這門學科叫 AI 實施科學（AI Implementation Science）。它脱胎於醫學界過去 20 年的 Implementation Science——研究「為什麼有效的東西沒被用起來」。 AI Implementation Science is the discipline. It descends from medicine's twenty-year-old Implementation Science—the study of why effective things don't get used.
Klarna 砸了 4000 萬美元給 OpenAI 做 AI 客服，一年後退回人機混合。麥當勞跟 IBM 做 AI 點單，三年後全部撤掉。不是技術不行，模型每代都在漲。是 benchmark 上能做的事情，企業裏做不成。中間那條鴻溝，模型公司不解決，諮詢公司沒工具。 Klarna spent $40M on OpenAI customer service. One year later, they walked it back. McDonald's pulled IBM AI ordering after three years. The technology works—models get smarter every quarter. The gap is the distance between benchmark and production. Model companies don't close it. Consultancies don't have the tools.
20 年前醫學界遇到過一模一樣的情況：大量臨牀試驗證明藥有效，但醫生不按指南開藥，病人不按處方吃藥。一條循證實踐從論文走到臨牀，平均要 17 年。醫學界的解法叫 Implementation Science。今天那門學科還活着，120 多個研究中心，幾千篇頂會論文。 Twenty years ago, medicine faced the same problem: clinical trials proved drugs worked, but doctors didn't follow guidelines and patients didn't follow prescriptions. Translating evidence from paper to bedside took 17 years on average. Medicine's answer was Implementation Science. The discipline lives—120+ research centers, thousands of peer-reviewed papers.
我們要做的，是把那套方法搬到 AI 上，加上 AI 特有的部分——模型漂移、角色模糊、監管月級變化。 Our work is to bring that method to AI, plus what AI uniquely needs—model drift, role ambiguity, monthly regulatory shifts.
回答 19 個問題，系統會按五個維度檢查你的業務：AI 是否適合、外部限制、內部流程、人員準備和實施條件。 Answer 19 questions. The system checks your business across five dimensions: AI fit, external constraints, internal workflows, people readiness, and implementation conditions.
完成後立即看到五維分數、主要瓶頸、優先場景和 30 天行動建議。基礎結果免費。 See your five-dimension scores, bottlenecks, priority scenarios, and a 30-day action plan immediately. The basic result is free.
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