AI Helps You Remember. It Doesn’t Help You Matter.: Dilpreet Singh, ITC Hotels, on Loyalty’s AI Problem \u2013 NervNow<\/title>\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Source+Serif+4:ital,opsz,wght@0,8..60,400;0,8..60,500;0,8..60,600;0,8..60,700;1,8..60,400;1,8..60,500;1,8..60,600&family=Source+Sans+3:wght@400;500;600&display=swap\" rel=\"stylesheet\" \/>\n<style>\n :root {\n --navy: #182a4f;\n --navy-faint: #e8edf5;\n --gold: #a87830;\n --gold-light: #d4a355;\n --off-white: #f8f7f4;\n --ink: #111111;\n --body: #222222;\n --mid: #444444;\n --rule: #d0ccc4;\n }\n\n *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }\n\n html { overflow-x: hidden; max-width: 100%; }\n\n body {\n background: var(--off-white);\n color: var(--body);\n font-family: 'Source Serif 4', Georgia, serif;\n font-weight: 400;\n line-height: 1.75;\n -webkit-font-smoothing: antialiased;\n hyphens: none;\n -webkit-hyphens: none;\n max-width: 100%;\n overflow-x: hidden;\n }\n\n \/* CATEGORY STRIP *\/\n .category-strip {\n border-top: 3px solid var(--navy);\n border-bottom: 1px solid var(--rule);\n padding: 10px 40px;\n display: flex;\n align-items: center;\n gap: 10px;\n font-family: 'Source Sans 3', sans-serif;\n font-size: 11px;\n letter-spacing: 0.12em;\n text-transform: uppercase;\n font-weight: 600;\n color: var(--mid);\n flex-wrap: wrap;\n }\n .category-strip .tag {\n background: var(--navy);\n color: #fff;\n padding: 3px 10px;\n border-radius: 2px;\n font-size: 10px;\n white-space: nowrap;\n }\n .category-strip .sep { color: #bbb; 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text-decoration: none; }\n\n \/* RESPONSIVE *\/\n @media (max-width: 640px) {\n .category-strip { padding: 10px 20px; font-size: 10px; }\n .hero { padding: 36px 20px 32px; }\n .hero h1 { font-size: 24px; }\n .hero-subtitle { font-size: 16px; }\n .profile-wrap { padding: 0 20px; }\n .profile-card { grid-template-columns: 1fr; }\n .profile-initial { display: none; }\n .body-wrap { padding: 36px 20px 56px; }\n .intro-text { font-size: 17px; }\n .q-text { font-size: 18px; }\n .a-text { font-size: 16px; }\n .pull-quote p { font-size: 18px; }\n .seo-links a { font-size: 16px; }\n .page-footer { padding: 18px 20px; }\n }\n\n @media (max-width: 380px) {\n .hero h1 { font-size: 21px; }\n .intro-text { font-size: 16px; }\n .q-text { font-size: 17px; }\n }\n\n * { min-width: 0; }\n img, video, iframe { max-width: 100%; height: auto; }\n @media (max-width: 640px) {\n .hero-inner,\n .profile-card,\n .body-wrap,\n .seo-links,\n .pull-quote,\n .qa-block {\n max-width: 100%;\n width: 100%;\n }\n .q-text,\n .a-text,\n .intro-text,\n .pull-quote p,\n .profile-bio,\n .hero h1,\n .hero-subtitle {\n word-break: normal;\n overflow-wrap: normal;\n hyphens: none;\n -webkit-hyphens: none;\n }\n }\n<\/style>\n<\/head>\n<body>\n\n<div class=\"category-strip\">\n <span class=\"tag\">Interview<\/span>\n <span class=\"sep\">\u203a<\/span>\n <span>AI in Loyalty<\/span>\n <span class=\"sep\">\u203a<\/span>\n <span>Enterprise CRM<\/span>\n<\/div>\n\n<section class=\"hero\">\n <div class=\"hero-inner\">\n <p class=\"hero-eyebrow\">NervNow Interview Series<\/p>\n <h1>AI Helps You <em>Remember.<\/em> It Doesn’t Help You Matter.<\/h1>\n <p class=\"hero-subtitle\">Dilpreet Singh, Head of Loyalty, CRM, and Partnerships at ITC Hotels, spoke with NervNow about where AI genuinely fits inside the loyalty stack, why most Indian enterprises are still congratulating themselves at the starting line, how hospitality brands can protect emotional connection at scale, and why redemption rates are one of the most misread signals in the industry.<\/p>\n <div class=\"hero-meta\">\n <div class=\"hero-meta-author\">\n <div class=\"author-avatar\">NN<\/div>\n <div class=\"author-info\">\n <strong>NervNow Editorial<\/strong>\n <span>May 2026<\/span>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n\n<div class=\"profile-wrap\">\n <div class=\"profile-card\">\n <div class=\"profile-initial\">D<\/div>\n <div>\n <div class=\"profile-name\">Dilpreet Singh<\/div>\n <div class=\"profile-title\">Head, Loyalty, CRM & Partnerships · ITC Hotels Limited<\/div>\n <p class=\"profile-bio\">Dilpreet Singh leads Loyalty, CRM, and Partnerships at ITC Hotels, where he oversees the technology platform and engagement framework underpinning the company’s retention and loyalty programs. His two-decade career spans financial services, quick service restaurants, and luxury hospitality, with tenures at American Express, Jubilant Food Works (Domino’s India), The Smile Group, and The Oberoi Group, where he served as Head of CRM, Loyalty, and Customer Analytics. He is a certified Loyalty Marketing Professional from The Loyalty Academy and was named a Top 30 Under 40 Loyalty Professional by Loyalty Magazine UK in 2020.<\/p>\n <\/div>\n <\/div>\n<\/div>\n\n<main class=\"body-wrap\">\n\n <p class=\"intro-text\">Dilpreet Singh has spent two decades building loyalty infrastructure across three industries that have almost nothing in common except the problem at the center: how do you make a customer come back? From American Express to Domino’s India to The Oberoi Group to ITC Hotels, he has operated at the intersection of CRM, martech, and customer analytics through several generations of technology change. NervNow spoke with him about where AI actually fits into the loyalty stack today, why most enterprises are still at the starting line, how hospitality brands can protect emotional warmth at scale, and why unredeemed points are one of the most misread signals in the industry.<\/p>\n\n <div class=\"section-label\">AI in the Loyalty Stack<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have spent two decades building loyalty infrastructure across financial services, quick service restaurants, and luxury hospitality. In that time, the underlying data architecture has changed significantly. Where does AI actually fit into the loyalty stack today, and where is it still overpromised?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>There has been a lot of noise about AI across every domain, but let us be honest: AI is not a magic wand and it is not an external layer you bolt on. It is the ability to simplify complex decisions using data and technology, complementing human thinking rather than replacing it. I look at it through a very simple lens. AI helps you remember and respond. It does not help you matter.<\/p>\n <p>As customers, we do not get attached to brands because they remembered our last purchase. We stay because the overall experience feels worth coming back to. So AI’s real role sits in what I call the 3R layer: remember what the customer does, recommend what might make sense next, and respond at the right moment.<\/p>\n <p>Where it is overpromised is when we expect it to build loyalty. Loyalty lives in a different layer entirely, one driven by value, consistency, and trust. If that layer is weak, AI just helps you execute faster. Not better. I do not see AI as the hero. It enhances what is already there. If the foundation is weak, enhancement does not fix it.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>AI helps you remember and respond. It does not help you matter. Loyalty lives in a different layer entirely, one driven by value, consistency, and trust.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have led multiple large-scale CRM and CDP implementations, including AI-powered analytics layers. What does the gap between a vendor’s AI pitch and production reality actually look like, and what does it cost enterprises that miss it?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>The gap is not in AI. It is in an organization’s readiness to absorb AI. And the unfortunate truth is that most brands are not even clear on what they want from it.<\/p>\n <p>The issue starts with the foundation. Most vendor conversations assume a clean world: unified data, aligned teams, clear use cases. Real organizations are far from that. The stepping stone for any organization is what I think of as a 4C Readiness framework: Clean, Connected, Contextual, Committed. Data needs to be clean. Systems need to be connected. Data needs context, not just volume. And teams need to be committed to actually using the outputs.<\/p>\n <p>The biggest cost is not financial. It is cultural. Once teams lose trust in AI-generated outputs, adoption dies. The real work is unglamorous and happens entirely at the backend: fixing data, aligning teams, defining problems clearly. AI is the easy part. Getting the organization ready for it is the real challenge.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Personalization and Emotional Experience<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">Hospitality loyalty is fundamentally about emotional connection, not points. When you introduce AI-driven personalization at scale, is there a risk that guests start to feel the warmth is manufactured? How do you design against that?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Absolutely, and customers are perceptive enough to sense it immediately. There is a meaningful difference between being known and being processed.<\/p>\n <p>Imagine walking into a hotel where everything feels perfectly tailored but slightly mechanical. You know you are being handled by a system. But when a small, imperfect, human moment happens, when someone remembers something casually and without a script, it feels real. That is the distinction that matters.<\/p>\n <p>The concept I keep coming back to is what I call invisible intelligence. If the intelligence is visible, the experience weakens. AI should work in the background, enabling people to deliver better moments, not replacing those moments. Hospitality is not about accuracy. It is about how an experience made you feel. Feelings do not come from perfect targeting. They come from genuine, well-timed human interaction that happens to be supported by insight underneath.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>If the intelligence is visible, the experience weakens. AI should work in the background, enabling people to deliver better moments, not replacing those moments.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Data Readiness in India<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">In a previous role, you built a master database capable of fetching data across more than 200 scenarios in a single pull. That kind of data architecture is a prerequisite for serious AI deployment. In your experience, how many Indian enterprises are actually AI-ready at the data layer, and what does readiness look like in practice?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Honestly, the number is almost beside the point, because almost every organization believes it has arrived at AI readiness. The reality is that most are still congratulating themselves at the starting line. Most are in what I call the Data Illusion Stage: they have a lot of data, so they assume they are ready.<\/p>\n <p>Readiness is not about data volume. It is about decision speed, agility, and clarity. Brands need to assess their data layer across three parameters: access, accuracy, and actionability. Can teams access the data easily? Is it accurate and consistent? Can you act on it quickly?<\/p>\n <p>If a simple customer question takes multiple teams and several days to answer, AI will not fix that. When we built large data systems, the real objective was always to reduce the distance between signal and action. Organizations succeed when they focus on connecting their data rather than collecting it.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Measurement and Attribution<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have overseen campaigns generating over 100 crore in incremental revenue through targeted, data-driven execution. As generative AI enters campaign orchestration, how do you think about measurement differently? Does attribution logic need to change when AI is co-authoring the campaign?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Customer behavior has never been linear. Brands have just forced it into linear models. As customers, we do not respond to a single message. It is always a combination: timing, context, mood, previous experiences. All of it becomes part of the decision.<\/p>\n <p>So attribution, as we have traditionally understood it, is an oversimplification. I prefer thinking in terms of decision influence systems rather than attribution models. It is not about what caused the action. It is about what combination enabled it.<\/p>\n <p>With AI now shaping content, timing, and targeting simultaneously, the need to shift becomes even more urgent. We need to move from credit-seeking to understanding-seeking, from last touch to full journey context, and from a funnel mentality to a flywheel one. Today AI is not just executing campaigns. It is co-creating the path. You cannot measure a journey with a single checkpoint.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Redemption and Program Health<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">The loyalty industry has historically struggled with one persistent problem: members earn points and never redeem, which looks good on the balance sheet but may signal disengagement. Can AI solve this, or does it simply make the obfuscation more sophisticated?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Unredeemed points are one of the most misunderstood signals in the industry. From a business lens, they look positive. From a customer lens, they often mean the member did not find it worth engaging. No brand wants to hear that.<\/p>\n <p>Redemption is a function of three things: value, simplicity, and timing. Is the reward worth it? Is the process easy? Is the offer relevant right now? AI can help with timing and nudges. It can simplify discovery. But it cannot create perceived value. If the reward does not excite the member or feels complicated to access, no volume of reminders will change behavior.<\/p>\n <p>AI does not solve the underlying problem. It intensifies whatever already exists. If the program is strong, AI scales engagement. If the program is weak, AI scales indifference.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>AI does not solve the underlying problem. It intensifies whatever already exists. If the program is strong, AI scales engagement. If the program is weak, AI scales indifference.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Organizational Alignment<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You operate at the intersection of CRM, partnerships, and martech: three functions that often sit in different technology stacks with different owners. How does AI change the organizational question, not just the technology question, for enterprises trying to unify these?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>AI brings one uncomfortable truth to the surface: the customer experiences your organization as one entity, but you operate as many. Earlier, silos could survive because systems were slower and less connected. AI removes that buffer.<\/p>\n <p>The simplest lens here is one customer, one memory, one experience. If different teams hold different versions of the same customer, AI will expose it quickly through inconsistent messaging, broken journeys, or irrelevant offers.<\/p>\n <p>So the shift required is not purely technological. It is cultural. Organizations need to move from ownership of tools to ownership of journeys, and from measuring department success to measuring customer success. In my experience, alignment across people unlocks far more value than any AI model.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Regional Players vs. Global Scale<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">Regional luxury hospitality players compete with international chains that have dramatically larger data pools. When a global operator can train models on tens of millions of transactions worldwide, how does a regional player use AI in a way that is differentiated rather than derivative?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Global players win on scale of data. Regional players can win on depth of understanding. As a guest, what matters is not how much you are known, but how well you are understood in that moment. I think of this as context advantage.<\/p>\n <p>A global system may know your travel frequency. A regional player might know you are traveling for a family occasion, and that changes expectations entirely. AI performs best when data carries meaning, not just volume. So instead of chasing scale, regional brands should focus on context, culture, and occasion.<\/p>\n <p>In hospitality, relevance always beats reach.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Closing Thought<\/div>\n\n <div class=\"qa-block\">\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>For me, loyalty and CRM are not tech constructs. They come down to a very simple human question: did this brand make my life easier or better in any meaningful way?<\/p>\n <p>Everything else, AI, data, platforms, is just infrastructure. Because in the end, customers do not stay because you know them well. They stay because you used that understanding wisely.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"disclaimer\">\n <strong>Disclaimer:<\/strong> The views expressed in this interview are personal to Dilpreet Singh and do not represent the positions of ITC Hotels or NervNow.\n <\/div>\n\n \n <div class=\"seo-section\">\n <div class=\"seo-section-label\">Do Not Miss These Interviews<\/div>\n <ul class=\"seo-links\">\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/linkedins-guna-grace-on-indias-enterprise-ai-gap-deep-at-the-top-of-the-funnel-shallow-everywhere-else\/\" target=\"_blank\" rel=\"noopener\">\n LinkedIn’s Guna Grace on India’s Enterprise AI Gap: Deep at the Top of the Funnel, Shallow Everywhere Else\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/ekgaons-vijay-pratap-singh-on-indias-agri-paradox-data-and-ai-exist-intent-doesnt\/\" target=\"_blank\" rel=\"noopener\">\n Ekgaon’s Vijay Pratap Singh on India’s Agri Paradox: Data and AI Exist, Intent Doesn’t\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/georg-langlotz-ubs-india-does-not-have-an-ai-talent-problem-it-has-an-ai-ambition-problem\/\" target=\"_blank\" rel=\"noopener\">\n Georg Langlotz, UBS: India Does Not Have an AI Talent Problem, It Has an AI Ambition Problem\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/sportsedtv-ceo-victor-bergonzoli-on-how-ai-is-turning-athlete-data-into-a-financial-risk-model\/\" target=\"_blank\" rel=\"noopener\">\n SportsEdTV CEO Victor Bergonzoli on How AI Is Turning Athlete Data Into a Financial Risk Model\n <\/a>\n <\/li>\n <\/ul>\n <\/div>\n\n \n <div class=\"sources-section\">\n <div class=\"sources-label\">Sources<\/div>\n <ol class=\"sources-list\">\n <li>ITC Hotels, Loyalty and CRM division. Available at itchotels.com.<\/li>\n <li>The Loyalty Academy, Certified Loyalty Marketing Professional program.<\/li>\n <li>Loyalty Magazine UK, Top 30 Under 40 Loyalty Professionals, 2020.<\/li>\n <\/ol>\n <\/div>\n\n <p class=\"footer-note\">This interview was conducted by NervNow. All responses are reproduced from Dilpreet Singh’s submissions and have been lightly edited for formatting only. No responses have been altered in substance. The views expressed are personal to the interviewee and do not represent the positions of ITC Hotels or NervNow.<\/p>\n\n<\/main>\n\n<footer class=\"page-footer\">\n © 2026 <a href=\"https:\/\/nervnow.com\/ro\/\">NervNow<\/a> All rights reserved\n<\/footer>\n\n<\/body>\n<\/html>","protected":false},"excerpt":{"rendered":"<p>Dilpreet Singh of ITC Hotels explains where AI truly fits in loyalty and CRM, why most Indian enterprises are still not data-ready, and how hospitality brands can use AI to enhance personalization without losing emotional connection.<\/p>","protected":false},"author":5,"featured_media":7136,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[106,95,107],"tags":[123],"class_list":["post-7134","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analysis-ai-technology","category-analysis","category-analysis-marketing-advertising","tag-interview"],"blocksy_meta":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/comments?post=7134"}],"version-history":[{"count":5,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134\/revisions"}],"predecessor-version":[{"id":7144,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134\/revisions\/7144"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/media\/7136"}],"wp:attachment":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/media?parent=7134"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/categories?post=7134"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/tags?post=7134"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":7134,"date":"2026-05-11T15:57:46","date_gmt":"2026-05-11T10:27:46","guid":{"rendered":"https:\/\/nervnow.com\/?p=7134"},"modified":"2026-05-11T16:07:52","modified_gmt":"2026-05-11T10:37:52","slug":"enhancement-does-not-fix-a-weak-foundation-dilpreet-singh-itc-hotels-on-ai-loyalty","status":"publish","type":"post","link":"https:\/\/nervnow.com\/ro\/enhancement-does-not-fix-a-weak-foundation-dilpreet-singh-itc-hotels-on-ai-loyalty\/","title":{"rendered":"Enhancement Does Not Fix a Weak Foundation: Dilpreet Singh, ITC Hotels, on AI & Loyalty"},"content":{"rendered":"\n\n\n\n\nAI Helps You Remember. It Doesn’t Help You Matter.: Dilpreet Singh, ITC Hotels, on Loyalty’s AI Problem \u2013 NervNow<\/title>\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Source+Serif+4:ital,opsz,wght@0,8..60,400;0,8..60,500;0,8..60,600;0,8..60,700;1,8..60,400;1,8..60,500;1,8..60,600&family=Source+Sans+3:wght@400;500;600&display=swap\" rel=\"stylesheet\" \/>\n<style>\n :root {\n --navy: #182a4f;\n --navy-faint: #e8edf5;\n --gold: #a87830;\n --gold-light: #d4a355;\n --off-white: #f8f7f4;\n --ink: #111111;\n --body: #222222;\n --mid: #444444;\n --rule: #d0ccc4;\n }\n\n *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }\n\n html { overflow-x: hidden; max-width: 100%; }\n\n body {\n background: var(--off-white);\n color: var(--body);\n font-family: 'Source Serif 4', Georgia, serif;\n font-weight: 400;\n line-height: 1.75;\n -webkit-font-smoothing: antialiased;\n hyphens: none;\n -webkit-hyphens: none;\n max-width: 100%;\n overflow-x: hidden;\n }\n\n \/* CATEGORY STRIP *\/\n .category-strip {\n border-top: 3px solid var(--navy);\n border-bottom: 1px solid var(--rule);\n padding: 10px 40px;\n display: flex;\n align-items: center;\n gap: 10px;\n font-family: 'Source Sans 3', sans-serif;\n font-size: 11px;\n letter-spacing: 0.12em;\n text-transform: uppercase;\n font-weight: 600;\n color: var(--mid);\n flex-wrap: wrap;\n }\n .category-strip .tag {\n background: var(--navy);\n color: #fff;\n padding: 3px 10px;\n border-radius: 2px;\n font-size: 10px;\n white-space: nowrap;\n }\n .category-strip .sep { color: #bbb; 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}\n .seo-links a {\n font-family: 'Source Serif 4', Georgia, serif;\n font-size: 17px;\n font-weight: 500;\n color: var(--navy);\n text-decoration: none;\n line-height: 1.45;\n display: block;\n overflow-wrap: normal;\n }\n .seo-links a:hover {\n color: var(--gold);\n text-decoration: underline;\n }\n\n \/* Sources *\/\n .sources-section {\n margin-top: 52px;\n padding-top: 24px;\n border-top: 1px solid var(--rule);\n }\n .sources-label {\n font-family: 'Source Sans 3', sans-serif;\n font-size: 10px;\n letter-spacing: 0.26em;\n text-transform: uppercase;\n font-weight: 700;\n color: var(--navy);\n margin-bottom: 14px;\n }\n .sources-list {\n padding-left: 18px;\n font-family: 'Source Sans 3', sans-serif;\n font-size: 13px;\n color: var(--mid);\n line-height: 1.8;\n }\n\n \/* Footer note *\/\n .footer-note {\n border-top: 1px solid var(--rule);\n padding-top: 28px;\n margin-top: 50px;\n font-family: 'Source Serif 4', Georgia, serif;\n font-size: 13px;\n color: var(--mid);\n font-style: italic;\n line-height: 1.72;\n font-weight: 400;\n }\n\n \/* Page footer *\/\n .page-footer {\n background: var(--navy);\n color: rgba(255,255,255,0.55);\n text-align: center;\n font-family: 'Source Sans 3', sans-serif;\n font-size: 12px;\n letter-spacing: 0.1em;\n padding: 22px 40px;\n text-transform: uppercase;\n font-weight: 500;\n }\n .page-footer a { color: var(--gold-light); text-decoration: none; }\n\n \/* RESPONSIVE *\/\n @media (max-width: 640px) {\n .category-strip { padding: 10px 20px; font-size: 10px; }\n .hero { padding: 36px 20px 32px; }\n .hero h1 { font-size: 24px; }\n .hero-subtitle { font-size: 16px; }\n .profile-wrap { padding: 0 20px; }\n .profile-card { grid-template-columns: 1fr; }\n .profile-initial { display: none; }\n .body-wrap { padding: 36px 20px 56px; }\n .intro-text { font-size: 17px; }\n .q-text { font-size: 18px; }\n .a-text { font-size: 16px; }\n .pull-quote p { font-size: 18px; }\n .seo-links a { font-size: 16px; }\n .page-footer { padding: 18px 20px; }\n }\n\n @media (max-width: 380px) {\n .hero h1 { font-size: 21px; }\n .intro-text { font-size: 16px; }\n .q-text { font-size: 17px; }\n }\n\n * { min-width: 0; }\n img, video, iframe { max-width: 100%; height: auto; }\n @media (max-width: 640px) {\n .hero-inner,\n .profile-card,\n .body-wrap,\n .seo-links,\n .pull-quote,\n .qa-block {\n max-width: 100%;\n width: 100%;\n }\n .q-text,\n .a-text,\n .intro-text,\n .pull-quote p,\n .profile-bio,\n .hero h1,\n .hero-subtitle {\n word-break: normal;\n overflow-wrap: normal;\n hyphens: none;\n -webkit-hyphens: none;\n }\n }\n<\/style>\n<\/head>\n<body>\n\n<div class=\"category-strip\">\n <span class=\"tag\">Interview<\/span>\n <span class=\"sep\">\u203a<\/span>\n <span>AI in Loyalty<\/span>\n <span class=\"sep\">\u203a<\/span>\n <span>Enterprise CRM<\/span>\n<\/div>\n\n<section class=\"hero\">\n <div class=\"hero-inner\">\n <p class=\"hero-eyebrow\">NervNow Interview Series<\/p>\n <h1>AI Helps You <em>Remember.<\/em> It Doesn’t Help You Matter.<\/h1>\n <p class=\"hero-subtitle\">Dilpreet Singh, Head of Loyalty, CRM, and Partnerships at ITC Hotels, spoke with NervNow about where AI genuinely fits inside the loyalty stack, why most Indian enterprises are still congratulating themselves at the starting line, how hospitality brands can protect emotional connection at scale, and why redemption rates are one of the most misread signals in the industry.<\/p>\n <div class=\"hero-meta\">\n <div class=\"hero-meta-author\">\n <div class=\"author-avatar\">NN<\/div>\n <div class=\"author-info\">\n <strong>NervNow Editorial<\/strong>\n <span>May 2026<\/span>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n\n<div class=\"profile-wrap\">\n <div class=\"profile-card\">\n <div class=\"profile-initial\">D<\/div>\n <div>\n <div class=\"profile-name\">Dilpreet Singh<\/div>\n <div class=\"profile-title\">Head, Loyalty, CRM & Partnerships · ITC Hotels Limited<\/div>\n <p class=\"profile-bio\">Dilpreet Singh leads Loyalty, CRM, and Partnerships at ITC Hotels, where he oversees the technology platform and engagement framework underpinning the company’s retention and loyalty programs. His two-decade career spans financial services, quick service restaurants, and luxury hospitality, with tenures at American Express, Jubilant Food Works (Domino’s India), The Smile Group, and The Oberoi Group, where he served as Head of CRM, Loyalty, and Customer Analytics. He is a certified Loyalty Marketing Professional from The Loyalty Academy and was named a Top 30 Under 40 Loyalty Professional by Loyalty Magazine UK in 2020.<\/p>\n <\/div>\n <\/div>\n<\/div>\n\n<main class=\"body-wrap\">\n\n <p class=\"intro-text\">Dilpreet Singh has spent two decades building loyalty infrastructure across three industries that have almost nothing in common except the problem at the center: how do you make a customer come back? From American Express to Domino’s India to The Oberoi Group to ITC Hotels, he has operated at the intersection of CRM, martech, and customer analytics through several generations of technology change. NervNow spoke with him about where AI actually fits into the loyalty stack today, why most enterprises are still at the starting line, how hospitality brands can protect emotional warmth at scale, and why unredeemed points are one of the most misread signals in the industry.<\/p>\n\n <div class=\"section-label\">AI in the Loyalty Stack<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have spent two decades building loyalty infrastructure across financial services, quick service restaurants, and luxury hospitality. In that time, the underlying data architecture has changed significantly. Where does AI actually fit into the loyalty stack today, and where is it still overpromised?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>There has been a lot of noise about AI across every domain, but let us be honest: AI is not a magic wand and it is not an external layer you bolt on. It is the ability to simplify complex decisions using data and technology, complementing human thinking rather than replacing it. I look at it through a very simple lens. AI helps you remember and respond. It does not help you matter.<\/p>\n <p>As customers, we do not get attached to brands because they remembered our last purchase. We stay because the overall experience feels worth coming back to. So AI’s real role sits in what I call the 3R layer: remember what the customer does, recommend what might make sense next, and respond at the right moment.<\/p>\n <p>Where it is overpromised is when we expect it to build loyalty. Loyalty lives in a different layer entirely, one driven by value, consistency, and trust. If that layer is weak, AI just helps you execute faster. Not better. I do not see AI as the hero. It enhances what is already there. If the foundation is weak, enhancement does not fix it.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>AI helps you remember and respond. It does not help you matter. Loyalty lives in a different layer entirely, one driven by value, consistency, and trust.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have led multiple large-scale CRM and CDP implementations, including AI-powered analytics layers. What does the gap between a vendor’s AI pitch and production reality actually look like, and what does it cost enterprises that miss it?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>The gap is not in AI. It is in an organization’s readiness to absorb AI. And the unfortunate truth is that most brands are not even clear on what they want from it.<\/p>\n <p>The issue starts with the foundation. Most vendor conversations assume a clean world: unified data, aligned teams, clear use cases. Real organizations are far from that. The stepping stone for any organization is what I think of as a 4C Readiness framework: Clean, Connected, Contextual, Committed. Data needs to be clean. Systems need to be connected. Data needs context, not just volume. And teams need to be committed to actually using the outputs.<\/p>\n <p>The biggest cost is not financial. It is cultural. Once teams lose trust in AI-generated outputs, adoption dies. The real work is unglamorous and happens entirely at the backend: fixing data, aligning teams, defining problems clearly. AI is the easy part. Getting the organization ready for it is the real challenge.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Personalization and Emotional Experience<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">Hospitality loyalty is fundamentally about emotional connection, not points. When you introduce AI-driven personalization at scale, is there a risk that guests start to feel the warmth is manufactured? How do you design against that?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Absolutely, and customers are perceptive enough to sense it immediately. There is a meaningful difference between being known and being processed.<\/p>\n <p>Imagine walking into a hotel where everything feels perfectly tailored but slightly mechanical. You know you are being handled by a system. But when a small, imperfect, human moment happens, when someone remembers something casually and without a script, it feels real. That is the distinction that matters.<\/p>\n <p>The concept I keep coming back to is what I call invisible intelligence. If the intelligence is visible, the experience weakens. AI should work in the background, enabling people to deliver better moments, not replacing those moments. Hospitality is not about accuracy. It is about how an experience made you feel. Feelings do not come from perfect targeting. They come from genuine, well-timed human interaction that happens to be supported by insight underneath.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>If the intelligence is visible, the experience weakens. AI should work in the background, enabling people to deliver better moments, not replacing those moments.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Data Readiness in India<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">In a previous role, you built a master database capable of fetching data across more than 200 scenarios in a single pull. That kind of data architecture is a prerequisite for serious AI deployment. In your experience, how many Indian enterprises are actually AI-ready at the data layer, and what does readiness look like in practice?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Honestly, the number is almost beside the point, because almost every organization believes it has arrived at AI readiness. The reality is that most are still congratulating themselves at the starting line. Most are in what I call the Data Illusion Stage: they have a lot of data, so they assume they are ready.<\/p>\n <p>Readiness is not about data volume. It is about decision speed, agility, and clarity. Brands need to assess their data layer across three parameters: access, accuracy, and actionability. Can teams access the data easily? Is it accurate and consistent? Can you act on it quickly?<\/p>\n <p>If a simple customer question takes multiple teams and several days to answer, AI will not fix that. When we built large data systems, the real objective was always to reduce the distance between signal and action. Organizations succeed when they focus on connecting their data rather than collecting it.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Measurement and Attribution<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You have overseen campaigns generating over 100 crore in incremental revenue through targeted, data-driven execution. As generative AI enters campaign orchestration, how do you think about measurement differently? Does attribution logic need to change when AI is co-authoring the campaign?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Customer behavior has never been linear. Brands have just forced it into linear models. As customers, we do not respond to a single message. It is always a combination: timing, context, mood, previous experiences. All of it becomes part of the decision.<\/p>\n <p>So attribution, as we have traditionally understood it, is an oversimplification. I prefer thinking in terms of decision influence systems rather than attribution models. It is not about what caused the action. It is about what combination enabled it.<\/p>\n <p>With AI now shaping content, timing, and targeting simultaneously, the need to shift becomes even more urgent. We need to move from credit-seeking to understanding-seeking, from last touch to full journey context, and from a funnel mentality to a flywheel one. Today AI is not just executing campaigns. It is co-creating the path. You cannot measure a journey with a single checkpoint.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Redemption and Program Health<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">The loyalty industry has historically struggled with one persistent problem: members earn points and never redeem, which looks good on the balance sheet but may signal disengagement. Can AI solve this, or does it simply make the obfuscation more sophisticated?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Unredeemed points are one of the most misunderstood signals in the industry. From a business lens, they look positive. From a customer lens, they often mean the member did not find it worth engaging. No brand wants to hear that.<\/p>\n <p>Redemption is a function of three things: value, simplicity, and timing. Is the reward worth it? Is the process easy? Is the offer relevant right now? AI can help with timing and nudges. It can simplify discovery. But it cannot create perceived value. If the reward does not excite the member or feels complicated to access, no volume of reminders will change behavior.<\/p>\n <p>AI does not solve the underlying problem. It intensifies whatever already exists. If the program is strong, AI scales engagement. If the program is weak, AI scales indifference.<\/p>\n <\/div>\n <div class=\"pull-quote\">\n <p>AI does not solve the underlying problem. It intensifies whatever already exists. If the program is strong, AI scales engagement. If the program is weak, AI scales indifference.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Organizational Alignment<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">You operate at the intersection of CRM, partnerships, and martech: three functions that often sit in different technology stacks with different owners. How does AI change the organizational question, not just the technology question, for enterprises trying to unify these?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>AI brings one uncomfortable truth to the surface: the customer experiences your organization as one entity, but you operate as many. Earlier, silos could survive because systems were slower and less connected. AI removes that buffer.<\/p>\n <p>The simplest lens here is one customer, one memory, one experience. If different teams hold different versions of the same customer, AI will expose it quickly through inconsistent messaging, broken journeys, or irrelevant offers.<\/p>\n <p>So the shift required is not purely technological. It is cultural. Organizations need to move from ownership of tools to ownership of journeys, and from measuring department success to measuring customer success. In my experience, alignment across people unlocks far more value than any AI model.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Regional Players vs. Global Scale<\/div>\n\n <div class=\"qa-block\">\n <div class=\"q-label\">NervNow<\/div>\n <div class=\"q-text\">Regional luxury hospitality players compete with international chains that have dramatically larger data pools. When a global operator can train models on tens of millions of transactions worldwide, how does a regional player use AI in a way that is differentiated rather than derivative?<\/div>\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>Global players win on scale of data. Regional players can win on depth of understanding. As a guest, what matters is not how much you are known, but how well you are understood in that moment. I think of this as context advantage.<\/p>\n <p>A global system may know your travel frequency. A regional player might know you are traveling for a family occasion, and that changes expectations entirely. AI performs best when data carries meaning, not just volume. So instead of chasing scale, regional brands should focus on context, culture, and occasion.<\/p>\n <p>In hospitality, relevance always beats reach.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"section-label\">Closing Thought<\/div>\n\n <div class=\"qa-block\">\n <div class=\"a-label\">Dilpreet Singh<\/div>\n <div class=\"a-text\">\n <p>For me, loyalty and CRM are not tech constructs. They come down to a very simple human question: did this brand make my life easier or better in any meaningful way?<\/p>\n <p>Everything else, AI, data, platforms, is just infrastructure. Because in the end, customers do not stay because you know them well. They stay because you used that understanding wisely.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"disclaimer\">\n <strong>Disclaimer:<\/strong> The views expressed in this interview are personal to Dilpreet Singh and do not represent the positions of ITC Hotels or NervNow.\n <\/div>\n\n \n <div class=\"seo-section\">\n <div class=\"seo-section-label\">Do Not Miss These Interviews<\/div>\n <ul class=\"seo-links\">\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/linkedins-guna-grace-on-indias-enterprise-ai-gap-deep-at-the-top-of-the-funnel-shallow-everywhere-else\/\" target=\"_blank\" rel=\"noopener\">\n LinkedIn’s Guna Grace on India’s Enterprise AI Gap: Deep at the Top of the Funnel, Shallow Everywhere Else\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/ekgaons-vijay-pratap-singh-on-indias-agri-paradox-data-and-ai-exist-intent-doesnt\/\" target=\"_blank\" rel=\"noopener\">\n Ekgaon’s Vijay Pratap Singh on India’s Agri Paradox: Data and AI Exist, Intent Doesn’t\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/georg-langlotz-ubs-india-does-not-have-an-ai-talent-problem-it-has-an-ai-ambition-problem\/\" target=\"_blank\" rel=\"noopener\">\n Georg Langlotz, UBS: India Does Not Have an AI Talent Problem, It Has an AI Ambition Problem\n <\/a>\n <\/li>\n <li>\n <a href=\"https:\/\/nervnow.com\/ro\/sportsedtv-ceo-victor-bergonzoli-on-how-ai-is-turning-athlete-data-into-a-financial-risk-model\/\" target=\"_blank\" rel=\"noopener\">\n SportsEdTV CEO Victor Bergonzoli on How AI Is Turning Athlete Data Into a Financial Risk Model\n <\/a>\n <\/li>\n <\/ul>\n <\/div>\n\n \n <div class=\"sources-section\">\n <div class=\"sources-label\">Sources<\/div>\n <ol class=\"sources-list\">\n <li>ITC Hotels, Loyalty and CRM division. Available at itchotels.com.<\/li>\n <li>The Loyalty Academy, Certified Loyalty Marketing Professional program.<\/li>\n <li>Loyalty Magazine UK, Top 30 Under 40 Loyalty Professionals, 2020.<\/li>\n <\/ol>\n <\/div>\n\n <p class=\"footer-note\">This interview was conducted by NervNow. All responses are reproduced from Dilpreet Singh’s submissions and have been lightly edited for formatting only. No responses have been altered in substance. The views expressed are personal to the interviewee and do not represent the positions of ITC Hotels or NervNow.<\/p>\n\n<\/main>\n\n<footer class=\"page-footer\">\n © 2026 <a href=\"https:\/\/nervnow.com\/ro\/\">NervNow<\/a> All rights reserved\n<\/footer>\n\n<\/body>\n<\/html>","protected":false},"excerpt":{"rendered":"<p>Dilpreet Singh of ITC Hotels explains where AI truly fits in loyalty and CRM, why most Indian enterprises are still not data-ready, and how hospitality brands can use AI to enhance personalization without losing emotional connection.<\/p>","protected":false},"author":5,"featured_media":7136,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[106,95,107],"tags":[123],"class_list":["post-7134","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analysis-ai-technology","category-analysis","category-analysis-marketing-advertising","tag-interview"],"blocksy_meta":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/comments?post=7134"}],"version-history":[{"count":5,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134\/revisions"}],"predecessor-version":[{"id":7144,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/posts\/7134\/revisions\/7144"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/media\/7136"}],"wp:attachment":[{"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/media?parent=7134"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/categories?post=7134"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nervnow.com\/ro\/wp-json\/wp\/v2\/tags?post=7134"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}