Why Your Company Needs a Chief Data, Analytics, and AI OfficerSKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoAI and machine learning|Why Your Company Needs a Chief Data, Analytics, and AI OfficerSubscribeSign InLatestMagazineTopicsPodcastsStoreReading ListsData & VisualsCase SelectionsHBR ExecutiveSearch hbr.orgCLEARSubscribeLatestPodcastsThe 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 LogoAI and machine learningWhy Your Company Needs a Chief Data, Analytics, and AI Officer by Vipin Gopal, Thomas H. Davenport and Randy BeanDecember 1, 2025Illustration by Miguel PorlanPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintHow is AI and data leadership at large organizations being transformed by the accelerating pace of AI adoption? Do these leaders’ mandates need to change? And should overseeing AI and data be viewed as a business or a technology role?VGVipin Gopal is a longtime senior industry executive, and data and AI leader. He has served as Chief Data and Analytics Officer for Eli Lilly and Company and Walgreens Boots Alliance, and as Senior Vice President of Analytics at Humana. Early in his career, he held data and analytics leadership roles with CIGNA and United Technologies.  Gopal holds a PhD from Carnegie Mellon University.Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and faculty director of the Metropoulos Institute for Technology and Entrepreneurship at Babson College, a visiting scholar at the MIT Initiative on the Digital Economy, and a senior adviser to Deloitte’s Chief Data and Analytics Officer Program.Randy Bean Randy Bean is the author of Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI. He is a contributor to Harvard Business Review, Forbes, and MIT Sloan Management Review, and has been an advisor to Fortune 1000 organizations on data and AI leadership for nearly 4 decades. He was previously founder and CEO of NewVantage Partners (NVP), a data and AI leadership advisory firm to Fortune 1000 clients, which he operated from 2001 until its acquisition in 2021.  You can contact at rbean@randybeandata.com or rbean@dataaiex.com and follow him on LinkedIn.PostPostShareSavePrintRead more on AI and machine learning or related topics Technology and analytics, Leadership, Corporate governance, Digital transformation, Data management, Analytics and data science and Generative AIPartner 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 PreferencesAccount FAQHelp 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 PreferencesAccount FAQHelp 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 ©2025 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School.

The article “Why Your Company Needs a Chief Data, Analytics, and AI Officer” posits a fundamental shift in organizational leadership necessitated by the accelerating adoption of Artificial Intelligence (AI) and machine learning. The authors, Vipin Gopal, Thomas H. Davenport, and Randy Bean, argue that the traditional approaches to data and analytics management are no longer sufficient, and a dedicated leader – a Chief Data, Analytics, and AI Officer – is required to effectively navigate this new landscape. The core argument revolves around the need to transition from viewing data and analytics as primarily a technology function to recognizing its critical role as a strategic business imperative.

The authors highlight several key factors driving this change. First, the pace of AI innovation is rapidly increasing, demanding a proactive and strategic response. Simply implementing analytics tools or hiring data scientists is no longer enough; a dedicated leader is needed to guide the overall AI strategy, ensuring it aligns with the company's broader business goals. Second, the rise of AI elevates data from a support function to a core asset. This transformation requires a new mindset—one that emphasizes data-driven decision-making at all levels of the organization. This means the CDIAO must champion a culture of data literacy and empower employees to leverage data effectively.

The piece identifies a move away from siloed data management practices. Historically, organizations often treated data as a byproduct of specific business units. However, the authors stress the need for a holistic view of data, integrating information across departments to generate actionable insights. The CDIAO is instrumental in breaking down these silos and fostering collaboration between data teams and business leaders. Crucially, the CDIAO must ensure data governance and quality, which are increasingly complex in an environment of diverse data sources and rapidly evolving AI technologies.

The authors advocate for a leadership role that goes beyond technical expertise. While technical proficiency is essential, the CDIAO must also possess strong business acumen, strategic thinking abilities, and change management skills. They must be able to translate complex technical concepts into understandable terms for business stakeholders, secure executive sponsorship, and drive organizational change.

Randy Bean’s earlier work with NewVantage Partners underscores the importance of a data-driven culture—one where decisions are informed by data, and where data is treated as a competitive advantage. The piece implicitly calls for a role that embodies this shift, overseeing not just the implementation of AI technologies, but the entire data ecosystem within the organization.

Furthermore, the piece points to a need for strategic prioritization. Given the sheer volume of AI possibilities, the CDIAO must be skilled at identifying the most impactful use cases – those that will deliver the greatest return on investment and align with the company’s strategic objectives. This requires a deep understanding of the business, coupled with an ability to assess the technical feasibility and potential risks of different AI initiatives.

In essence, the article argues for a leadership role—the CDIAO—that provides a framework for effectively harnessing the power of data and AI to drive business innovation and competitive advantage. It's a move from reactive data management to proactive, strategic leadership.