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

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