AI优先操作系统：运营与商业模式创新蓝图

W H I T EP A P E R Images:Getty Images Contents Executive summary4 Introduction5 Block 1: Intelligence engine9 1.1 The speed loop10 1.2 The scale loop12 1.3 The scope loop14 Block 2: Adaptive AI technology stack17 Foreword Michael RömerSenior Partner & Global Lead,Activate: Digital and Analytics,Kearney Cathy LiHead, Centre for AI Excellence;Member, Executive Committee Maria BassoHead, AI Applications andImpact, Centre for AI Excellence, For most of business history, the enterprisehas had a ceiling.There were limits on how fastenterprises could learn and how fast informationcould travel from the edge of an organization tothe centre to inform action. Additionally, there wereconstraints on how rapidly decisions could be madeand executed, and how far enterprises could scale can do for industry, global ecosystems and societyby exploring the business and operating modelbreakthroughs that AI is making possible andshaping the next era of enterprise. Over the pastyear, the workstream went deep into the frontier of What we found is both clarifying and demanding.It's "clarifying", because we have discovered acoherent set of fundamentals across companiesthat seem different from one another – from drugdiscovery to financial infrastructure, and fromautonomous logistics to legal AI. It's "demanding", A small but growing number of enterprises aredismantling those limits. They are achieving thisnot by adopting AI as a tool, but by designing theirentire operating logic around artificial intelligence (AI)– building systems that learn from every interaction,improve with every cycle and expand into newdomains without proportional increases in cost orcomplexity. These are the “AI-first” enterprises, The five building blocks in this paper – theintelligence engine, the adaptive technologystack, redesigned operations, human-AI teamingand new value creation – are not a roadmap fortransformation. They describe how the frontier The World Economic Forum’s AI-FirstEnterprises workstream, part of the AI GlobalAlliance, brought together more than 50 of the The structural limits are gone. What comes next,how far this frontier moves, who it reaches and whatit makes possible for industries and societies are the Executive summary A new enterprise operating system is emerging:organizations designed around intelligence as acore capability for value creation. A new class of organizations is emerging, designingtheir operations around intelligence, using data asa key resource and embedding artificial intelligence(AI) into processes, decision-making and execution.These “AI-first” enterprises are demonstrating –Human-AI teaming: Roles, teams andorganizational structures are designed to enablecontinuous collaboration between people and –New value creation: Every AI-first organization,regardless of sector, must decide how toposition intelligence integration in the market.From AI as a product feature to AI as invisibleinfrastructure, positioning choice determines This white paper examines how these organizationsare built, how they operate and what separatesthem. Drawing on deep engagement with morethan 50 of the world’s most advanced AI-first Together, these building blocks form a blueprintfor operating in a world where intelligence isabundant and continuously advancing. Tomake this actionable, this paper extendsthe traditional business model canvas with Five building blocks capture the fundamentals ofhow AI-first enterprises are designed and run: –Intelligence engine at the core:Enterprisesplace intelligence at the centre of theiroperations and business models, turning everyinteraction into a compounding source of The rise of AI-first enterprises is in its early stages.It remains unclear which approaches will provemost effective across industries, how broadly theywill scale and what their long-term implications will For leaders, the imperative is to build thecapabilities required to test and scale AI-firstoperating systems across the enterprise. Forentrepreneurs, the opportunity lies in turningintelligence into differentiated products, servicesand systems at scale. For policy-makers, the –Adaptive AI technology stack:Organizationsbuild modular, adaptable technologyarchitectures that integrate data, models and –Operations redesign: Enterprises systematicallydigitize their workflows with intelligence – notoptimizing them at the margins but connecting all Introduction Artificial intelligence (AI) is the latest class ofgeneral-purpose technology, like electricity,computers and the internet. Historically, thesetechnologies had a limited impact when incumbent resulting in no productivity gains but reducingenergy costs by 20–60%.1 The breakthrough came when pioneering factoriesredesigned their entire blueprints around electricity;one example is Henry Ford reworking his assemblyline system between 1919 and 1926.2Theseleaders reconfigured workflows, distributed powerto individual workstations and rebuilt production In ele