2025年首席数据官研究：AI乘数效应——利用决策就绪型数据加速增长

The AI multiplier effect Accelerate growth withdecision-ready data How IBM can help IBM has been at the forefront of helping organizations tap intothe power of data and AI to drive business transformation. Withextensive experience and expertise, IBM provides tailoredsolutions that address specific data challenges and opportunities,including developing dynamic data strategies, implementingAI-enabled decision support systems, and establishing scalableenterprise data architectures. IBM watsonx™ empowersorganizations to harness AI for predictive analytics, real-timedata processing, and automated decision-making. For more information about IBM’s data and AI services,visithttps://www.ibm.com/consulting/data-ai To explore AI solutions from IBM Software, visitibm.com/watson. For insights into AI innovations from IBM Research,visithttps://research.ibm.com/artificial-intelligence Contents Foreword2 Introduction4 Strategy: Don’t just collect data. Deploy it on a mission.10 Scale: Give AI agents a fast track to data.16 Resilience: Build unbreakable data pipelines.22 Innovation: Deliver data to every desk.26 Growth: Spot breakthroughs waiting to happen.30 Foreword The architecture for scaling AI: Fromfragmented to integrated enterprise data Enterprise AI at scale is finally within reach. The technology is ready—as longas organizations can feed it the right data. Ed LovelyVP and Chief Data OfficerIBM But many simply cannot. This year, I’ve personally spoken to more than 150enterprise clients, and one challenge has emerged above all others: data istrapped in silos. Finance has their data. HR has theirs. Marketing, supply chain,legal—each function’s data operates in isolation. No common taxonomy. Noshared standards. No end-to-end visibility. This isn’t just an operational inconvenience. It’s the Achilles’ heel of enterpriseAI transformation. When data lives in disconnected silos, every AI initiativebecomes a drawn-out, six-to-twelve-month data cleansing project. Teams spendmore time hunting for and aligning data than generating meaningful insights. This year’s Chief Data Officer (CDO) Study offers an alternative. Based on datafrom 1,700 enterprise data leaders, it highlights what can be achieved with atruly integrated enterprise data architecture. AI agents can be deployed at scale—and fast. With access to the right data, they can go beyond isolated use casesto cross-functional, high-impact use cases. First, leaders must fundamentally shift their mindset. Stop seeing data as anapplication byproduct. Start viewing it as a strategic asset that flows acrossthe entire value chain. This means creating data standards that work across all systems, not just withinindividual ERPs. It means working backward from business outcomes to identifythe workflows and data that truly matter. It means treating data experiences likeproduct experiences—designed to attract users, drive adoption, and deliverintuitive value. Most importantly, it means shifting from data ownership to datastewardship, making information accessible where and when decisions are made. The goal is federated access with security and governance—democratizing datain a safe, controlled way. This will transform your employees, regardless of theirrole, into trusted business advisors who can spend time generating insightsinstead of chasing data across silos. Get this right, and the advantages compound rapidly. In the short term, you’ll seefaster AI deployment, better decision-making, and enhanced productivity. Longterm? You’ll have built an enterprise operating model that circulates intelligencethroughout your organization. While competitors struggle with siloed AIexperiments, you’ll be scaling intelligent automation across every criticalbusiness process. The companies that crack this code won’t just have better AI—they’ll havefundamentally different capabilities. They’ll move faster, decide smarter, andadapt more quickly to market changes. Will your enterprise be among them? Keytakeaways CDOs who tap into theirorganization’s most valuabledata—and have a clear visionof what they want to achieve—deliver better AI-poweredbusiness results. CDOs are navigating in fog. 92% say they must focus on business outcomes tosucceed in their role. But only 29% are confident theyhave clear measures to determine the business valueof data-driven outcomes. Data democratizationexpedites AI efforts. 80% of CDOs say giving employees accessto data helps their organization move faster. AI agents get the job done. 83% of CDOs say the potential benefits of deploying AIagents in their organizations outweigh the risks—and 77%say they’re comfortable with their organization relying onoutcomes from AI agents. Data products give organizationsthe high ground. 78% of CDOs say leveraging proprietary data is a topstrategic objective to differentiate their organizationin the market. Introduction In an AI-first enterprise,data makes the difference AI-first enterprises are rede