人工智能战略践行手册：从试点到全面落地

A playbook forcrafting AI strategy Preface “A playbook for crafting AI strategy” is an MIT Technology Review Insights reportsponsored by Boomi. To produce this report, MIT Technology Review Insightsconducted a global survey of C-suite and senior data executives across countriesand industries. The report also draws on in-depth interviews conducted with businessleaders on data and AI. Adam Green was the author of the report, Teresa Elsey was the editor, and NicolaCrepaldi was the publisher. The research is editorially independent, and the viewsexpressed are those of MIT Technology Review Insights. We would like to thank the following executives and experts for their time and insights:Kevin Collins, Founder and Chief Executive Officer, Charli AIAmy Machado, Senior Research Manager, IDCMatt McLarty, Chief Technology Officer, BoomiSP Singh, Senior Vice President and Global Head, Enterprise Application Integrationand Services, Infosys About the survey The survey forming the basis of this report was conducted by MIT Technology ReviewInsights in March 2024. The survey sample consists of 205 executives and data andtechnology leaders. Eleven industries are represented: financial services, manufacturing,IT and telecommunications, consumer goods and retail, pharmaceutical and health care,government, travel and hospitality, professional services, energy and utilities, transportand logistics, and media and marketing. Nearly all survey respondents (88%) come from the C-suite. These include chiefexecutive officers (20%), chief information officers (18%), chief technology officers(19%), and chief data officers (15%). The respondents’ organizations are headquarteredin North America (31%); Europe, the Middle East, and Africa (25%); Asia-Pacific (26%);and Central and South America (18%). All respondents work at organizations with morethan US $500 million in global annual revenue, with 73% representing organizationsgenerating more than US $1 billion, and 34% more than US $10 billion. CONTENTS 01Executive summary..................................................................................................402Partnering for success...........................................................................................6Selecting a vendor........................................................................................................ 7Finance-friendly AI....................................................................................................... 703Counting the cost.......................................................................................................8Spending expectations.............................................................................................9Measuring return on investment.......................................................................1004Building a data core.................................................................................................. 11Data management: Tips and tactics................................................................ 11Reckoning with legacy infrastructure............................................................13Data lineage and liquidity.......................................................................................13Metadata...........................................................................................................................1305Acceleration versus caution.............................................................................14Hallucinations, errors, and bias..........................................................................14Cyber risk.........................................................................................................................14Data privacy and protection.................................................................................14Rising regulatory tide................................................................................................ 15Compliance challenges...........................................................................................16 06Conclusion..................................................................................................................... 17 11Executivesummary Giddy predictions about AI, from itscontributions to economic growth to theonset of mass automation, are now asfrequent as the release of powerful newgenerative AI models. The consultancyPwC, for example, predicts that AI could boost globalgross domestic product (GDP) 14% by 2030, generatingUS $15.7 trillion.1 “No job, no function willremain untouched by AI.” SP Singh, Senior Vice President andGlobal Head, Enterprise ApplicationIntegration and Services, Infosys Forty percent of our mundane tasks could be automatedby then, claim researchers at the University of Oxford,while Goldman Sachs forecasts US $200 billion in AIinvestment by 2025.2,3“No job, no function will remainuntouched by AI,” says SP Singh, senior vice presidentand gl