{"id":82237,"date":"2026-10-26T13:11:40","date_gmt":"2026-10-26T12:11:40","guid":{"rendered":"https:\/\/aton.com\/atonews\/service-desk-fashion-retail-ai-gestione-richieste\/"},"modified":"2026-10-27T10:44:07","modified_gmt":"2026-10-27T09:44:07","slug":"service-desk-fashion-retail-ai-request-management","status":"publish","type":"post","link":"https:\/\/aton.com\/en\/atonews\/service-desk-fashion-retail-ai-request-management\/","title":{"rendered":"Service Desk in fashion retail: how AI supports request management"},"content":{"rendered":"<p data-pm-slice=\"1 1 []\"><em>Does a store need to know how to classify an issue before asking for support?<\/em><\/p>\n<p>That was the question we started with on Thursday 22 October during our LinkedIn webinar, <strong>\u201cFashion retail: more time for customers with AI in the Service Desk\u201d<\/strong>.<\/p>\n<p>We followed the journey of a support request, from the initial report through to bringing in the expertise needed to resolve it, exploring <strong>how artificial intelligence can support the different stages of the process<\/strong>.<\/p>\n<p>Among the technologies presented, we focused on two solutions developed by Aton: <strong>AI Call Manager<\/strong> and <strong>Live Call Translator<\/strong>.<\/p>\n<h2><strong>AI Call Manager: gathering information from the very first call<\/strong><\/h2>\n<p>When an operator is not immediately available, <strong>AI Call Manager<\/strong> can start gathering the information needed to handle the request.<\/p>\n<p>By listening to and transcribing the caller\u2019s description of the issue, the system helps <strong>build a clear picture of the problem and its context<\/strong>. Store staff can simply describe what is happening, while the Service Desk starts organising the information needed to handle the request.<\/p>\n<p>This can reduce the initial handling time from under one minute ,our standard, to around <strong>15\u201320 seconds<\/strong>, using the waiting time to prepare the request before an operator takes over.<\/p>\n<h2><strong>Live Call Translator: supporting international retail networks<\/strong><\/h2>\n<p>When a retail network operates across different countries, support requests need to be understood and routed correctly, <strong>regardless of the language spoken by the store team<\/strong>.<\/p>\n<p>Aton\u2019s <strong>Live Call Translator<\/strong>, developed to support the languages required by each customer, is designed to make support requests easier to translate and understand, while also helping with ticket classification and assignment.<\/p>\n<p>The technology complements Aton\u2019s multilingual Service Desk, which already provides support in <strong>14 languages<\/strong>.<\/p>\n<h2><strong>AI in the Service Desk: the Aton model<\/strong><\/h2>\n<p>AI Call Manager and Live Call Translator are part of Aton\u2019s <a href=\"https:\/\/aton.com\/en\/service-desk\/\" target=\"_blank\" rel=\"noopener\">Service Desk<\/a> model, built around a <strong>human-first approach<\/strong>, where technology supports people and their expertise.<\/p>\n<p>Artificial intelligence can support some of the preliminary stages of the process, from gathering information and translation to classification and request routing. Operators can therefore receive <strong>requests that are already contextualised<\/strong> and focus on analysis, decision-making and coordinating the expertise needed to resolve each issue.<\/p>\n<p><strong>People remain at the heart of the service<\/strong>, bringing their experience and judgement, while AI helps simplify day-to-day activities.<\/p>\n<p>During the webinar, we demonstrated this model through <strong>real-life cases, demos and simulations<\/strong>, while also exploring the role of the <strong>knowledge base<\/strong> and coordination across the different levels of support.<\/p>\n<p><span class=\"NormalTextRun SCXW186316928 BCX8\">[<\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW186316928 BCX8\">cta_button<\/span><span class=\"NormalTextRun SCXW186316928 BCX8\"> link=&#8221;https:\/\/aton.com\/en\/contact\/&#8221; label=&#8221;Contact&#8221; size=&#8221;_slim&#8221; target=&#8221;_blank&#8221;]<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Does a store need to know how to classify an issue before asking for support? That was the question we started with on Thursday 22 October during our LinkedIn webinar, \u201cFashion retail: more time for customers with AI in the Service Desk\u201d. We followed the journey of a support request, from the initial report through [&hellip;]<\/p>\n","protected":false},"author":22,"featured_media":82247,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false},"class_list":["post-82237","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","keyword-service-desk-en"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Service Desk in fashion retail: the role of AI - Aton<\/title>\n<meta name=\"description\" content=\"How can AI improve the Service Desk in fashion retail? 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