How to Get Your Customers to Trust AISKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoCustomer experience|How to Get Your Customers to Trust AISubscribeSign InLatestMagazineTopicsPodcastsStoreReading ListsData & VisualsCase SelectionsHBR ExecutiveSearch hbr.orgSubscribeLatestPodcastsThe MagazineStoreWebinarsNewslettersAll TopicsReading ListsData & VisualsCase SelectionsHBR ExecutiveMy LibraryAccount SettingsSign InExplore HBRLatestThe MagazinePodcastsStoreWebinarsNewslettersPopular TopicsManaging YourselfLeadershipStrategyManaging TeamsGenderInnovationWork-life BalanceAll TopicsFor SubscribersReading ListsData & VisualsCase SelectionsHBR ExecutiveSubscribeMy AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesSign InHarvard Business Review LogoCustomer experienceHow to Get Your Customers to Trust AI by Ashley Reichheld, Sebastian Goodwin and Courtney ShermanJanuary 22, 2026Yaroslav Danylchenko/StocksyPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintTransparency is supposed to build trust. But as companies rush to open the black box of artificial intelligence and explain how it works to customers, many are discovering a surprising truth: You can say too much and too little at the same time. The balance is hard to get right: Too little transparency breeds suspicion; too much overwhelms, blurring the very clarity it’s meant to provide.Ashley Reichheld is a principal at Deloitte Consulting LLP. She created TrustID, a system for helping companies measure, predict, and build trust with key stakeholders. She is the lead author of the book The Four Factors of Trust.Sebastian Goodwin , the chief trust officer at Autodesk, leads the company’s global strategy on trusted AI, security, privacy, and cloud resilience. He also lectures on managing cyber risk at the University of California, Berkeley.Courtney Sherman is a principal at Deloitte Consulting LLP and leads the firm’s Digital Product and Innovation practice.PostPostShareSavePrintRead more on Customer experience or related topics AI and machine learning and Consumer behaviorPartner CenterStart my subscription!Explore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceExplore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceFollow HBRFacebookX Corp.LinkedInInstagramYour NewsreaderHarvard Business Review LogoAbout UsCareersPrivacy PolicyCookie PolicyCopyright InformationTrademark PolicyTerms of UseHarvard Business Publishing:Higher EducationCorporate LearningHarvard Business ReviewHarvard Business SchoolCopyright ©2026 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School.

The pursuit of trust within customer relationships is complicated by the accelerating introduction of artificial intelligence, as outlined by Ashley Reichheld, Sebastian Goodwin, and Courtney Sherman. The article highlights a specific challenge: businesses attempting to explain AI systems often struggle to find the optimal balance between providing sufficient detail to foster confidence and overwhelming customers with superfluous information, thereby diminishing clarity. Reichheld’s work with TrustID, a system for quantifying and building stakeholder trust, provides a framework for understanding this issue. Goodwin’s role as Autodesk’s Chief Trust Officer underscores the strategic importance of prioritizing trust in AI, security, privacy, and cloud resilience. Sherman’s leadership within Deloitte Consulting’s Digital Product and Innovation practice emphasizes the need to integrate trust considerations across digital product development.

The core argument presented is that transparency, while generally beneficial, can backfire if not carefully managed in the context of complex technologies like AI. Customers are wary of black-box systems and require explanations to understand how decisions are made, but excessively technical descriptions can be confusing, raise further questions, and ultimately erode trust rather than enhance it. The authors suggest that a nuanced approach is necessary, one that acknowledges the inherent complexity of AI while still prioritizing clear, accessible communication.

The piece doesn’t offer a prescriptive formula for achieving this balance, but it strongly implies a focus on demonstrating *why* trust is being built, rather than simply detailing *how* the AI functions. It highlights the importance of acknowledging potential risks and limitations associated with AI systems, proactively addressing customer concerns, and demonstrating a commitment to ethical and responsible AI implementation. Furthermore, the authors emphasize the need for ongoing dialogue and feedback loops to continuously refine communication strategies and adapt to evolving customer expectations.

The article subtly positions trust as a strategic differentiator in an increasingly competitive market. Businesses that successfully navigate the complexities of AI-driven interactions and build genuine trust with their customers are likely to reap significant benefits, including increased loyalty, positive word-of-mouth referrals, and a stronger brand reputation. Conversely, those that fail to prioritize trust risk alienating customers and losing market share. The implications of this imbalance suggest a considerable investment in developing communication strategies and processes that center around fostering belief among users surrounding AI-driven initiatives.