The Role of Generative AI in E-Commerce

Introduction

E‑commerce has become a fiercely competitive landscape where customer expectations are no longer just nice to meet; they’re critical to survival.

Shoppers now expect hyper‑personalized recommendations, lightning‑fast service, and clear, compelling product content.

But maintaining all of that manually across thousands of SKUs and millions of customer interactions isn’t sustainable for most brands.

Traditional methods are straining under the pressure of scale, leading to cost blowouts, inconsistencies, and slower response times.

What was once an experimental novelty is now rapidly becoming a foundational capability for e‑commerce brands.

• Nearly 89% of retailers are either using AI in daily operations or running pilot projects.
• The AI‑enabled e‑commerce market is valued at about US$8.65‑9.0 billion, with projections placing it well above US$60 billion by 2032‑2034.
• About 77% of e‑commerce professionals now use AI daily, and 80% of executives believe AI‑powered automation will be standard by the end of the year.
• Consumer behavior is shifting sharply: in recent surveys, 39% of consumers report using generative AI tools for online shopping, with over half planning to do so soon.

Why Generative AI is changing the way products are sold online

At its core, e‑commerce is about helping people make informed decisions, how products are presented, described, and discovered.

Generative AI changes that game by automating, personalizing, and scaling many of the internal and external processes.

Below are the ways it does so, with verified data & platform examples.

External Impact

The real impact of Generative AI in E-commerce

40% of retail tasks are automated by AI

• McKinsey’s 2023 report indicates that nearly 40% of retail tasks, ranging from content creation to inventory updates and customer service, can be automated using AI.
• This automation reduces the need for manual effort on repetitive tasks.
• For example, product descriptions that once took hours to write can now be generated in seconds. AI chatbots handle customer queries and basic support requests.
• As a result, teams can focus on strategy, new product launches, and customer engagement, improving operational efficiency and reducing costs. (Source)

60% of online retailers use AI personalization

• Forbes reported in 2024 that 60% of online retailers have implemented AI personalization tools that track user behavior, purchase history, and browsing patterns to show relevant products.
• Personalized recommendations help customers find what they need faster, increasing satisfaction and trust.
• For instance, a shopper browsing for running shoes might see suggestions for socks, insoles, or fitness trackers that match their style and size.
• This not only boosts engagement but also drives more purchases per visit, enhancing overall conversion rates. (Source)

AI recommendations contribute up to 30% of retailer revenue

• According to Salesforce’s 2023 data, AI-driven product recommendations account for up to 30% of total revenue in some retail companies
• By analyzing customer behavior and preferences, AI can suggest products they are likely to buy.
• This keeps shoppers exploring multiple products in a single visit and increases average order value.
• For retailers, this means AI is not just a supporting tool; it directly drives revenue growth by turning browsing into buying opportunities. (Source)

$229 billion in global online sales influenced by AI

• Salesforce’s 2024 holiday shopping data shows that AI tools, including recommendation engines, targeted offers, and conversational agents, influenced $229 billion in global online sales
• This highlights how AI is shaping shopper behavior on a massive scale. By providing relevant suggestions and faster answers to questions, AI helps customers make purchasing decisions more efficiently.
• Retailers benefit from higher sales volumes and better customer experiences during peak shopping seasons. (Source)

Retailers could unlock up to $390 billion in value with AI

• McKinsey estimates that generative AI could unlock up to $390 billion in value for the retail industry by automating tasks, enhancing personalization, and improving decision-making.
• This potential value comes from multiple areas: lower operational costs, higher revenue through personalization, faster time-to-market for products, and improved inventory management.
• Retailers that adopt AI strategically can gain a significant competitive advantage while improving both efficiency and customer satisfaction. (Source)

Do companies really benefit from Generative AI?

Generative AI can deliver value to businesses of all sizes, but the way it is used varies depending on resources and scale.

Small startups

• Small e-commerce businesses often struggle with limited staff and resources for content creation and customer support. AI can generate product descriptions, write marketing content, and assist in social media posts.
• Chatbots powered by AI can handle frequently asked questions, freeing the owner or team to focus on strategic decisions.
• Example: Meesho utilizes AI to handle thousands of daily customer queries, enabling a small team to serve a larger number of customers more efficiently.

Mid-Size brands

• Mid-size brands typically have larger catalogs and more complex operations. Generative AI can power recommendation engines, helping customers discover products that match their preferences.
• AI also helps optimize SEO content to improve search rankings and assists with inventory management and demand forecasting, preventing stockouts and overstocking.
• Example: Amarra, a mid-size gown distributor, used AI to reduce overstock by 40% and create product descriptions 60% faster.

Enterprises

• Large e-commerce companies deal with massive data volumes and complex logistics. Generative AI helps automate logistics, predict demand across regions, and optimize supply chains.
• AI enables hyper-personalized experiences, tailoring recommendations, promotions, and messaging to each customer while providing analytics for faster, informed decisions.
• Example: Amazon uses AI-driven recommendations that contribute up to 30% of revenue, and Walmart employs AI for inventory and order management across its global network.

How Generative AI is reshaping different e-commerce sectors

Fashion & apparel

In the fashion space, where seasonality, personalization, and visual presentation are critical, Gen AI is becoming indispensable.

• Take Zalando, for example, the European fashion giant is now using AI to create marketing visuals and model imagery.
• What used to take six to eight weeks of manual production is now being turned around in just 3–4 days, with up to 90% cost savings.
• This has allowed them to launch campaigns faster, align with current trends in real-time, and improve customer engagement by showing more relevant, diverse models.

Source: Reuters.com

Pet products & pet care

An industry you might not expect to be leading in Gen AI adoption, pet products, is actually ahead in several areas.

Pet food brands, for instance, are using AI to create personalized nutrition plans, generate custom product recommendations, and forecast demand more accurately.

According to recent reports:

• 68% of pet food companies use AI for personalization
• 70% are applying it in supply chain optimization and demand forecasting
• 37% use AI chatbots for customer support

Source: Zipdo

Furniture/home furnishings

About 45% of furniture retailers had integrated AI tools into their operations by 2023.

AI‑powered virtual showrooms increased online furniture sales conversion rates by up to 25‑30%.

IKEA Kreativ

• IKEA has launched an AI assistant that helps customers design rooms using IKEA’s furniture collection. It takes the user’s style preferences and suggests items, layout, etc.
• By helping customers see furniture in their own or a simulated context, AI helps with decision confidence and reduces returns, improving upsell opportunities.

Source: bhg

Food service

• Applebee’s and IHOP are working on AI‑powered personalization engines to suggest menu items and deals based on a customer’s past orders and those of similar diners. The goal is to increase loyalty and upsells.

• Preacher’s Son (fine dining) introduced a chatbot “Becca” that helps with wine pairing suggestions based on menu and customer preferences.
• This helps enhance experience, adds engagement, and possibly drives up average order or complement sales.

Source: theverge

How to decide if Generative AI is right for your business

Generative AI can bring big benefits, but it only works if it addresses real business challenges.

Before adopting it, you should carefully evaluate whether it fits your needs. Here’s a clear approach:

Step 1: Identify your pain points

Look at the areas where your business is struggling. AI works best when it solves a clear problem. Common pain points include:

• Slow content creation: Writing product descriptions, marketing copy, or blog posts takes too much time.
• Low conversions: Visitors browse your site but leave without buying because product discovery or recommendations are weak.
• High customer support workload: Your team spends hours handling repetitive questions, delaying responses to more complex issues.

Understanding your current challenges helps you see where AI could make the most impact.

Step 2: Consider how your products are sold

Not every business benefits equally from AI. Ask:

Does personalization drive your sales?

If customers expect tailored recommendations or content, AI can deliver it automatically.

Is speed critical for your operations?

For example, quickly creating product catalogs, updating promotions, or managing inventory online.

If your success depends on fast, personalized experiences, generative AI is likely to improve efficiency and increase sales.

Step 3: Ask key questions to evaluate fit

Before implementing AI, answer these questions honestly:

• Are we struggling to scale content across all products and marketing channels?
• Are we losing customers because they cannot easily find the products they want?
• Can AI reduce support workload while keeping service quality high?

By auditing your pain points, evaluating how your products are sold, and asking the right questions, you can decide if generative AI is right for your business.

The key is to focus on areas where AI will save time, improve customer experience, and increase revenue.

How to implement generative AI in your E-commerce stack

Implementing generative AI in your e-commerce business doesn’t have to be overwhelming. The key is to approach it step by step, starting small, learning from initial results, and then scaling strategically. Here’s a practical roadmap:

Step 1: Pilot small

Start with simple, high-impact tasks that are easy to measure. Common starting points include:

• Product descriptions: Use generative AI to create or optimize product copy. This can save hours of manual writing and ensure consistency across thousands of SKUs.
• Chatbots for customer support: Deploy AI-powered chatbots to answer common customer questions such as shipping policies, product availability, or return procedures.
• Why it works: Piloting small reduces risk and lets your team observe real benefits quickly. You can see improvements in efficiency, customer engagement, and content quality without overhauling existing systems.
• Example: A mid-size fashion retailer started with AI-generated product descriptions for 500 SKUs. Within a month, content creation time dropped by 50%, and product pages became more engaging for shoppers.

Step 2: Integrate recommendation engines and SEO tools

Once the pilot proves successful, expand AI to enhance customer experience and marketing:

• Recommendation engines: Use AI to suggest products based on browsing history, past purchases, or similar shopper behavior. This helps customers discover relevant products and increases the likelihood of additional purchases.
• SEO content optimization: Generative AI can create blog posts, category descriptions, and meta content optimized for search engines, improving your visibility and organic traffic.
• Why it works: AI here starts impacting revenue directly by improving product discovery and driving more qualified traffic to your site.
• Example: An online electronics store implemented AI recommendations across its catalog. Conversion rates for recommended products increased by 25%, and shoppers spent more time exploring related items.

Step 3: Connect to backend systems

The next step is integrating generative AI with your operational backend:

• Inventory management: AI can forecast demand, predict stockouts, and suggest replenishment schedules.
• Logistics planning: AI can optimize warehouse operations, delivery routes, and fulfillment schedules.
• Why it works: Integrating AI with backend systems reduces waste, ensures products are available when customers need them, and keeps operations running smoothly.
• Example: A mid-size apparel brand connected AI forecasting to its inventory system. Overstock was reduced by 35%, while popular items stayed in stock, leading to higher sales and lower storage costs.

Step 4: Scale with measurable KPIs

Once AI is integrated across customer-facing and operational systems, it’s time to scale and measure impact:

• Track KPIs such as conversion rate uplift, reduced churn, faster content creation, and improved time to market for new products.
• Continuously refine AI models based on performance data and customer behavior.
• Why it works: Scaling without measurement can lead to wasted effort. Tracking clear KPIs ensures AI investments deliver tangible business results and helps you prioritize further AI initiatives.
• Example: A large e-commerce marketplace scaled AI across content creation, recommendations, and logistics. Within six months, conversion rates improved by 15%, cart abandonment dropped by 12%, and content creation time was reduced by 60%.

Implementing generative AI is a gradual journey. Start small, prove value, expand into marketing and operations, and finally scale with clear metrics.

By following this structured approach, businesses of all sizes can harness AI effectively, improving efficiency, boosting revenue, and enhancing the customer experience.

What’s next for Generative AI in e-commerce

Generative AI is still evolving, and the next wave of innovation will change how customers shop and how businesses sell.

Here are three major directions shaping the future of e-commerce:

Virtual commerce and hyper-realistic try-ons

• Shopping online often comes with uncertainty: Will this shirt fit me? Does this sofa look good in my living room? Generative AI is addressing this by powering virtual try-ons and interactive product previews. Customers can upload their photo or room dimensions, and AI can generate realistic previews of how products look on them or in their space.
• This goes beyond static images. Imagine trying on sneakers virtually in your size or visualizing a dining table in your actual home before buying. By reducing guesswork, AI lowers return rates and gives customers confidence in their purchases.

AI-Generated influencer campaigns and ad creatives

• Influencer marketing is a cornerstone of e-commerce, but creating fresh campaigns is time-consuming and expensive.
• Generative AI is beginning to create realistic influencer-style content, from product demos to lifestyle shots, without requiring a full production team.
• E-commerce brands can also use AI to generate ad creatives tailored to different audiences.
• For example, the same product ad might feature different visuals and copy depending on whether it’s shown to a college student or a working professional.
• This level of personalization can increase ad performance while reducing costs.

Fully autonomous e-commerce experiences

• Looking ahead, generative AI may enable “self-running” e-commerce operations. Imagine an online store that automatically generates new product descriptions, creates targeted campaigns, forecasts demand, updates inventory, and responds to customer queries, all with minimal human input.
• While businesses will still guide strategy and decision-making, AI could handle much of the execution.
• This future opens the door to leaner teams, faster go-to-market timelines, and highly personalized customer journeys that adjust in real time.

The future of generative AI in e-commerce is about giving customers more confidence, brands more creativity, and businesses more automation.

Companies that start exploring these opportunities today will be better positioned to lead the next era of online retail.

Summing up

Generative AI isn’t just “nice to have” anymore; it is quickly becoming the foundation of how products are sold and how customers engage with e-commerce brands.

From generating product copy to predicting demand and creating personalized shopping journeys, AI is transforming every layer of the online retail experience.

The businesses that adapt to this shift will not only meet customer expectations but also gain a clear competitive edge.

To get real value, companies must go beyond experimentation. It’s important to assess where AI fits into their operations, what return on investment it can deliver, and whether the organization is ready for adoption.

By starting with clear goals and scaling thoughtfully, e-commerce businesses can turn generative AI into a core driver of growth and customer loyalty.

External sources:

This blog drew insights and data from trusted resources:

1. DemandSage
2. Ecomposer
3. Search Engine Land
4. Shopify Help Center
5. Business Insider
6. Wifitalent
7. GitnuxWorldmetrics
8. Worldmetrics
9. nw-arkansas