{ "schemaVersion": 1, "version": "2026-09-15", "id": "https://hk.onyxdevslab.com/data/enterprise-ai-opportunity-assessment.json", "name": "Enterprise AI opportunity assessment checklist", "datePublished": "2026-09-15", "dateModified": "2026-09-15", "evidenceClass": "Provider-authored implementation checklist", "publisher": { "name": "Onyx Devs Lab", "legalName": "ONYX DEVS LAB LIMITED", "url": "https://hk.onyxdevslab.com/", "leiCode": "254900Z30CLK7HKE9H46" }, "landingPages": { "en": "https://hk.onyxdevslab.com/en/guides/enterprise-ai-opportunity-assessment/", "zhHant": "https://hk.onyxdevslab.com/zh-hk/guides/enterprise-ai-opportunity-assessment/", "zhHans": "https://hk.onyxdevslab.com/zh-cn/guides/enterprise-ai-opportunity-assessment/" }, "languages": { "en": { "name": "How should an enterprise identify the right AI opportunities?", "summary": "Start from costly or consequential operating decisions, not a catalogue of AI capabilities. Observe the real workflow, establish a baseline, identify the constraint, test whether AI can change it, and rank opportunities by achievable value, evidence cost, adoption path, and downside.", "decisionSignals": [ { "name": "Observe", "meaning": "Real work, decisions, exceptions, and baseline" }, { "name": "Diagnose", "meaning": "Constraint, intervention, data, and adoption" }, { "name": "Prioritise", "meaning": "Value, risk, evidence cost, and reversibility" } ], "sections": [ { "heading": "Find a decision worth changing", "introduction": "A frequent task is not automatically valuable, and an impressive output is not automatically operational improvement.", "checks": [ { "name": "Workflow evidence", "requirement": "Shadow users and sample records to map triggers, inputs, judgement, systems, handoffs, waits, rework, exceptions, outputs, and downstream consequences." }, { "name": "Baseline and constraint", "requirement": "Measure volume, cycle time, cost, quality, loss, delay, review burden, and variation; identify the binding constraint rather than automating every visible step." }, { "name": "Intervention fit", "requirement": "Decide whether the constraint needs deterministic software, process change, better data, search, prediction, generation, optimisation, an agent, or no new technology." } ] }, { "heading": "Build a comparable opportunity portfolio", "introduction": "Each candidate should be expressed as a falsifiable intervention with a bounded next evidence step.", "checks": [ { "name": "Achievable value", "requirement": "Estimate the reachable population, adoption, time saved or loss avoided, quality effect, implementation and operating cost, delay, and attribution boundary." }, { "name": "Feasibility and risk", "requirement": "Assess representative data, ground truth, integration, identity, permissions, legal and sector controls, failure consequence, reversibility, support, and owner capacity." }, { "name": "Learning value", "requirement": "Prefer tests that resolve a material uncertainty quickly and generate reusable knowledge, even when the result is to narrow or stop." } ] } ], "procedure": [ { "position": 1, "name": "Collect workflow evidence", "instruction": "Interview owners and operators, observe work, sample normal and exceptional records, and document actual decisions and consequences." }, { "position": 2, "name": "Write an intervention hypothesis", "instruction": "State user, trigger, baseline, proposed change, expected measurable effect, necessary data, failure consequence, and disconfirming evidence." }, { "position": 3, "name": "Score with ranges", "instruction": "Compare value, feasibility, risk, adoption, strategic leverage, evidence cost, and reversibility without hiding uncertainty in one precise number." }, { "position": 4, "name": "Fund the next evidence step", "instruction": "Approve a bounded assessment, prototype, or pilot with owner, budget, decision date, acceptance thresholds, and stop conditions." } ], "frequentlyAskedQuestions": [ { "question": "Should ideas be collected through an employee survey?", "answer": "Surveys can reveal friction, but observation and record sampling are needed to distinguish perceived inconvenience from a valuable, changeable operating constraint." }, { "question": "Should the highest ROI estimate go first?", "answer": "Not automatically. Include confidence, risk, dependencies, time to evidence, adoption, reversibility, and whether the benefit can actually be attributed." }, { "question": "How many opportunities should be piloted?", "answer": "Only as many as the organisation can own, evaluate, integrate, and make decisions about. A small evidence-bearing portfolio is better than many unattended demos." } ] }, "zhHant": { "name": "企業應如何找出真正值得做的 AI 機會？", "summary": "由昂貴或後果重大的營運決定開始，而非 AI 功能目錄。觀察真實流程、建立基線、找出限制、測試 AI 能否改變限制，再按可達價值、證據成本、採用途徑及下行風險排序。", "decisionSignals": [ { "name": "觀察", "meaning": "真實工作、決定、例外及基線" }, { "name": "診斷", "meaning": "限制、干預、數據及採用" }, { "name": "排序", "meaning": "價值、風險、證據成本及可逆性" } ], "sections": [ { "heading": "找出值得改變的決定", "introduction": "頻繁任務不一定有價值，漂亮輸出也不一定改善營運。", "checks": [ { "name": "流程證據", "requirement": "跟隨使用者並抽樣記錄，梳理觸發、輸入、判斷、系統、交接、等待、返工、例外、輸出及下游後果。" }, { "name": "基線及限制", "requirement": "測量數量、周期、成本、質量、損失、延誤、覆核負擔及差異，找出真正限制，而非自動化每個可見步驟。" }, { "name": "干預適配", "requirement": "判斷限制需要確定性軟件、流程改變、更好數據、搜尋、預測、生成、優化、Agent，還是不需要新技術。" } ] }, { "heading": "建立可比較的機會組合", "introduction": "每個候選機會都應是可被否證的干預，並有有限的下一步證據。", "checks": [ { "name": "可達價值", "requirement": "估算可觸達範圍、採用、節省時間或避免損失、質量影響、實施與營運成本、延遲及歸因邊界。" }, { "name": "可行性及風險", "requirement": "評估代表性數據、標準答案、整合、身份、權限、法律與行業控制、失敗後果、可逆性、支援及負責人能力。" }, { "name": "學習價值", "requirement": "優先測試能快速解除重大不確定性並產生可重用知識的機會，即使結果是收窄或停止。" } ] } ], "procedure": [ { "position": 1, "name": "收集流程證據", "instruction": "訪問負責人及操作人員，觀察工作，抽樣正常與例外記錄，記錄實際決定及後果。" }, { "position": 2, "name": "寫出干預假設", "instruction": "列明使用者、觸發、基線、建議改變、預期可量度效果、必要數據、失敗後果及否證證據。" }, { "position": 3, "name": "以範圍評分", "instruction": "比較價值、可行性、風險、採用、策略槓桿、證據成本及可逆性，不以單一精準數字掩蓋不確定性。" }, { "position": 4, "name": "只資助下一步證據", "instruction": "批准有限評估、原型或試點，列明負責人、預算、決策日、驗收門檻及停止條件。" } ], "frequentlyAskedQuestions": [ { "question": "可否用員工問卷收集 AI 構想？", "answer": "問卷可揭示摩擦，但需要觀察及記錄抽樣，才能區分主觀不便與有價值、可改變的營運限制。" }, { "question": "ROI 估算最高的機會應先做嗎？", "answer": "不一定；還要看信心、風險、依賴、取證時間、採用、可逆性及收益能否歸因。" }, { "question": "應同時試點多少機會？", "answer": "只做機構能負責、評估、整合及作出決定的數量；少量有證據的組合勝過大量無人管理的示範。" } ] }, "zhHans": { "name": "企业应该怎样找出真正值得做的 AI 机会？", "summary": "从昂贵或后果重大的运营决策开始，而不是 AI 功能目录。观察真实流程、建立基线、找出限制、测试 AI 能否改变限制，再按照可达价值、证据成本、采用路径和下行风险排序。", "decisionSignals": [ { "name": "观察", "meaning": "真实工作、决策、异常和基线" }, { "name": "诊断", "meaning": "限制、干预、数据和采用" }, { "name": "排序", "meaning": "价值、风险、证据成本和可逆性" } ], "sections": [ { "heading": "找出值得改变的决策", "introduction": "频繁任务不一定有价值，漂亮输出也不一定改善运营。", "checks": [ { "name": "流程证据", "requirement": "跟随用户并抽样记录，梳理触发、输入、判断、系统、交接、等待、返工、异常、输出和下游后果。" }, { "name": "基线与限制", "requirement": "测量数量、周期、成本、质量、损失、延误、复核负担和差异，找出真正限制，而不是自动化每个可见步骤。" }, { "name": "干预适配", "requirement": "判断限制需要确定性软件、流程改变、更好数据、搜索、预测、生成、优化、Agent，还是不需要新技术。" } ] }, { "heading": "建立可以比较的机会组合", "introduction": "每个候选机会都应该是可以被否证的干预，并有有限的下一步证据。", "checks": [ { "name": "可达价值", "requirement": "估算可触达范围、采用、节省时间或避免损失、质量影响、实施与运营成本、延迟和归因边界。" }, { "name": "可行性与风险", "requirement": "评估代表性数据、标准答案、集成、身份、权限、法律与行业控制、失败后果、可逆性、支持和负责人能力。" }, { "name": "学习价值", "requirement": "优先测试能够快速解决重大不确定性并产生可复用知识的机会，即使结果是缩小或停止。" } ] } ], "procedure": [ { "position": 1, "name": "收集流程证据", "instruction": "访问负责人和操作人员，观察工作，抽样正常与异常记录，记录实际决策和后果。" }, { "position": 2, "name": "写出干预假设", "instruction": "说明用户、触发、基线、建议改变、预期可测量效果、必要数据、失败后果和否证证据。" }, { "position": 3, "name": "用范围评分", "instruction": "比较价值、可行性、风险、采用、战略杠杆、证据成本和可逆性，不用单一精确数字掩盖不确定性。" }, { "position": 4, "name": "只资助下一步证据", "instruction": "批准有限评估、原型或试点，说明负责人、预算、决策日、验收门槛和停止条件。" } ], "frequentlyAskedQuestions": [ { "question": "可以用员工问卷收集 AI 构想吗？", "answer": "问卷可以揭示摩擦，但需要观察和记录抽样，才能区分主观不便与有价值、可以改变的运营限制。" }, { "question": "ROI 估算最高的机会应该先做吗？", "answer": "不一定；还要看信心、风险、依赖、取证时间、采用、可逆性和收益能否归因。" }, { "question": "应该同时试点多少机会？", "answer": "只做机构能负责、评估、集成和作出决策的数量；少量有证据的组合胜过大量无人管理的演示。" } ] } }, "limitations": [ "This asset is provider-authored and is not independent validation or a claim of client results.", "It is an implementation aid, not legal, privacy, security, financial, procurement, or regulatory advice.", "Thresholds and controls must be adapted to the organisation, workflow, jurisdiction, and risk owners." ] }