glance

AI in E-commerce Business: Use Cases, Impact & Future Ahead

Ian Anderson2025-04-07

In 2010, ecommerce was about putting things in a cart. In 2025, it’s about context, prediction, and personalization. The ecommerce game has fundamentally changed, and AI is the silent engine driving this transformation.

According to Precedence Research, the global AI in the ecommerce market is projected to touch a staggering $45.7 billion by 2030. That's not just a growth story—it's a complete reshaping of how we buy, sell, and interact online. Add to that Epsilon's report stating 88% of online shoppers are more likely to purchase from brands offering personalized experiences, and it's clear: AI isn't just the future; it's the new standard.

In this guide, we’re diving deep into how AI is powering the ecommerce revolution. You’ll discover use cases, real-world stats, best practices, and a future-forward outlook that will help you stay ahead of the curve.

What Is AI in Ecommerce Business? 

ai in e commerce

At its core, AI in the e-commerce industry refers to the use of machine learning, natural language processing, and predictive algorithms to mimic human decision-making and personalize user experience at scale.

Think of it this way: traditional ecommerce reacts. AI-powered ecommerce anticipates.

By 2025, Gartner projects that at least 30% of digital businesses will use AI to improve customer experience. From personalized recommendations to voice search and dynamic pricing, AI is no longer a nice-to-have. It’s fundamental.

Key Use Cases of AI in Ecommerce Business (With Real-World Examples)

Let’s break down exactly where AI is showing up and reshaping the way ecommerce businesses operate.

A. Personalized Recommendations

Amazon’s product recommendation engine drives 35% of its total revenueAnd that’s just the beginning. AI algorithms analyze browsing history, purchase behavior, location, and even time of day to serve up the perfect product suggestion.

B. AI-Powered Customer Support (Chatbots & NLP)

AI chatbots now handle everything from order status to complex returns. IBM reports that AI can cut customer support costs by up to 30%.

Shopify’s AI assistant, Kit, helps merchants write Facebook ads, suggest products, and even manage campaigns—all via chat.

C. Dynamic Pricing & Demand Forecasting

AI helps ecommerce platforms adjust prices in real-time based on demand, competition, and inventory. McKinsey found that retailers using AI for pricing optimization saw a 2-5% increase in margins.

D. Visual & Voice Search

Visual search allows users to upload an image and get similar product suggestions. Voice search is booming too, especially with Gen Z consumers. HubSpot states that 62% of Gen Z prefers visual search over text.

E. Generative AI for Content Creation

From product descriptions to landing page copy, generative AI is cutting creative production time by half. According to BCG, brands using Gen AI tools see up to 40% reduction in content creation costs.

F. Inventory Optimization

Capgemini research shows that AI-driven inventory management can reduce stockouts by up to 30%. It predicts demand, aligns supply, and helps businesses avoid both overstocking and lost sales.

Benefits of Using AI in Ecommerce Businessai in fashion

1. Hyper-Personalization at Scale

AI enables retailers to offer every user a curated shopping experience. Using behavioral data, search patterns, and even social media activity, AI generates product suggestions that feel tailor-made — not just based on what users like, but what they might like next.

Did you know? McKinsey reports that personalization can drive a 10–15% revenue uplift in eCommerce.

2. Intelligent Search and Discovery

With AI-powered semantic search (like Algolia or Shopify's AI search), consumers no longer have to type perfect keywords. Instead, the system understands intent — even if queries are vague or misspelled.

For example: Searching for “comfy work-from-home shoes” yields results aligned with comfort, style, and use case — not just brand or category.

3. Dynamic Pricing and Inventory Management

AI models predict demand spikes, competitor pricing shifts, and supply chain constraints. This allows businesses to automatically adjust prices for higher conversions and profit margins, while also minimizing stockouts or overstock issues.

4. Conversational AI & 24/7 Support

AI chatbots like ChatGPT or ElevenLabs offer real-time, context-aware support. They reduce support ticket volumes by 40–60%, resolve common issues quickly, and improve CSAT scores — especially outside working hours.

5. Fraud Detection and Security

AI’s pattern recognition is unmatched in detecting anomalies — from suspicious login attempts to unusual checkout behavior. This safeguards both the merchant and consumer from evolving cyber threats.

According to PwC, AI adopters in retail saw a 25% average increase in customer satisfaction, and the World Economic Forum highlights $70B saved annually in supply chain planning alone.

Challenges & Barriers in Adoption of AI in Ecommerce Business 

use of AI in ecommerce

1. Data Dependency and Quality Issues
AI thrives on data. But poor data hygiene, siloed systems, or inconsistent labeling can skew outcomes — leading to irrelevant recommendations or flawed automation.

2. Integration with Legacy Systems
Many traditional eCommerce platforms aren’t designed with AI in mind. Integrating AI tools with ERP systems, POS data, or outdated CMS platforms can delay rollouts and require costly middleware solutions.

3. Cost and Resource Constraints
Deploying generative AI — especially with custom models — can be expensive. From hiring skilled data scientists to paying for computer infrastructure, the costs can be prohibitive for SMBs without clear ROI projections.

4. Talent Gap in AI and ML
There's a global shortage of skilled professionals in AI, ML, and data science. Even if tools are available, lack of in-house expertise can prevent proper implementation and long-term optimization.

Only 26% of small ecommerce businesses use AI (Statista). Also, Cisco reports that 65% of consumers are concerned about how their data is used in AI-based personalization.

How is Glance AI Transforming Ecommerce Business Globally? 

Leveraging AI for personalized shopping, virtual try-ons, and predictive trend analysis, Glance is redefining the fashion industry. Glance AI app offers:  

  • Personalized Recommendations: Using AI, Glance understands your style preferences, making sure every product suggestion feels like it was handpicked for you.
  • AI Styling: With Gen AI, the app allows you to visualize outfits on your own digital avatar, removing the guesswork and reducing returns.
  • Predictive Trend Analysis: By analyzing global fashion data, Glance can forecast emerging styles, ensuring you’re always ahead of the curve.

So you can stay ahead of the fashion industry. 

What is the Future of AI in E-commerce?

So, what’s next? As AI continues to mature, you can expect:

Deeper Personalization:

Beyond just style recommendations, AI might tailor entire lookbooks based on your past purchases, social media activity, or even local weather.

Immersive AR/VR Stores:

Imagine browsing a virtual store where you walk through digital aisles, pick up items, and try them on in a 3D environment—no real-world store needed.

Sustainability Analytics:

AI could analyze every stage of a product’s lifecycle to ensure ethical sourcing, minimal waste, and carbon footprint reduction.

Real-Time Inventory and Pricing:

Dynamic pricing and stock management could become even more precise, ensuring you always find what you need, right when you need it.

Voice Commerce:

With advancements in natural language processing, you might soon ask your voice assistant to “show me a red jacket for under $100” and get instant, curated results.

Wrap Up

AI is propelling the global fashion industry to new heights. With its growing role in fashion, it's taking the shopping experience to the next level. It’s making shopping more interactive, personalized, and efficient. No more “Will this look good on me?”  AI styling features can show you exactly how an outfit fits before you click “buy.” Additionally, chatbots powered by AI can answer your questions in real time, guiding you toward the perfect purchase.

AI in the e-commerce &  fashion industry is not just about convenience. This tech-driven shift also encourages more sustainable choices by helping brands avoid overproduction and reducing the rate of returns. In essence, AI is aligning business goals with consumer desires, making fashion more responsive to individual needs while staying mindful of environmental impact.

FAQs

1. How is AI used in the fashion industry?
AI powers virtual try-ons, trend forecasting, and personalized styling. It also optimizes supply chains and reduces overproduction.

2. What is an AI eCommerce business?
It’s an online retail model that uses AI for recommendations, chatbots, pricing, and customer insights to boost sales and experience.

3. How is AI used in eCommerce?
AI drives smart search, personalization, inventory planning, and fraud prevention—making online shopping faster and smarter.


 

Glance

Ian Anderson is VP of AI at Glance, leading innovation in Gen AI, computer vision, and NLP. He holds a PhD in Mobile Computing and formerly led the Data Science team at InMobi’s Unified Marketing Cloud.


 

Download the Glance AI app now