimmick. It’s becoming a foundational layer across their business, impacting everything from merchandising and inventory to customer experience and operations.

This shift matters. More than 80% of U.S. retailers plan to increase their use of AI across operations this year, not just for the front end but also for backend systems that directly drive margin and efficiency.

This article breaks down how e-commerce brands are using AI across the entire customer journey and business stack. We’ll explore real use cases, tools, and strategies you can implement to stay ahead of the curve.

AI for Merchandising and Inventory Planning

Artificial intelligence is transforming how e-commerce retailers approach merchandising and inventory management. By leveraging AI-driven tools, businesses can forecast demand more accurately, optimize stock levels, and reduce operational inefficiencies.

Amarra, a New Jersey-based global distributor of special-occasion gowns, integrated an AI-powered inventory management system to predict stock needs based on historical data and seasonal trends. This implementation led to a 40% reduction in overstocking, enhancing efficiency and customer experience. 

Why AI-Driven Merchandising Is a Game Changer for e-commerce

• Enhanced Demand Forecasting: AI models analyze historical sales data, market trends, and external factors to predict future demand, reducing the risk of overstocking or stockouts.
• Optimized Inventory Levels: By predicting demand more accurately, retailers can maintain optimal inventory levels, reducing holding costs and increasing turnover rates.
• Personalized Merchandising: AI tools enable dynamic product assortments tailored to customer preferences, enhancing the shopping experience and increasing conversion rates.

Here’s a look at how generative AI is being applied across key ecommerce merchandising functions.

Implementing AI in backend operations has led to measurable improvements. For instance, AI integration in logistics has resulted in a 15% reduction in logistics costs, a 35% improvement in inventory management, and a 65% boost in service levels. (Gauss).

By automating and optimizing these critical functions, e-commerce businesses can achieve significant cost savings and operational efficiencies.

Where AI Delivers the Most Impact in CX Today

Here are the most common and effective applications of AI in customer experience:

• Smarter Site Search: AI tools understand misspellings, vague queries, and natural language, helping customers find the right product faster.
• Dynamic Content Rendering: Product pages, banners, and offers adjust based on browsing history, location, or referral source.
• Conversational AI and Chatbots: Tools trained to answer FAQs, recommend products, or assist with orders without escalating to a human unless needed.

These aren’t futuristic ideas. They’re already in play at top-performing e-commerce brands, helping customers feel like the experience was built around them, not a funnel.

AI Is Quietly Powering the Back End of E-commerce

While AI often gets attention for what customers see on the front end, some of the biggest gains are happening behind the scenes. Brands are using AI to automate support, streamline logistics, prevent fraud, and improve operational decision-making.

These backend systems are rarely flashy, but they drive real business outcomes like lower costs, faster resolution times, and better customer retention.

How AI Is Reshaping Core E-commerce Operations

Here are some of the most impactful backend use cases where AI is actively solving problems and increasing profitability:

• Customer Support Automation: AI chatbots handle FAQs, order status updates, and returns without involving human agents.
• Fraud Detection: AI models analyze transactional patterns to flag suspicious behavior in real time.
• Returns Forecasting: AI predicts return likelihood based on product type, customer history, and behavior, helping reduce reverse logistics costs.
• Inventory and Fulfillment Optimization: AI helps determine optimal stock levels, warehouse placement, and delivery paths to improve speed and lower shipping costs.

These applications create a more efficient e-commerce engine that helps brands scale without scaling headcount.

AI Is Directly Impacting E-commerce Profitability

AI isn't just improving e-commerce experiences. It's driving real financial results. From better inventory decisions to automated upselling, AI influences nearly every part of the customer journey that affects revenue and margin.

Further, AI could unlock between $240 billion and $390 billion in annual value for retailers, equating to a margin increase across the industry of 1.2 to 1.9 percentage points.

When used strategically, AI allows brands to increase revenue while reducing costs, which is a rare double win in e-commerce.

These are the areas where AI is delivering measurable improvements to the bottom line:

• Fewer Stockouts and Overstocking: Smarter forecasting helps brands meet demand without tying up capital in excess inventory.
• Higher Average Order Value: Personalized recommendations and dynamic bundles boost AOV without increasing ad spend.
• Lower Support Costs: AI handles routine customer inquiries, reducing the need for large support teams.
• Improved Retention: Better experiences lead to more repeat customers and higher lifetime value.
• Reduced Returns: AI tools can match shoppers with the right size or product fit, reducing return rates and associated costs.

Brands often look to promotions or cost-cutting to improve profitability. But AI opens a different path: smarter decisions that lead to healthier margins without discounting or sacrificing experience.

AI Is No Longer Optional for Growth-Oriented E-commerce Brands

If your AI strategy begins and ends with product recommendations, you're missing the bigger opportunity.

The most competitive e-commerce brands are applying AI across their entire business, not just to impress shoppers on the front end, but to build intelligent systems that scale profitably, adapt quickly, and retain customers longer.

From forecasting demand and optimizing inventory to automating customer support and personalizing site experiences, AI is proving its value far beyond marketing.

Here’s what separates brands that are scaling with AI from those just experimenting:

• They start with real business problems, not shiny tools. AI is applied where it drives measurable impact like reducing returns, improving sell-through, or increasing AOV.
• They integrate AI across functions. It’s not siloed to one team. Ops, CX, marketing, and support all use it to improve decision-making and workflows.
• They treat AI as a multiplier, not a magic trick. Instead of hoping AI “fixes” weak processes, they use it to amplify what already works.

The goal isn’t to replace people or over-automate. It’s to build an effective, more adaptive e-commerce engine that can grow sustainably even in an evolving market.

About the Author

Caleb Bradley Founder & CEO at Bighorn Web Solutions LLC

Caleb Bradley is the Founder and CEO of Bighorn Web Solutions LLC, a specialized eCommerce development agency established in 2020. With over a decade of experience in the eCommerce services space, Caleb has led his team of experts in platforms like Shopify Plus and Magento, focusing on site speed, conversion rate optimization, platform migrations, and custom development. Under his leadership, Bighorn Web Solutions has garnered recognition, including being named one of the Top 3 Best Design & Development Agencies to hire in 2025 by DesignRush! along with one of Clutch’s Top 100 Fastest-Growing Companies for 2025. Caleb’s commitment to delivering high-quality, revenue-generating eCommerce experiences has earned praise from clients, positioning Bighorn Web Solutions as a trusted partner in the industry.

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