AI’s Impact on SaaS Will Be Uneven. Here’s What Leaders Need to Know.SKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoCorporate strategy|AI’s Impact on SaaS Will Be Uneven. Here’s What Leaders Need to Know.SubscribeSign 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 LogoCorporate strategyAI’s Impact on SaaS Will Be Uneven. Here’s What Leaders Need to Know. by Christopher StantonMay 27, 2026Flavio Coelho/Getty ImagesPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintFor two decades, software-as-a-service (SaaS) grew by digitizing workflows. Customer relationship management systems recorded sales activity. Field-service platforms scheduled jobs, retrieved customer histories, and fed upsell opportunities back into sales teams. The model created value by taking opaque or messy information and putting it in workers’ hands. Before AI coding tools, few buyers were positioned to build comparable feature sets in-house.Christopher Stanton is the Marvin Bower Associate Professor of Business Administration at Harvard Business School.PostPostShareSavePrintRead more on Corporate strategy or related topics Information management, Data management, Generative AI, Competitive strategy and Budgets and budgetingPartner 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 historical trajectory of software-as-a-service (SaaS) growth for the past two decades was fundamentally driven by the digitization of workflows. This growth was anchored by systems such as customer relationship management and field-service platforms, which effectively structured sales activities, managed job scheduling, retrieved customer histories, and fed upsell opportunities back into sales teams. The core value proposition of this SaaS model stemmed from its ability to transform opaque or disorganized information into actionable data placed directly into the hands of the workforce. Prior to the advent of sophisticated AI coding tools, this capability meant that very few potential buyers possessed the requisite internal capacity to develop feature sets comparable to what was being offered by competitors. This historical context establishes a critical framework for understanding the forthcoming impact of artificial intelligence on the SaaS sector, suggesting that the unevenness in AI's adoption will be influenced by the existing legacy of data management and workflow integration.