Dive Brief:深度简报：
- Despite widespread adoption efforts, fewer than one-quarter of enterprises have successfully scaled AI across multiple business units, according to Gartner data released Tuesday. The IT advisory firm surveyed more than 1,300 leaders from organizations with more than $50 million in revenue between January and April of this year. 根据Gartner周二发布的数据，尽管企业普遍在采用AI方面做出努力，但成功将AI扩展至多个业务部门的企业不足四分之一。这家IT咨询公司在今年1月至4月期间，调查了收入超过5000万美元的组织的1300多名领导者。
- The lag in adoption isn’t slowing plans to roll out the technology, with 85% of tech leaders planning to up their AI investments next year. About 11% of the organizations that responded said they lacked visibility into what they spent on AI in 2025, according to Gartner.采用上的滞后并未减缓企业推广该技术的计划，85%的技术领导者计划明年增加AI投资。Gartner指出，约11%的受访组织表示，他们对2025年在AI上的支出缺乏了解。
- Low visibility into AI spending heightens the risk of missing ROI, Tina Nunno, distinguished VP and fellow at Gartner, said in the report. “Without disciplined measurement tied directly to business outcomes, organizations risk wasted resources and unmet expectations,” she said. Gartner杰出副总裁兼研究员Tina Nunno在报告中表示，对AI支出缺乏了解会增加错失投资回报的风险。她说：“如果没有与业务成果直接挂钩的严格衡量标准，组织就可能面临资源浪费和预期落空的风险。”
Dive Insight:深度见解：
Enterprises continue to fuel AI investments despite a lack of clear ROI, but this approach can muddy an organization’s chance at finding the right use cases for it. 尽管缺乏明确的投资回报，企业仍在加大AI投资，但这种做法可能让组织更难找到适合自身的AI应用场景。
Nearly three-quarters of senior business executives said they’ve scaled fewer than 25% of their AI pilots successfully, and two-thirds said their organization struggles to measure the ROI generated by AI to prove the positive benefits executives tout, according to an August Infosys report.Infosys今年8月的一份报告显示，近四分之三的高级业务高管表示，他们成功扩展的AI试点项目不到25%；三分之二的高管表示，其组织难以衡量AI产生的投资回报，以证明高管们所宣扬的积极效益。
Many enterprises aren’t as prepared for AI deployment — especially agentic systems — as they think. Only 1 in 5 senior managers and C-suite executives said their organization is prepared to redesign business processes to run autonomously with AI agents, an August Deloitte report found.德勤8月份的一份报告发现，许多企业对AI部署（尤其是智能体系统）的准备并不像自己想象的那样充分。只有五分之一的高级经理和C级高管表示，其组织已准备好重新设计业务流程，以实现AI智能体的自主运行。
Enterprises that constantly track the ROI of their AI initiatives, treat it as a portfolio of value and regularly assess project performance see greater returns, Gartner’s data showed. Companies that follow this framework and discontinue underperforming initiatives reported positive returns in 81% of their AI initiatives. Gartner的数据显示，持续跟踪AI项目投资回报、将其视为价值组合并定期评估项目绩效的企业，会获得更大的回报。遵循这一框架并终止表现不佳项目的企业报告称，其81%的AI项目取得了正回报。
“We want companies to get more out of AI, rather than risk spending more and either not getting appropriate return on investment, or creating more technical risk,” Nunno said in an email to CIO Dive.Nunno在给CIO Dive的电子邮件中表示：“我们希望企业从AI中获得更多价值，而不是冒着支出更多却无法获得相应投资回报或产生更多技术风险的风险。”
Tech leaders can fall prey to AI hype cycles, Nunno said. The most widely pursued AI use cases, such as cybersecurity, threat detection and IT service desk automation, don’t always deliver the highest ROI. Nunno表示，技术领导者可能会陷入AI炒作周期的陷阱。最广泛采用的AI用例，如网络安全、威胁检测和IT服务台自动化，并不总能带来最高的投资回报。
Intelligent IT asset and cost optimization, synthetic data generation and automated code generation and refactoring were among the top three AI use cases with positive returns, according to Gartner.据Gartner称，智能IT资产与成本优化、合成数据生成以及自动代码生成和重构，是位居前三的具有正回报的AI用例。
However, the AI use cases that will prove the most value for a company are the ones that target specific business needs and build necessary data foundations when needed, Nunno said.然而，Nunno表示，能为公司带来最大价值的AI用例，是那些针对特定业务需求、并在必要时构建所需数据基础的用例。
“CIOs should always prioritize use cases where the business case and financial logic make sense for their specific company, AI maturity and business needs,” Nunno said. “Having rigor both around the business case, and ensuring it meets your company’s strategic vision for AI will ensure CIOs choose the best use cases to maximize value.”Nunno表示：“CIO应始终优先考虑那些业务案例和财务逻辑符合其公司具体情况、AI成熟度和业务需求的用例。在业务案例上严格把关，并确保其符合公司AI战略愿景，将有助于CIO选择最佳用例以实现价值最大化。”
