AI is woven into every part of modern e-commerce.
Leading brands use it to forecast demand, personalize storefronts, automate customer conversations, and optimize fulfillment with far greater accuracy than manual workflows.
They rely on machine learning to predict what each shopper is likely to buy next. They use conversational AI to handle sales queries inside chat interfaces. And they deploy automation in e-commerce platforms to manage inventory and cut operational waste.
This shift is happening. Companies that adopt AI early are running leaner operations and converting more sessions into sales.
In this article, we break down how brands are using AI in e-commerce to simplify operations end-to-end.
Here’s an overview of how AI is trending in the e-commerce market:
Based on examples available on the market, brands in e-commerce are using AI in the following ways:
50% of consumers report that they would rather interact with a chatbot instead of a human for routine activities such as finding a product for them. AI is making it really easy to find a product.
AI analyzes real-time signals like browsing patterns, price sensitivity, and seasonality to surface products customers are more likely to buy. Instead of manual rule-based engines, AI adapts instantly to emerging trends and inventory changes.
This reduces wasted impressions by showing what works, not what’s available.
Two-thirds of customers expect answers to their inquiries within 10 minutes (often instantly). AI-powered chatbots assist in such situations, reducing resolution time from an average of 38 hours to just 5.4 minutes for level one inquiries, which aligns with customer expectations.
These chatbots reduce the customer service cost by 30% compared to what brands invest in 24/7 support agents. Human agents get to focus more on complex or challenging issues that demand their expertise, leaving the simple queries for the chatbots.
AI influencers have moved from novelty to a proven marketing strategy, helping e-commerce brands cut through noise and reach digital-native audiences.
The following examples illustrate how global brands are already applying this technology:
Source: Sharelo
As consumers expect more relevance and less noise, brands that can “be smart” in serving the right message at the right time win.
Companies that grow faster drive 40% more of their revenue from personalization compared to their slow-growing counterparts. This personalization usually comes from identifying the unique moments or triggers in every buyer’s journey and using the same context in messaging.
This messaging can be targeted through email, push notifications, pop-ups, and even through voice agents.
Beyond these use cases, visual and voice searches are picking up pace. Visual search is one of the fastest-growing AI use cases in retail. According to Market Growth Reports, e-commerce and retail account for 62% of total visual searches, amounting to 1.4 billion monthly queries. Mobile usage dominates with 55% of these searches happening in apps, with categories like furniture and clothing showing adoption rates above 58% among top retailers.
Voice commerce is following a similar trajectory. Platforms like Alexa are seeing shopping interactions grow 40% year-over-year, and over half of users have made at least one purchase through voice commands.
For retailers, this is a signal to rethink discoverability; product listings must now be optimized not just for eyes but for ears, and optimized to be cited by these virtual assistants.
AI usage across sectors is no longer a new story.
You’re likely seeing it all around. The data from McKinsey support the fact that AI usage and adoption are accelerating. In a survey, 78% of respondents reported that their organizations currently use AI in at least one business function. In early 2024, it was 72%, and 55% a year earlier.
When it comes to e-commerce specifically, 84% of businesses are either actively integrating AI solutions or have it as a top strategic priority.
If we look at the global market of AI in the e-commerce market, it’s expected to grow from $5.79 billion in 2023 to $50.98 billion by 2033. It’s expanding at a compound annual growth rate of 24.3%.
North America currently leads with a market share of 38.6%.
Based on current data and market trends, AI’s most significant impact in e-commerce is personalization.
The average customer today interacts with AI-powered recommendations 85% of the time they shop online. This shift has redefined how brands engage, convert, and retain customers.
AI is set to increase sales from product recommendations by 59%. Researchers found that companies that grow faster drive 40% more of their revenue from personalization than slower-growing peers
Amazon embodies this perfectly. Product upselling and cross-selling account for 35% of Amazon’s total revenue, powered by AI-driven recommendation engines. These algorithms analyze browsing and purchase histories to suggest items customers are most likely to buy next.
But personalization isn’t only about relevance; it’s about trust. AI also helps filter fake reviews, ensuring credibility in product feedback. Amazon’s AI models now detect counterfeit reviews and prioritize verified ones.
A PR Newswire report found that 83% of consumers worldwide would browse or buy products directly through messaging conversations. Another 77% said they’re more likely to purchase if they can get real-time answers via chat.
That explains why AI chatbots now handle 40–60% of customer queries, drastically improving service efficiency. These assistants are no longer static pop-ups, they guide users, answer questions, and even trigger conversions.
Consumers are getting comfortable with this new normal:
However, there’s still a line customers won’t cross. 66% of consumers refuse to let AI make purchases on their behalf, even if it promises better deals. Most people like AI as a helper, not a decision-maker.
AI doesn’t just drive front-end experiences; it powers the logistics behind them. Predictive analytics is now core to managing inventory, pricing, and fulfillment in e-commerce.
A PwC Digital Supply Chain Survey found that 53% of companies use AI to anticipate and mitigate supply chain disruptions, while another 31% are piloting AI in forecasting and planning. These systems analyze historical and real-time data to predict trends, enabling better stock allocation and pricing decisions.
Meanwhile, 70% of e-commerce businesses report that AI improved inventory accuracy by over 25%, reducing overstocking and out-of-stock incidents. For retailers, that’s not just efficiency, it’s resilience.
As e-commerce expands, so do fraud risks. The e-commerce fraud detection and prevention market is expected to exceed $100 billion by 2029, more than doubling from 2023 levels.
According to Prove’s 2023 report,
Retailers are countering this with AI-powered fraud detection systems that analyze behavioral data, location patterns, and device signals in real time.
Beyond fraud risks, there’s a trust gap too.
58% of consumers worry about how AI handles their personal data, while 28% say they don’t trust any company with their information. Another 42% feel overwhelmed by “too many targeted ads,” suggesting personalization is crossing the line into intrusion.
When AI gets it wrong, the backlash is quick:
of shoppers have abandoned purchases because of poor AI interactions. 21% report that inaccurate recommendations frequently create frustration.
Source: Omnisend
Customers don’t mind AI when it’s useful, but they reject it when it feels manipulative or opaque. Brands must strike a careful balance. 48% of shoppers say improving AI-powered customer service should be retailers’ top priority.
McKinsey describes the future of e-commerce as agentic commerce, where autonomous AI agents will interact, negotiate, and transact on behalf of users. By 2030, this model could generate $3–5 trillion globally, unlocking a new wave of efficiency and consumer convenience.
Already, 28% of leading e-commerce players have integrated AI and machine learning platforms into their operations.
As these capabilities mature, consumers will increasingly rely on agents that compare prices, verify reviews, and even pre-empt purchases based on intent, blurring the line between shopping and automation.
Here are some questions people frequently ask when it comes to AI in e-commerce:
Amazon and Shopify are great examples. Amazon uses AI for product recommendations, dynamic pricing, and fraud detection. Shopify helps merchants use AI to predict demand, personalize emails, and automate customer support.
AI makes shopping faster, easier, and more personal. It recommends products based on browsing behavior, answers questions instantly through chatbots, and predicts when customers might reorder.
Based on G2’s top AI products in 2025 list, the top AI tools used in e-commerce are:
Start simple. Use AI chatbots to answer common questions, email automation tools to segment customers, and product recommendation apps to increase conversions.
Many affordable AI features are already built into platforms like Shopify, WooCommerce, and BigCommerce.
AI has transformed the way people shop and how brands sell. The real question is whether your e-commerce business is keeping up. From more brilliant product suggestions to automated service and inventory control, AI has the potential to simplify your customers’ entire journey.
The right tools can make it happen. Leverage automation to increase efficiency in your workflows and make the customers’ experience consistent throughout the journey. It’s realistic with AI-driven personalization and efficiency gains.
Discover more about e-commerce automation and learn how it combines efficiency and customer experience.
Sagar Joshi is a former content marketing specialist at G2 in India. He is an engineer with a keen interest in data analytics and cybersecurity. He writes about topics related to them. You can find him reading books, learning a new language, or playing pool in his free time.
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