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IBM:2026财务执行力驱动AI价值规模化释放洞察报告:规范管控决定成败 而非技术(英文版)(32页).pdf

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1、IBM Institute for Business Value|Research InsightsFinance execution unlocks AI value at scaleDisciplinenot technology determines success2 2Contents Introduction Capturing the full value of AI .2Part one Understanding the AI-in-finance cadence .4Part two Where and how AI in finance pays off .10Part t

2、hree Enabling an AI-friendly operating model .15Action guide The road to AI maturity .221AI dramatically cuts finance costsbut scale unlocks the largest gains.Experienced adopters cut total finance cost by a median 8%,and up to 18%where AI is built into end-to-end processes rather than siloed use ca

3、ses.AI speed and return depend on operating model maturitynot technology choice.Organizations with mature execution models see faster payback(around six months versus eight)and lower delivery cost(USD39 versus USD59 per employee),underscoring that finance-led operating models,not tools,drive enterpr

4、ise-wide transformation with AI.Uneven adoption signals how AI priorities should unfold in sequence.Among optimizing adopters,AI adoption reaches 95%in financial planning and analysis,but only 58%in procure-to-pay,revealing a clear sequencing roadmap:where to scale now and where to build prerequisit

5、es.Organizations with mature execution models see faster payback(around six months versus eight)and lower delivery cost(USD39 versus USD59 per employee).Key takeaways1IntroductionAI is quickly becoming a defining capability for finance,already delivering measurable improvements in cost,cycle time,an

6、d quality.Yet the results across organizations are unevenand the gap is widening.The difference is not the technology itself.It is how finance leaders holistically implement AI across processes,data,controls,and people.Finance functions that fail to scale AI risk more than slower efficiency gainsthe

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1. **AI价值核心**:纪律性执行(非技术)决定成功,成熟企业AI使总财务成本中位数降低8%,端到端流程优化可达18%。 2. **成熟模型优势**:执行成熟企业投资回报周期更短(6个月 vs 8个月),交付成本更低(人均39美元 vs 59美元)。 3. **采用优先级**:AI在财务规划与分析(FP&A)采用率最高(95%),采购到付款(P2P)最低(58%),需优先部署数据标准化、流程重复性高的领域。 4. **关键障碍**:46%企业担忧AI可靠性/合规性,37%缺乏内部技能,32%数据质量差或系统碎片化。 5. **行动建议**:构建基于流程的AI路线图,建立受治理的数据基础,工业化执行(如正式用例流程),将信任融入设计,规模化技能与问责制。
AI如何降本? AI落地关键? AI优先序?
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