In a recent McKinsey survey, 78% of organizations report using AI in at least one business function, up from just 55% a year ago.
That rise signals a tipping point: AI has shifted from niche experiments to foundational tools that are redefining how we work and shop.
This changes things for retailers and e-commerce too.
Imagine systems that anticipate what your customers want, create the right message at the right moment, optimize pricing in real time, and even rebuild store layouts on the fly – all without manual input.
In 2025, these aren’t futuristic scenarios.
In our article, we’ll look at how top platforms are weaving AI into the very fabric of their operations.
Table of contents
- Numbers that matter
- AI & automation innovation lessons from the best in the industry
- #1 Personalization of customer experience
- Example 1: Amazon’s real-time adaptation engine
- Example 2: Shopware and its contextual Copilot
- Example 3: Bloomreach and its multi-channel intelligence with Loomi
- Example 4: Otto and its 70+ AI-powered personalization modules
- #2 Marketing and communication automation
- Example 1: Klaviyo and its predictive churn & order timing engine
- Example 2: Brevo and its Aura multi-agent marketing assistant
- Example 3: Shopify and its Sidekick goal-based campaign builder
- #3 Intelligent deep search and data analysis
- Example 1: Shopware and its Spatial Commerce discovery toolkit
- Example 2: eBay and its agentic AI shopping assistant
- Example 3: Nosto and its generative synonym engine
- #4 Business process & operations automation
- Example 1: Alibaba International and its Aidge-powered supply chain & dispute automation
- Example 2: Kaufland and its AI demand forecasting engine
- #5 Content generation & UX optimization
- Example 1: Optimizely and its Opal AI content & layout engine
- Example 2: AB Tasty and its emotionally intelligent UX personalization
- Final thoughts
Before AI, marketing teams often spent their days running manual workflows like drafting emails, updating segments or scheduling batches.Now, AI systems take on the heavy lifting, predicting the optimal time to reach a customer, generating personalized content, and adjusting campaigns in real time.
AI today does much more than provide automated replies. It powers core functions through:
- predictive models that assess who’s likely to churn or when they might return.
- generative engines that craft personalized emails, SMS messages, banners, and product copy, all tailored to individual behavior.
- dynamic experiences where store layouts, pricing, and offers update instantly based on customer actions, inventory, and context.
- ad optimization tools that auto-adjust creatives and bids to maximize campaign efficiency.
- conversational assistants that guide selections, analyze sentiment, and make shopping feel seamless and helpful.
These systems operate behind the scenes, driving improvements in customer engagement and business metrics.
As we’ll see, companies from Shopware and Amazon to Klaviyo are integrating AI into personalization, discovery, marketing, and operations: making e-commerce smarter, faster, and more relevant.
Behind these shifts is a story of mindset change.
Many smaller retailers hesitate, worried AI tools are too complex or costly. But when brands pilot AI in narrowly scoped areas, like churn-risk emails or subject-line generation, they quickly experience measurable gains and confidence grows.
AI becomes a trust-building partner in everyday marketing.
Numbers that matter
- 76% of consumers expect personalization in shopping – frustration is the result when they don’t get it.
- 84% of e-commerce brands view AI as a strategic priority in growth plans.
- The AI-in-retail market is projected to hit $15.3 billion in 2025, growing at about 36% annually.
- Personalization tools have been shown to increase average order values by up to 369% in certain use cases.
These data points clearly show that AI in e-commerce is playing a core role in delivering measurable business impact.
How do companies respond to this shift?
Some approach AI with caution, rolling out select features and carefully monitoring their effects. Others move quickly, integrating advanced AI into nearly every touchpoint of the customer journey.
A few choose to experiment in smaller areas first, testing tools in marketing, search, or logistics, before scaling up.
No matter the pace, one thing is clear: AI and automation are shaping how the industry operates, what customers expect, and how brands compete.
The rest of this article looks at the companies setting new standards, the innovations that stand out, and the areas where real value appears, not just in theory, but in daily operations and customer experiences.
AI & automation innovation lessons from the best in the industry
#1 Personalization of customer experience
Most personalization still feels basic, but leading platforms now deliver intuitive, tailored experiences. Brands using advanced personalization see up to 40% more revenue and 20% higher conversion rates, proving that true customization drives real results.
Example 1: Amazon’s real-time adaptation engine
Let’s start with Amazon here. Their generative AI continuously rewrites product descriptions, reorders recommendations, and even tweaks storefront layouts based on your behavior.
Look at your cart, pause on a product image, and the page shifts. That’s the system learning your intent in real time.
Amazon’s approach to personalization is rooted in its ability to analyze immense amounts of behavioral data.
For example, when a user hesitates on a category or returns to a product page, Amazon’s recommendation engine responds by surfacing relevant accessories, alternative brands, or seasonal deals.
This ongoing optimization reportedly contributes to Amazon’s industry-leading repeat purchase rates and helps drive their Prime program’s remarkable retention.
Example 2: Shopware and its contextual Copilot
Meanwhile, across the field, Shopware has raised personalization by bringing context into the mix.
Think “I’m planning a trip to New York” typed into the search bar – and Shopware offering suitcases, city guides, travel sneakers without you ever specifying “luggage.”
Their AI Copilot tags customers automatically, summarizes reviews, creates custom checkout messages – and it knows what you like and what you need before you do.
Shopware’s innovation stands out in a crowded landscape because it understands context and intent, so product discovery feels natural and frictionless.
Example 3: Bloomreach and its multi-channel intelligence with Loomi
And Bloomreach’s Loomi AI feels less like a tool and more like a backstage director.
It connects your email opens, purchase rhythms, and even your churn risk, delivering a fluently personalized journey across devices.
Loomi runs deep – supporting search in over 30 languages and orchestrating messaging that feels personal, because it really is.
Bloomreach’s ability to unify customer data across email, web, and even SMS channels means that every shopper’s journey adapts on the fly.
Retailers using AI solutions see not only higher engagement rates, but also report a smoother customer experience – where product recommendations, on-site banners, and even follow-up campaigns reflect what the customer is doing in real time.
Brands using multi-channel personalization can achieve a 19% lift in average order value.
Example 4: Otto and its 70+ AI-powered personalization modules
Otto is redefining what it means to embed intelligence into every layer of a retail experience.
With more than 70 AI-powered modules in continuous operation, Otto has transformed personalization, logistics, content, and customer service into a seamlessly orchestrated system – setting the standard for intelligent commerce at scale.
Across the shopper journey, Otto delivers real-time, behavior-driven personalization.
From the moment a visitor lands on otto.de, AI adapts homepage layouts, refines product search results with semantic intelligence, and even delivers motivational nudges – all informed by browsing history, cart behavior, and purchasing patterns.
This creates a shopping experience that feels personal and personalized to the second.
Under the hood, Otto’s AI forecasts 7.5 billion sales and returns scenarios monthly, empowering smarter inventory planning, campaign timing, and warehouse logistics.
But Otto’s commitment to intelligence goes far beyond commerce mechanics. They’ve developed their own generative AI platform, ogGPT, used by employees daily to craft text, generate images, and speed up internal workflows – processing over 3,000 prompts and 1,700 images a day.
It’s also being tested in customer-facing pilots, like a chat assistant trained on product reviews and descriptions, which successfully guided users to the right purchases in seconds.
Otto is also pushing into AI-powered content production, automatically generating product descriptions to support their rapidly growing marketplace.
They’re even exploring A/B testing of AI-generated product images based on visual context, like staging a sofa in a loft versus a small apartment, to increase conversions.
Every part of this ecosystem reflects Otto’s long-term platform strategy: not just using AI to optimize what’s already working, but creating a continuously learning commerce environment where scale and personalization coexist.
The result? Fewer abandoned carts. Shorter decision times. And a measurable lift in customer loyalty.
Otto isn’t adapting to AI trends, they’re shaping them. And for the rest of the industry, they’ve become the benchmark for what’s possible when AI is truly end-to-end.
#2 Marketing and communication automation
Marketing teams used to spend hours on emails and A/B testing. In 2025, AI handles the busywork and adds real-time intelligence – powering faster launches, sharper targeting, and fully personalized campaigns that adapt automatically to user behavior.
Example 1: Klaviyo and its predictive churn & order timing engine
Klaviyo uses its predictive engine to spot who’s about to churn or place another order.
With churn risk and “expected date of next order” baked into every profile, Klaviyo lets brands automatically send the right message at the perfect moment, before a customer slips away, or right when they’re primed to buy again.
This isn’t theory – many merchants, like Willow Tree Boutique, saw a 53% uptick in holiday campaign revenue using these insights.
The power of Klaviyo’s predictive analytics comes from vast data pools: millions of signals from browsing, past purchases, and even timing of previous engagements.
Brands using this system can shift their focus from one-size-fits-all blasts to highly customized flows. Recent reports indicate that Klaviyo customers often see double-digit improvements in email open and click-through rates.
Example 2: Brevo and its Aura multi-agent marketing assistant
Brevo (formerly Sendinblue) has taken a bold step beyond the standard AI add-on by building Aura, a fully integrated suite of intelligent agents embedded across its platform.
Aura is a tightly orchestrated system of AI-powered assistants that simplify marketing, sales, customer service, and data operations.
For any growing brand, it’s like adding a small, brilliant team to your bench without the headcount.
The Marketing agent is a game-changer for campaign creation. It can instantly generate optimized subject lines, rewrite content to better engage specific segments, schedule sends at the right moment, and dynamically recommend products, all in a few clicks.
Meanwhile, the Conversations agent turns customer interactions into efficient, on-brand exchanges. It auto-generates summaries of chat sessions, offers pre-written responses, and refines replies to match your preferred tone, so that every touchpoint feels helpful and human, even at scale.
The Sales and Data Management agents bring the same intelligence to behind-the-scenes workflows. From automatically enriching contact and company profiles to creating deals and reminders, they help sales teams close faster and operate smarter.
Coming features like smart sales sequences and contact imports hint at just how much of the funnel Aura is about to automate.
Best of all? Aura lives right inside the Brevo interface, accessible via chat or embedded directly into campaign tools and sales flows. No matter if you’re launching an email, handling support tickets, or building your next nurture stream, Aura is there, context-aware and ready to assist.
For marketers and revenue teams alike, Aura represents a rare blend of power and simplicity: AI that’s both capable but collaborative. The brands that adopt it are thinking bigger.
Example 3: Shopify and its Sidekick goal-based campaign builder
As for Shopify, meet Sidekick – your AI-powered marketing partner. It helps you build newsletters, segment shoppers, run SMS campaigns, and even suggest products to bulk-send.
And with their “declarative commerce” goal-setting, you can say: “I want to increase summer promo signups”, and Sidekick builds the whole flow. It’s like telling a teammate your target, and letting them run it.
Shopify’s Sidekick offers a hands-on experience: marketers describe a goal in plain language, and the platform suggests tactics, sets up automations, and optimizes creative.
This natural language interface saves teams countless hours in setup and adjustment, while data-driven recommendations often outperform manual tweaks.
Early adopters point to increased efficiency and confidence in campaign planning, even for teams with little technical background.
#3 Intelligent deep search and data analysis
In 2025, search is a prediction engine. Over 60% of shoppers expect it to understand vague queries, and 40% want image-based search. Retailers using AI-powered, multimodal search are seeing double-digit conversion jumps, as smarter discovery drives real revenue.
Example 1: Shopware and its Spatial Commerce discovery toolkit
Shopware goes a step beyond basic search with its contextual and visual discovery, but the real revelation lies in their new Spatial Commerce toolkit.
Customers can now not only search by typing vague phrases like “rainy-day gear for city walks” or upload images, but they can also preview 3D product models in their own environment via AR.
Merchants simply upload GLB-formatted 3D files, and shoppers can place furniture, décor, or other items into their rooms – or scan a QR code on desktop to launch the experience on mobile.
And, it’s converting.
Shopware’s early adopters report 70% fewer returns and 200% higher engagement on pages using AR visualization.
That’s a powerful signal: by letting customers investigate products in realistic settings, retailers alleviate doubts and elevate trust – those are the kinds of micro-interactions that transform browsers into buyers.
Example 2: eBay and its agentic AI shopping assistant
Across the pond, eBay is remaking how people find things.
Their newly launched Agentic AI Shopping Assistant is a standout example of what’s possible when decades of customer insight meet the cutting edge of conversational intelligence.
This intelligent assistant is woven directly into the shopper’s journey, delivering real-time, hyper-personalized product suggestions as users browse the marketplace.
Whether you’re looking for a unique birthday gift, assembling a seasonal wardrobe, or just exploring, the agent anticipates your needs, surfacing curated bundles, tailored deals, and suggestions with minimal effort on your part.
Unlike legacy chatbots that wait for a prompt, eBay’s AI actively guides shoppers, responding to intent signals or stepping in proactively with inline messaging.
This transforms search from a task into an experience. Less clicking, more finding. It’s assistant-led discovery that feels natural, frictionless, and even fun.
What makes this launch especially compelling is the strategic foundation behind it. eBay is pairing agentic AI with nearly 30 years of marketplace data, deep product knowledge, and robust infrastructure.
This is a platform-level shift that enhances personalization, accelerates decision-making, and unlocks new growth opportunities for both buyers and sellers.
And they’re doing it responsibly. Every AI feature, including the shopping assistant, is developed in collaboration with eBay’s Responsible AI team, so there is alignment with core values like transparency and safety.
Chief Technology Officer Mazen Rawashdeh put it best:
“These agentic AI advancements help us better serve our customers with efficiency and a deep understanding of their needs, while positioning eBay at the forefront of the futuristic, agent-powered ecommerce landscape.”
Currently available to a select group of U.S. users, this experience is rolling out gradually, ushering in a new era where AI collaborates. With tools like this, eBay is actively shaping the ecommerce evolution.
Example 3: Nosto and its generative synonym engine
Nosto brings a sharp edge to search and content personalization through its intelligent use of generative AI.
By integrating OpenAI’s large language models with its native commerce experience platform (CXP), Nosto goes far beyond basic enhancements. It creates intuitive, high-performing touchpoints that feel smart and relevant across the board.
At the search level, Nosto’s Generative Synonyms feature automatically expands keyword coverage by blending predictive models with ChatGPT-driven semantics. That means a shopper typing “denim tee” could be seamlessly matched with products labeled “casual jeans shirt” or “relaxed-fit cotton top.”
This seemingly small shift reduces zero-result pages and lifts conversion rates in real time, especially on stores with broad or niche catalogs.
But Nosto doesn’t stop at discovery.
Its generative copy capabilities bring automation and nuance to campaign execution. Using contextual inputs, like recommendation type, page layout, customer segment, and brand vertical, Nosto generates ready-to-use, high-performing recommendation titles. These are linguistically optimized suggestions, personalized to the shopper’s journey and product context.
This isn’t theory, it’s powering results for top retail brands including Dermalogica, Case-Mate, and Volcom, who use Nosto to streamline content workflows and personalize at scale.
Customers report improved translation quality on recommendation titles and higher engagement when A/B testing generative copy versus manual versions.
In short, Nosto’s generative features help brands move faster, sound smarter, and sell better at scale.
#4 Business process & operations automation
Behind the scenes of every order is a web of AI-driven operations that make delivery fast, inventory smarter, and dispute handling nearly invisible. In 2025, the real magic happens backstage.
Example 1: Alibaba International and its Aidge-powered supply chain & dispute automation
Alibaba International is quietly leading one of the most advanced AI transformations in global commerce. At the heart of this evolution is Aidge, its professional-grade AI platform powering everything from dispute resolution to multilingual content creation and visual merchandising.
Aidge is a multi-capability AI ecosystem integrated across Alibaba International’s vast marketplace infrastructure.
Every day, its automated chargeback and refund agents resolve millions of disputes, slashing resolution times from days to minutes. This alone drastically reduces operational costs for over 500,000 merchants, while building trust and transparency on cross-border transactions.
Behind the scenes, Aidge’s supply chain AI constantly adjusts stock levels, routes, and order flows using real-time data. It allows for dynamic, demand-driven logistics on a global scale, giving customers what they need, when they need it, no matter the market.
But what truly sets Aidge apart is its breadth.
It combines LLM-powered translation, image enhancement, and virtual modeling to help merchants launch faster and scale with fewer resources. Product descriptions, titles, and even images can be translated and localized instantly for cultural fluency and increasing conversion by up to 30% in new markets.
Tools like ManekenAI allow sellers to create realistic, customizable virtual models, slashing photoshoot costs while boosting product appeal. Meanwhile, Aidge’s advanced image APIs support cropping, background removal, and upscaling to meet aesthetic standards across all channels.
With over 600 million API calls per day, Aidge is driving measurable impact across Alibaba International’s global platforms, including AliExpress, Lazada, Daraz, Trendyol, and Miravia. The result? A 90% time savings for teams, a 7.7% boost in product click-through rates, and a 2.8% lift in GMV.
Alibaba International isn’t playing catch-up in AI, it’s setting the pace. With Aidge, they’re not only powering seamless shopping experiences but building the infrastructure for the future of borderless, intelligent commerce.
Example 2: Kaufland and its AI demand forecasting engine
Kaufland, one of Europe’s largest hypermarket chains, is redefining large-scale retail planning through a cutting-edge AI partnership with Schwarz IT and SAP.
Their joint implementation of AI-powered demand forecasting and smart pricing systems is turning complexity into clarity, motivating over 1,500 stores across eight countries to make smarter inventory decisions.
At the core is SAP’s Unified Demand Forecast (UDF) module, deployed by Schwarz IT to handle up to 35 million store-product combinations daily.
The system analyzes 800 days of sales history and calculates expected sales for the next 100 days, helping teams anticipate demand with remarkable accuracy.
Thanks to factoring in variables like weather conditions, sales trends, and real-time inventory data, the system dynamically adjusts replenishment and sourcing strategies.
The result? Fewer stockouts, less overstock waste, and tighter margin control during promotions.
This AI-driven agility is especially impactful in managing perishable goods, where spoilage can erode both revenue and customer trust. Kaufland’s new forecasting capability allows for rapid response to shifting demand patterns, no matter if it’s a spike in summer barbecue supplies or a run on winter essentials.
According to Schwarz IT, this transformation is about delivering better service. With AI sharpening the entire replenishment cycle, customers benefit from improved product availability, fresher goods, and more consistent in-store experiences.
Kaufland’s investment proves that AI isn’t a tool for ecommerce giants only but also a powerful lever for brick-and-mortar retailers to modernize their supply chains and future-proof their operations.
#5 Content generation & UX optimization
Top platforms now use AI to co-create, speeding up content, design, and UX decisions. In a space where every detail impacts conversion, AI helps teams build and test landing pages, messaging, and visuals in minutes, boosting both relevance and brand consistency.
Example 1: Optimizely and its Opal AI content & layout engine
Start with Optimizely’s Opal AI – a suite of intelligent agents embedded into their One platform.
It can auto-generate SEO-optimized product descriptions based on attributes like color, size, or material; it can craft email copy, social headlines, and ad variations tuned to test results; it even suggests better UI layouts based on past experiments.
Early users report Opal boosts content output and nails copy performance by suggesting what actually resonates. Digging deeper, Optimizely data show that teams using Opal see a 30% reduction in content creation time, freeing up resources to experiment more and drive innovation.
The system analyzes past test results to propose data-validated campaign ideas, and can generate and assign workflow tasks – including social posts, experiment briefs, and alerts – automatically.
Example 2: AB Tasty and its emotionally intelligent UX personalization
AB Tasty enters the emotional personalization arena with EmotionsAI. Across 60% of tested variants, campaigns that tapped into users’ emotional triggers (safety, curiosity, urgency) produced 5–10% revenue increases, compared to just ~10% for normal A/B tests.
Its Visual Editor also lets marketers quickly tweak images or layouts based on segmented emotional needs – speedy, smart, and surprisingly effective.
AB Tasty’s La Redoute case study underscored the tool’s value: they tripled the success rate of A/B tests, and achieved a 4% boost in revenue per visitor, with conversations rising by 3%. EmotionsAI identifies emotional drivers like competition, safety, or quality, and delivers targeted experiences accordingly, making UX more empathetic and effective.
Final thoughts
What we’ve covered is only a glimpse of how AI is reshaping e-commerce – from personalization and predictive marketing to logistics and content creation.
A recent Quid report shows AI is now a core pillar across nearly all retail functions. As brands shift from pilot projects to full integration, AI will connect experience, operations, and insights into one smart engine. The journey is just the beginning and the biggest opportunities are still ahead.
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