AI Agents: How They Are Transforming the E-Commerce Sector

At present, a sleek website and retargeting ads are not enough for e-commerce brands. As technology is evolving, it has become essential to adapt to automation tools where AI agents won’t just recommend, but act on behalf of your customers. This is the new era, where you can expect AI agents to know the preferences of your customers, get a detailed price comparison sheet in real time, and even handle post-purchase challenges without putting manual effort.

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So yes, 2025 is all about exploring and using the right AI agents to increase your e-commerce sales. After getting a thorough understanding of AI agents that are prevailing in the e-commerce sector, I have compiled everything that you might wonder about. Without further ado, let’s begin.

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What is agentic commerce - A detailed overview

Initially, I wasn’t sure whether using AI agents would be worth it for e-commerce businesses. Then, as I went deeper into its core aspects from both fundamental and technical areas, I found that Agentic commerce is the present, not the future. Unlike traditional recommendation engines and automation tools, these agents are quite context-aware, proactive, and capable of making decisions. 

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Agentic commerce is an evolution where autonomous AI agents perform on behalf of the users/customers to make purchases, manage their preferences, and even handle post-sale tasks without depending on their prompts. So, what does it mean for an e-commerce professional? You need to alter your strategies and start building your business for AI agents. This involves optimizing your product data, APIs, and pricing logic in a way that not only humans but even machines can read them. 

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Thus, your upcoming conversions may not come from a customer, but from their AI agent. These agents would scan your store in milliseconds and pick the best for their user. 

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Difference between e‑commerce agents and bots

At first, e-commerce bots and AI agents look quite similar, but they are very different in reality. They mainly differ in the area of intelligence and autonomy. How? Let me explain. Bots are usually reactive. They have preset rules that help them perform tasks like tracking orders, answering FAQs, or sending reminders. 

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Whereas e-commerce agents are autonomous and designed to achieve business goals. They handle the entire shopping process for a user, from finding the right product to handling exchange/returns without waiting for their input every single time. They learn from users’ shopping behaviour, adapt to their preferences, and then operate proactively. 

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 Bots can help to automate surface-level customer interactions, while agents offer deeper personalization, higher conversions, and even aid in making real-time decisions. 

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Attributes of an e-commerce agent

1. Making autonomous decisions - E-commerce agents operate without depending on the user to search or click. Whether a user wants to reorder a purchase, find the best deal, or handle a return, these agents perform actions in real time. They work using logic-based decision systems and reinforcement learning models. This helps them to act proactively. This can result in conversions initiated by agents rather than direct customer actions. 

2. Goal-based intelligence system -  Like traditional bots, they do not merely execute the required tasks. AI agents for e-commerce are designed to achieve specific goals. For instance, if your customer wants ‘affordable hiking shoes under $200 with fast delivery’, such an agent could potentially explore multiple e-commerce platforms like yours, compare different pricing options, check shipping time, and then choose the best shoes, depending on system integration. This is performed through their AI models that simulate human-like reasoning and ensure that every step brings them closer to achieving the end goal.

‍3. Context-based awareness - Modern e-commerce agents are great at understanding context. Before making any decision, they would consider factors like location, time of day, inventory levels, seasonal trends, and past behaviour. This is achieved through their dynamic data inputs coming from behavioural analytics, APIs, and triggers. This allows agents to deliver deeper personalization features.

‍4. Execute multi-step workflows - An e-commerce agent won’t just ‘add to the cart’, they will perform all the actions that are involved in the shopping journey. Also, they would leave reviews as well. This technically works with the help of agentic orchestration frameworks that usually connect different services with function routing and API chaining. With this, agents are able to fully handle customer journeys just like a human assistant. 

‍5. Optimize and quickly adapt  - The more you work with AI agents, the smarter they become with time. It quickly learns which brand a particular user trusts, what features and price they usually consider, which pattern they follow to respond to delays, and also when to hold back or upsell (for businesses). How does this work? This learning pattern is embedded directly into the agent’s LLM-based memory architecture or neural models. This ensures that next actions are well-optimized and efficient. 

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How can shoppers use AI Agents?

AI agents are already making the modern shopping experience seamless. Here’s how they benefit the customers. 

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• Goal-based shopping  - To avoid endless scrolling on shopping websites, AI agents simply consider purchase goals like ‘Find me a high-protein shake under $30 with fast shipping’. And then, it handles everything from search to checkout process. 

• Compare prices and optimize deals in real-time - AI agents are programmed to scan various retailers, apply time-based purchases and discounts based on dynamic pricing. This helps customers grab the best deal without spending extra time and effort. 

• Automates the reordering process - Many customers are using AI agents to keep a check on product usage patterns. These agents also help them reorder frequently purchased items like personal care products, household supplies, or groceries automatically (without any manual intervention). 

• Tracks order and manages post-purchase process - AI agents track order deliveries in real time, handle product returns or refunds, and also send proactive updates. This minimizes customer effort and chaos in the shopping journey. 

• Personalizes the product discovery stage - AI agents make use of user preferences and behavioural data. They even recommend highly relevant products based on their users' needs, lifestyle, and budgets. This way, they make suggestions more precisely. 

• Manage subscriptions - Agents in the e-commerce industry perform tasks like cancelling underused services, managing renewals, and even switching to better-paid plans, as required. This helps customers to control their recurring expenses in a more organized way. 

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How can merchandising teams adapt to AI agents?

AI agents have become an important part of merchandising teams. They help e-commerce business owners to grow with ease. These AI agents automate repetitive tasks and thus allow businesses to focus on strategic work.  The following are some of the ways they benefit merchandisers:

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1. Sort and automate the product categorization process - AI agents help to scan product titles and descriptions. They even categorize SKUs across different channels automatically. With this, the catalogs are properly maintained, manual tagging errors are gradually reduced, and onboarding becomes smoother. This is especially beneficial for businesses dealing in FMCG products. 

2. Helps to optimize inventory - After analyzing regional demand, seasonality and sales velocity, these AI agents recommend redistribution of inventory or predict stock refill (with proper data). This can help avoid the possibility of overstocking or stockouts and help increase profits and enhance customer experience.

‍3. Analyse competitors and their pricing patterns - E-commerce agents keep a check on competitors' pricing, demand patterns and historical sales data in real time and accordingly suggest best price points. As a merchandiser, you can stay updated with competitive pricing without constantly performing manual research. You can even modify pricing strategies as per the shift in the current market. 

• Personalize product bundling - Agents often use trends and purchase behaviour to recommend better product bundles or suggest cross-selling opportunities. You can thus use this to increase your AOV (Average Order Value) and improve the perceived value of the customers without much guesswork. 

• Improve visual merchandising - You can make use of AI agents to find out which products should be placed in premium positions like category highlights or homepage banners. They analyze performance data such as conversions, CTR, and scroll depth, and then suggest accordingly.

• Forecast future performance and trends - AI agents help to find upcoming social trends, change in customer behaviour and demand, and then suggest products that can bring profits.  This can help you build a merchandising process instead of reactive restocking.

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How are AI agents transforming the current e-commerce industry?

• Shifting from user to agent-driven commerce - AI agents are creating a shift from user to agent-based commerce. They simply do this taking responsibility for the complete buyer’s journey, which includes everything from browsing products to purchasing them. This way, they are shopping on behalf of users. 

• Helping businesses optimize for AI buyers - With the help of agentic systems, businesses are able to optimize their product data and storefront for both humans and AI buyers. Apart from this, they are learning to prioritize machine-readable content, real-time availability, and structured metadata.

• Improving backend automation - To handle inventory to pricing structures, AI agents are strategically embedded into the internal business workflows. This leads to an increase in speed and responsiveness.

• Making data-based decisions - AI agents can simply process large datasets in real-time. This helps businesses to swiftly optimize their product placement, visibility, and pricing effectively. 

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How are AI agents solving e-commerce challenges?   

• Helps to avoid decision fatigue - AI agents have started recommending only what is highly relevant to the user. This way, it helps to narrow down the choices and improve satisfaction. This even helps businesses improve their sales. 

• Aids in reducing cart abandonment rates - Agentic systems complete purchases without asking for manual inputs. They even send reminders and smartly apply discounts. This helps reduce drop-offs and friction.

• Helps to increase customer retention - AI agents help deliver a personalized shopping experience across different repeat cycles. This can help brands swiftly move from acquisition-heavy models to relationship-driven growth. 

• Assist in managing rising operational and ad costs - Agentic systems do not heavily depend on paid ads or manual merchandising. They would rather automate product search and backend operations. This can help in optimizing margins. 

• Helps to solve post-sale issues - AI agents handle refunds, returns, and warranty claims with minimal human effort. This gradually reduces support loads and improves customer trust. 

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How are AI agents elevating the shopping experience? 

1. Offer intent-based product search - AI agents engage with shoppers and help them find the best product. Users just need to type in the prompt and mention their goal. For instance, a shopper may say ‘Find me a glowing sunscreen under $30. This should suit oily skin.’ The agent will not just interpret these words but focus on the intent behind them. 

2. Hyper-personalizes the journey with great memory - Agentic systems operate with their great contextual memory. With every interaction with a user, they learn and adapt with time. These systems minutely remember your preferences for fabric, delivery time frame, or a particular size or your favourite colour. This level of personalization can impact customer retention rate and also cart value. 

3. Proactively engages with shoppers - Agentic systems don’t wait for input; instead, they predict needs. From sending reminders related to the product launch or restock to suggesting complementary products based on past purchases, they keep on sending notifications to the user. This can help to increase the frequency of orders and your brand value at the same time. 

4. Provides 24x7 support - Shoppers don’t have to waste time reading or navigating boring FAQs. AI agents are enough for that. They provide 24/7 assistance across all platforms. Whether you need help in solving order issues or require a better understanding of purchase policies or styling tips, these systems are designed in a way that can cater to all their queries seamlessly. If you are in the D2C sector, this will help gradually reduce dependency on large support teams and simultaneously improve CSAT scores. 

5. Smoothly offer post-purchase support - AI agents do not stop at checkout. They would keep updating you on your order returns, refunds, and replacements, if any. Also, if you want, they will add reviews and send reminders for warranty claims. This way, they make the after-sales phase more systematic and seamless.

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Applications of AI agents in e-commerce (business cases)

1. Retail and fashion industry - AI agents can help users find products based on their preferences in real time. They would also keep a check on trending styles, past returns, fit size, and fabric material. These systems can recommend full outfits that are in stock and match your style. This can help you cut down on cart abandonment and increase the average order value as a business person. 

2. Beauty and skincare sector - Agentic systems suggest hair and skin care routines, based on the compatibility of ingredients used in products. They learn and adapt with feedback. Apart from that, they can even automate sample selections during the checkout phase and notify your customers when their serums or moisturizers are running low. This can help to build a loyal community.

3.. FMCG and grocery area - Based on the diet goals, shopping habits, and household size, AI agents can simply auto-create grocery lists and optimize them as per changing seasons and deals. For businesses, these agents can simply track purchase cycles and provide suggestions before you run out of stock. This will reduce food wastage and rotate pantry staples in a systematic manner.

4. Electronics and gadgets area - Without putting manual efforts, AI agents help compare specs, compatibility, price drops, and warranty policies. They track tech launches and notify shoppers when certain products are on sale. They also suggest add-on accessories like chargers and protection plans. 

5.Home and lifestyle sector - AI agents help to find products. They consider the decor style, wishlist, and past purchases of a customer. Also, these agentic systems can guide users through the entire product setup process, troubleshooting, and the steps to book service visits. Shoppers can get all this without depending completely on human intervention.

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Steps to get started with AI agents in e-commerce 

1. Identify the gaps in your present e-commerce setup - You first need to audit your present workflow and analyze your inventory management system, customer service, marketing, logistics, and product discovery area with personalization. After getting a thorough understanding of these aspects, identify the core gap. This is where the AI agents will come into the picture. 

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2. Define the role of your AI agent - All AI agents do not cater to the same issues. Based on your main goal, you need to find the right AI agent. For example, you can choose customer-facing agents, backend optimization agents, or marketing agents depending on your needs. Remember, the choice of agents will directly affect your training, data, tooling, and other integrations. 

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3. Organize your business data  -  To get better results from AI agents, keep your data clean and readable for them. So, make sure you keep your data clean before connecting these agents to your business workflow. It includes your customer support tickets, product catalogs, user interaction data, and sales history. Without writing a line of code, tools like Boltic can help you collect all your business data across CRM systems, marketplaces, and applications. 

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4. Pick your AI agent framework - Based on your tech bandwidth and client needs, you can customize your AI agents with LangChain, OpenAI, or Pinecone (if you have a technical team). In case you are from a non-technical background, you can use pre-built solutions offered by platforms like Boltic.

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5. Test AI agents with limited use-cases - You don’t need to go live on day 1 itself. Instead, start with one agent in a low-risk business environment. You can use it for solving FAQs on a product page, recommending products based on the browsing behaviour of your customers, and automating email replies for your customers (related to their order status). Based on their performance, measure KPIs like bounce rates, response time, and an increase in conversion rates. 

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6. Scale and automate your workflow - Once your AI agent performs well in a low-risk environment, you can start trusting it and increase its access to more user data, and integrate it across different touchpoints like WhatsApp, emails, live chat; and even delegate complex tasks like answering queries related to loyalty programs, managing to upsell or cross-sell flows, etc. Boltic can help you continuously sync data across your sales channels to your AI agent in real time. 

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7. Train agents and monitor the progress - Your AI agents will not work consistently if you do not train and modify their actions. So, you need to keep on retraining them on new queries, updating all your knowledge bases, monitoring your feedback loops and improving your prompts and fallback logic. A/B testing is required to identify which sequence, tone and logic works the best for your team and customers. 

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Will agentic commerce completely replace traditional e-commerce? 

No, agentic commerce won’t completely replace traditional e-commerce. Instead, it would reshape the industry along with it. What does it mean? Both will co-exist and complement each other.

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At present, AI agents are already changing the way customers interact with online stores and handle their end-to-end buying journey. From repeat purchases, subscription renewals, price comparisons, to finding the right product, they take complete charge of everything. For tasks that require data, routine or consistent speed, I found that agentic commerce is more efficient as compared to manual browsing. How? They are frictionless with better intelligence. So, they are preferred mostly by busy individuals who often value convenience over a manual shopping experience. 

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On the other hand, traditional e-commerce is not fading anytime soon, but evolving with time. It will still remain important in categories where purchase decisions are either experiential or emotional. It includes areas like beauty, fashion, and luxury etc.  Customers still crave storytelling, inspiration, and the little joy of discovery that agentic systems cannot provide yet. 

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For e-commerce businesses, this doesn’t mean that you need to abandon your storefronts. It simply means building business for both humans and agents. Your product pages must be optimized not only for maintaining visual appeal, but also for machine readability. Also, your catalogs should have structured data, real-time pricing, and clean APIs for agents.