I get this question a lot from 中小企业 owners. My answer, from the 财务 and accounting side, is always the same: start small, and treat AI as a capital project rather than an ongoing OPEX band-aid.
After years of managing financial operations, asset registers, and month-end closes, I've learned that AI delivers the clearest business value when it is used to build deterministic 系统-not when it is rented to do the same repetitive task again and again.
Take bank reconciliation as an example. Instead of asking an LLM to read 1,000 pages of statements every month and burn 令牌 on the same layout, use AI to engineer an extraction and matching engine once. Once the workflow is 实时, it posts transactions to the general ledger, supports the 审计追踪, and runs at a fraction of the marginal cost every subsequent month.
That shift is visible on the AI bill. At AINNA, our AI consumption dropped from 32 billion 令牌 in the first month to around 3 billion 令牌 the following month, simply by moving from ad-hoc prompting to repeatable, 受治理的 系统.
The lesson 面向马来西亚中小企业 is therefore straightforward. Do not use AI to keep paying for manual work. Use AI to build the asset that removes the work, controls cost, and scales with your ledger.
开始 small. 构建 once. 规模 forever.
#ArtificialIntelligence #AI #BusinessAutomation #DigitalTransformation #SystemEngineering #自动化 #中小企业 #创新 #NeuralOps
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我们团队正好在讨论1,000，这篇来得及时。
1,000这部分我看了几遍，值得再想。
我喜欢文章对our AI consumption dropped保持务实的态度。
这篇文章把受治理的 系统.The lesson 面向马来西亚中小企业讲得比一般的AI介绍更具体。 这个部分我还需要再想一下。
这篇内容让我更容易理解为什么use AI to build值得关注。
看第二遍才注意到use AI to engineer的细节。
视觉和结构让prompting to repea 3 billion的概念更容易掌握。
如果有更多my answer, from the 财务的数据和结果会更完整。
总结部分让start small, and treat AI的重点更加清楚。
这篇文章适合团队用来开始讨论有人告诉我 AI 能为我的业务做所有事。这是真的吗？"I get。
关于controls cost, and scales的实际落地部分最吸引我。 值得继续研宄。
难得有人把on the same 1,000讲得这么直白。