弥合商业智能与人工智能之间的鸿沟

NetworkautomationCIO vision 2025:Bridging the gapbetweenBIandAI Preface “CIO vision 2025: Bridging the gap between business intelligence (BI) and AI” is an MITTechnology Review Insights report sponsored by Databricks. To produce this report, in Mayand June 2022, MIT Technology Review Insights conducted a global survey of 600 chiefinformation officers, chief technology officers, chief data and analytics officers, and othersenior data and technology executives. We also interviewed 10 C-level executives fromFortune 500 companies and successful start-ups. The survey respondents are evenlydistributed among North America, Europe, and Asia-Pacific. There are 14 sectorsrepresented in the sample, and all respondents work in organizations earning $500 million ormore in annual revenue. The research also included a series of interviews with executiveswho are directly involved in their organizations’ AI and machine learning initiatives. DenisMcCauley was the author of the report, Francesca Fanshawe was the editor, and NicolaCrepaldi and Natasha Conteh were the producers. The research is editorially independent,and the views expressed are those of MIT Technology Review Insights. We would like to thank the following executives for providing their time and insights: Sherry Aholm,Chief Digital Officer, CumminsVittorio Cretella,Chief Information Officer, Procter & GambleDavid Hogarth,Chief Information Officer, Virgin AustraliaMarc Kermisch,Chief Information Officer, CNH IndustrialSwamy Kocherlakota,Chief Information Officer, S&P GlobalMike Maresca,Global Chief Technology Officer, Walgreens Boots AllianceMasashi Namatame,Group Chief Digital Officer, Managing Executive Officer, Tokio MarineJeremy Pee,Chief Digital and Data Officer, Marks & SpencerPrasad Ramakrishnan,Chief Information Officer, FreshworksRowena Yeo,Chief Technology Officer & Global Vice President, Technology Services,Johnson & Johnson CONTENTSCONTENTS Preface...............................................................................................2Executive summary................................................................... 401Executive summary................................................................3About the survey............................................................................................... 4 Key takeaways..............................................................................5The new case for cloud computing.................................7More talk than action............................................................... 802Room to grow with AI.............................................................5Lofty ambitions.................................................................................................. 5Tokio Marine: Striving to become AI-driven.......................................... 7Databricks perspective.................................................................................. 8 Rethinking technology obsolescence..........................11The cloud is different...............................................................12The need to move.....................................................................1303A shift to financial value realization....................................9AI use case development to 2025:Selected company examples.................................................................... 10 Exploring the cost of technologyobsolescence..............................................................................1504Meeting the challenges of scale.........................................11Procter & Gamble (P&G): Automating to scale................................. 13 Look beyond the cost savings......................................... 16Conclusion: Changing thecloud conversation.................................................................. 1805The data priorities.................................................................14Priorities in focus.............................................................................................15Multi-cloud and open.....................................................................................17CNH Industrial: AI, open data, and the sustainable tractor......... 18An industry lens on data and AI................................................................ 19 06Conclusion.............................................................................20 It’s been several years since organizations beganadopting artificial intelligence (AI) to improve theirbusiness; few have come close to mastering itsexisting capabilities. A small number of organizations inour research aim to become AI-driven—a status wedefine as AI and machine learning underpinning almosteverything the enterprise does—by 2025. However, thiselite group—who we term “AI leaders”1—as well as themany others looking simply to embed AI more firmly in theenterprise foundations face formidable challenges toachieving their objectives. Following