人工智能规模化先行者指南：行业领导者的经验（英）

Lessons from industry leaders Authors Lan GuanChief AI Officer,Accenture Philippe RoussiereGlobal Lead forInnovation and AI,Accenture Research Senthil RamaniGlobal Lead forData & AI,Accenture About the research We surveyed 2,000 C-suite and data-scienceexecutives, who lead 1,998 of the world’s largestcompanies (revenues greater than $1 billion), which areheadquartered in 15 countries (Australia, Brazil, Canada,China, Germany, France, India, Italy, Japan, Saudi Arabia,Singapore, Spain, United Arab Emirates, United Kingdomand United States) and operate in nine industries(banking, insurance, energy, consumer goods and To identify the most important strategic bets (see “Getstrategic,” below), we also interviewed numerous C-suiteexperts within and outside Accenture. In addition, wedeployed machine learning to identify both the keycapabilities associated with scaling strategic bets and For the purposes of this report, “scaling AI” refers tothe process of expanding AI implementation across anenterprise to achieve broader, more impactful outcomes.Scaling includes integrating AI into diverse businessprocesses and workflows; ensuring widespread adoption Executive summary For businesses, securing a sustained advantage over competitorswas long the Holy Grail—a coveted, yet elusive prize. Today,however, generative artificial intelligence and other forms of AI Though every business may want an AI-powered edge, manycompanies are still struggling to advance beyond their initialAI experiments. A big reason for this, our research also shows, 70% of the companieswe surveyedacknowledged the Encouragingly, most business leaders recognize this challenge.For example, 70% of the companies we surveyed acknowledged But reinventing the enterprise with generative AI (gen AI) isn’tsimply a matter of deploying a few chatbots. Reinvention is aboutbuilding advanced AI capabilities like “agentic architecture,” Data, of course, isn’t the only obstacle to enterprise reinventionwith gen AI. Outdated IT systems, as well as workers’ lack of access Endowed with sophisticated reasoning, AI agents collaborateautonomously to improve quality, productivity and cost-efficiencyat scale. Agentic architecture is spreading fast: one-third of the At the same time, our research revealed that a small minority ofcompanies (“front-runners”) are already achieving considerablesuccess at reinventing their enterprises with gen AI. These Reinvention thus requires integrating AI deeply into the core ofa company’s strategy. To do this, businesses, under the proactiveleadership of their CEO and board, must go beyond surface-level Front-runners, for example, use agentic AI in their table stakes toboost efficiency. And in their strategic bets, they deploy agentic AIto radically reinvent their organizational processes and workflows. We found that 34% of surveyedcompanies have scaled at least onestrategic bet. Such companies also spendsignificantly more on cloud and AI(devoting 51% of their technology budgets To uncover the most important strategic bets in eachof the nine industries we studied, we solicited theviews of Accenture experts who have advised clientson 2,000 recent gen AI projects. We also interviewedexternal AI experts at various large companies around “Strategic bets” are significant, long-terminvestments in gen AI that focus on the core ofa company’s value chain (such as underwritingand claims for an insurer, asset managementfor a utility and R&D for a life sciences firm) and Later, our survey of 2,000 executives* from 1,998 ofthe world’s largest companies revealed the extent towhich these organizations have adopted gen AI byscaling their respective, industry-focused, strategicbets. Companies in the utilities industry, say, were “Table stakes” are the opposite: foundationalinvestments that drive broad AI adoption within anorganization and validate the technology’s abilityto handle specific uses cases (such as customer-support centers that seamlessly move between text Companies that scale strategic bets are usuallydelighted with their financial performance as well.For instance, compared to competitors that havenot done so, companies that have scaled at least one But regardless of whether they have a lot, or a little, work to do before theyscale more strategic bets, all the companies we surveyed expect big thingsfrom reinvention with gen AI. On average, these organizations expect a 13% Drawing on our empirical research and extensive client work, this reportexplores the distinguishing traits of AI reinvention-ready companies, whichremain poorly understood. In the following pages, we identify the essential 1.Lead with value2.Reinvent talent and ways of working As this report makes clear, artificial intelligence has already moved past itsfamiliar role as a powerful tool for boosting efficiency. When used to its fullpotential, AI is now something far greater: an unstoppable force for enterprise What makes a companyreinvention-ready fo