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正在致力于自动化小型企业的财务管理（记账、对账、基本报告）。我注意到的一件事是：与编程相比，会计往往看起来是更容易自动化的问题：它是基于规则的双重记账、科目表、税务规则、重要性阈值。对于大多数日常交易，你并不是在创造新的逻辑，而是在应用现有的规则。它是可验证的账本要么平衡，要么不平衡。分类账要么对账成功，要么不成功。几乎总有一个“真实依据”可以进行比较（银行数据、报表、前期数据）。它是无聊且重复的每个月都是相同的供应商、相同的类别、相同的模式。人类讨厌这项工作，而软件却喜欢。在会计方面，至少在小型企业层面，大部分工作感觉像是：从银行/信用卡/发票中规范化数据应用确定性或可配置的规则将例外情况呈现给人类审核进行一致性检查和报告真正困难的部分（税务策略、边缘案例、复杂历史、与当局沟通）占总工时的比例较小，但需要人类参与。繁琐的工作主要集中在重复的、基于规则的任务上。

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Working on automating small business finance (bookkeeping, reconciliation, basic reporting).One thing I keep noticing: compared to programming, accounting often looks like the more automatable problem:It’s rule-based Double entry, charts of accounts, tax rules, materiality thresholds. For most day-to-day transactions you’re not inventing new logic, you’re applying existing rules.It’s verifiable The books either balance or they don’t. Ledgers either reconcile or they don’t. There’s almost always a “ground truth” to compare against (bank feeds, statements, prior periods).It’s boring and repetitive Same vendors, same categories, same patterns every month. Humans hate this work. Software loves it.With accounting, at least at the small-business level, most of the work feels like:normalize data from banks / cards / invoicesapply deterministic or configurable rulessurface exceptions for human reviewrun consistency checks and reportsThe truly hard parts (tax strategy, edge cases, messy history, talking to authorities) are a smaller fraction of the total hours but require humans. The grind is in the repetitive, rule-based stuff.

人工智能编程很吸引人，但会计才是真正的低垂果实自动化目标。