{"id":458899,"date":"2026-03-12T11:37:50","date_gmt":"2026-03-12T11:37:50","guid":{"rendered":"https:\/\/www.drapersonline.com\/?p=458899"},"modified":"2026-03-16T14:31:08","modified_gmt":"2026-03-16T14:31:08","slug":"why-agentic-ai-is-the-new-must-have-for-ecommerce","status":"publish","type":"post","link":"https:\/\/www.drapersonline.com\/insight\/the-industry-view\/why-agentic-ai-is-the-new-must-have-for-ecommerce","title":{"rendered":"Why agentic AI is the new must-have for ecommerce"},"content":{"rendered":"
\"\"

Aakash Gupta, vice-president, analytics and AI services at data and AI solutions company EXL<\/p>\n\t

<\/p><\/p><\/div>\n

In the high-stakes world of digital fashion retailing, helping customers find the \u201cperfect fit\u201d is not just about sizes and measurements \u2013 it is about the entire shopping experience. Ecommerce is currently navigating a storm of economic volatility, rising service expectations and internal complexity. The pressures of inflation and shifting demand are forcing retail leaders to re-evaluate how they maintain loyalty and profitability.<\/p>\n

While some brands and retailers have reacted with aggressive discounting and absorbed higher fulfilment costs, these are short-term fixes that compress margins.<\/p>\n

Today\u2019s fashion consumers expect hyper-personalised experiences, recommendations that reflect their immediate intent and seamless service. If a website fails to deliver, the customer is gone in a single click, leaving behind another abandoned cart.<\/p>\n

The silo struggle<\/strong><\/p>\n

The barrier to true personalisation is often buried deep within a brand\u2019s own ecosystem. Storefronts, CRM (customer relationship management), marketing and inventory systems frequently live in disconnected silos. This data fragmentation makes coordinated action nearly impossible.<\/p>\n

When product attributes are inconsistent and customer data is unstructured, the dream of the \u201csegment of one\u201d \u2013 a hyper-personalised marketing strategy that treats each customer as a unique market segment, beyond traditional demographic grouping \u2013 remains out of reach.<\/p>\n

Agentic AI is the missing link. Unlike basic algorithms, agentic AI can act on behalf of the user, and be trained to understand nuances such as profit margins, fulfilment constraints and real-time inventory levels.<\/p>\n

Imagine a shopper looking for sustainable linen dresses. Instead of just seeing popular items, an agentic system optimises the display based on the shopper\u2019s past behaviour, current location and the brand\u2019s shipping costs. If the system triggers a dynamic offer for a near-term markdown, it creates a compelling call to action that a competitor simply cannot replicate.<\/p>\n

The AI revolution<\/strong><\/p>\n

Retailers are no longer just flirting with AI \u2013 they are committing to it: 83% of UK retailers name scaling AI as a top priority for 2026, EXL\u2019s Enterprise AI study, which interviewed 190 business leaders across industries, showed.<\/p>\n

The survey also found that 52% have already adopted generative AI in ecommerce and omnichannel settings, while brands prioritising AI in customer experience, pricing and customer care report 22% growth in profitability, and a 48% increase in organisational agility.<\/p>\n

Despite these gains, only 10% of retailers have fully operationalised AI. Many remain stuck in pilot mode, testing isolated features without integrating them properly into a system-wide deployment.<\/p>\n

The UK marketplace case<\/strong><\/p>\n

A leading unnamed UK-based digital marketplace recently proved the power of data fusion.<\/p>\n

By connecting its storefront, inventory and fulfilment data via agentic AI, it moved beyond generic filters.<\/p>\n

The AI learned shopper preferences and recommended full outfits based on specific occasions, ensuring every item was in stock and deliverable. The result? Revenue jumped 50% year on year, while customer complaints dropped by 10%.<\/p>\n

A blueprint for scaling<\/strong><\/p>\n

To move from a basic web store to a self-optimising engine, brands and retailers need a new playbook to overcome siloed platforms and legacy architecture.<\/p>\n

First, they must modernise their foundation by unifying CRM, fulfilment and campaign data into a single cloud-native platform, while also unifying teams, aligning marketing, tech and merchandising around shared metrics such as \u201cpersonalised average order value\u201d.<\/p>\n

Next, they should embed AI everywhere \u2013 not just isolating it in a chat box. Connect it to browsing, pricing and the checkout funnel, and tie AI success to gross margin lift and churn reduction, not just clicks.<\/p>\n

Brands should also be sure to use automated privacy controls to make data security a brand value and build trust.<\/p>\n

Self-improving eco-system<\/strong><\/p>\n

The next generation of shopping will be responsive and intuitive.<\/p>\n

We are moving toward multi-modal search, where shoppers upload a photo of a street-style look and are instantly matched with relevant, shoppable items.<\/p>\n

Conversational agents will guide shoppers from discovery to checkout in a single thread, and in-store intelligence will allow staff to access a customer\u2019s digital style profile the moment they walk through the door.<\/p>\n

Ecommerce leaders are not waiting for the future, they are building it. By connecting signals to outcomes, brands and retailers are already creating self-optimising engines where personalisation is no longer a luxury \u2013 it is the infrastructure of success.<\/p>\n

\n

How retailers are refining the shopping experience<\/strong><\/p>\n

1. Guided shopping and smart search<\/strong><\/p>\n

AI acts as a digital personal shopper, surfacing relevant pieces based on browsing behaviour, return patterns and even regional trends.<\/p>\n

2. Dynamic offers<\/strong><\/p>\n

Pricing engines use real-time demand and stock levels to automate discounts. Expiring inventory can trigger an exclusive promotion for specific shopper cohorts.<\/p>\n

3. Catalogue enrichment<\/strong><\/p>\n

Generative tools create SEO-rich descriptions and localised content in minutes, ensuring a consistent brand voice across thousands of products and SKUs.<\/p>\n

4. Service personalisation<\/strong><\/p>\n

AI bots handle \u201cwhere is my order?\u201d (WISMO) queries with session continuity, offering tailored styling advice or upsells during the conversation.<\/p>\n

5. Creative testing<\/strong><\/p>\n

Marketers can generate hundreds of advertising variants instantly, testing headlines and imagery to see what resonates with shoppers.<\/p>\n<\/div>\n

\n

To find out more about how EXL can help on your agentic AI journey, visit exlservice.com<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

In the high-stakes world of digital fashion retailing, helping customers find the \u201cperfect fit\u201d is not just about sizes and measurements \u2013 it is about the entire shopping experience. Ecommerce is currently navigating a storm of economic volatility, rising service expectations and internal complexity. The pressures of inflation and shifting demand are forcing retail leaders …<\/p>\n","protected":false},"author":2163,"featured_media":458900,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_oasis_is_in_workflow":0,"_oasis_original":0,"ep_exclude_from_search":false,"footnotes":""},"categories":[963,7742,996],"tags":[],"class_list":["post-458899","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-and-tech","category-digital-and-tech-topics","category-the-industry-view","editorial-digital-tech","editorial-ecommerce","editorial-industry-view"],"yoast_head":"\nWhy agentic AI is the new must-have for ecommerce<\/title>\n<meta name=\"description\" content=\"Aakash Gupta, vice-president, analytics and AI services at data and AI solutions company EXL, explains the power of agentic AI.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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