{"id":2165,"date":"2026-07-17T17:39:41","date_gmt":"2026-07-17T17:39:41","guid":{"rendered":"https:\/\/grupotisa.com\/sin-categoria\/customer-experience-with-ai\/"},"modified":"2026-07-17T17:39:41","modified_gmt":"2026-07-17T17:39:41","slug":"customer-experience-with-ai","status":"publish","type":"post","link":"https:\/\/grupotisa.com\/en\/business-central\/customer-experience-with-ai\/","title":{"rendered":"Customer experience with AI: the intelligence layer"},"content":{"rendered":"<p>For years, &quot;knowing the customer&quot; has meant opening five different screens: the ERP on one side, the sales spreadsheet on another, email, the incident history and, with luck, a dashboard that someone updates by hand. <strong>Customer experience with AI<\/strong> starts from a simple idea: bringing together all that scattered knowledge into an intelligence layer over your management system, so that information stops being hidden and starts working for you. It&#8217;s not about adding another tool, but about making better use of the one you already have.<\/p>\n<p>In this article we bring it down to a real SME: what that &quot;intelligence layer&quot; is, why Business Central is a good foundation to build it on, and how to take the first steps without falling for the hype.<\/p>\n<h2>From scattered data to the intelligence layer<\/h2>\n<p>The customer data you need already exists within your company. It&#8217;s in the orders, in the invoices, in the payment terms, in the complaints and in the purchase frequency. The problem isn&#8217;t the lack of data, but that it lives in silos and no one cross-references it in time.<\/p>\n<p>An intelligence layer is, precisely, what joins those sources and turns them into actionable information. It rests on three foundations:<\/p>\n<ul>\n<li><strong>Ordered and governed data.<\/strong> Without quality, access control and clear usage criteria \u2014what we call data governance\u2014, any subsequent analysis inherits the errors from the source.<\/li>\n<li><strong>Analytics that can be understood.<\/strong> Dashboards with Power BI that answer business questions (&quot;which customers are buying less than a year ago?&quot;), not pretty charts with no purpose.<\/li>\n<li><strong>AI applied to a use case.<\/strong> Models that detect patterns, anticipate behaviors or summarize information so that a person can decide better and faster.<\/li>\n<\/ul>\n<p>The order matters: first the data, then the analytics and, on top, the AI. Skipping the foundations is the most common reason why an AI project doesn&#8217;t deliver.<\/p>\n<h2>Customer experience with AI: what really changes<\/h2>\n<p>Here comes the &quot;agentic&quot; nuance that everyone talks about so much. The difference between classic automation and an AI agent is that the agent doesn&#8217;t just respond: it executes multi-step tasks using the business tools. It&#8217;s the leap from a <strong>reactive<\/strong> service (waiting for the customer to call) to a <strong>proactive<\/strong> one (anticipating before the problem arises).<\/p>\n<p>With a well-designed customer experience with AI, your team can go from &quot;looking for the information&quot; to &quot;receiving the context already digested&quot;. Some realistic examples:<\/p>\n<ul>\n<li>Detecting early on a customer whose purchase pattern is dropping, so that sales can act before losing them.<\/li>\n<li>Automatically summarizing a customer&#8217;s history before a call, so that whoever attends arrives with context.<\/li>\n<li>Prioritizing incidents according to their real impact on the relationship, not according to order of arrival.<\/li>\n<li>Suggesting the most likely complementary product or service based on past behavior.<\/li>\n<\/ul>\n<h3>From assistant to agent<\/h3>\n<p>Microsoft is integrating <strong>Copilot<\/strong> within Business Central and the rest of Dynamics 365 to bring these capabilities closer to SMEs.<\/p>\n<h2>Why Business Central is a good foundation<\/h2>\n<p>An intelligence layer needs a good starting point, and there Business Central plays with an advantage. As an ERP it integrates into a single system finance, sales and marketing, purchasing, inventory, projects and <strong>service management<\/strong>. That is: a good part of the customer journey is already recorded in a structured way.<\/p>\n<p>In addition, it is part of an ecosystem that facilitates the rest of the work: native integration with Power BI for analytics, with Power Platform to automate processes and with the Microsoft 365 environment where your team already works every day. Building customer intelligence on data that already lives in your ERP saves costly integrations and reduces the risk of duplicated or contradictory data.<\/p>\n<p>At Tisa we also develop <strong>sector-specific verticals<\/strong> on Business Central \u2014hospitality, distribution, sports centers, point of sale or fleet management\u2014, which allows capturing the specific data of each business from day one.<\/p>\n<h2>How to get started without dying in the attempt<\/h2>\n<p>The transformation doesn&#8217;t happen all at once. This is the path we recommend to an SME that wants to improve its customer experience relying on data and AI:<\/p>\n<ol>\n<li><strong>Put your data in order.<\/strong> Before any AI, define which customer data is relevant and establish some minimum governance rules: who accesses it, how it is updated and with what quality.<\/li>\n<li><strong>Make visible what you already have.<\/strong> A dashboard in Power BI that shows the health of the customer portfolio usually generates immediate value and doesn&#8217;t require AI.<\/li>\n<li><strong>Choose a concrete and measurable use case.<\/strong> Better &quot;reduce the incident resolution time&quot; than &quot;apply AI to the customer&quot;. A clear objective lets you know if the project works.<\/li>\n<li><strong>Pilot, measure and scale.<\/strong> Start small, validate the result with real data and only then expand to other areas.<\/li>\n<\/ol>\n<p>This staged approach \u2014advice, data analysis and, on that basis, an AI use case adapted to the business\u2014 is exactly how we work the intelligence part at Tisa.<\/p>\n<h2>An example by sector<\/h2>\n<p>Imagine a <strong>distribution<\/strong> company with thousands of references and hundreds of customers. The intelligence layer cross-references order history, margins and delivery times to warn which customers are reducing their volume and which products it&#8217;s worth proposing to them. The salesperson no longer reacts: they anticipate. In a <strong>sports center<\/strong>, the same principle helps to detect members at risk of leaving based on their attendance pattern and to activate a retention action in time.<\/p>\n<p>None of these examples requires a pharaonic project. It does require, however, ordered data and a well-chosen use case.<\/p>\n<h2>The next step<\/h2>\n<p>The customer experience of the future doesn&#8217;t depend on having &quot;more AI&quot;, but on turning the data you already generate into better and faster decisions. Business Central gives you the foundation; the intelligence layer and applied AI make the most of it.<\/p>\n<p>At Tisa we have been helping private companies since 1987 to make the most of their technology with good judgment, as a Microsoft partner and developer of custom solutions. If you want to assess where to start in your case, write to us at <strong>info@grupotisa.com<\/strong>, call us at <strong>(+34) 971 305 885<\/strong> or visit <strong><a href=\"https:\/\/grupotisa.com\">grupotisa.com<\/a><\/strong> for a no-obligation assessment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Discover how customer experience with AI on Business Central turns your data into decisions and into proactive service for your SME.<\/p>\n","protected":false},"author":3,"featured_media":2160,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[23],"tags":[80,47,241,202,240,84],"class_list":["post-2165","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-central","tag-artificial-intelligence","tag-business-central","tag-customer-data","tag-customer-experience","tag-customer-insights","tag-digital-transformation"],"yoast_head":"<!-- This site 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