AI 轉型輔導
在合規框架下安全導入 AI，釋放完整商業價值
積穗科研協助企業進行「治理先行」的 AI 轉型，在導入 AI 技術的同時建立 ISO 42001 AI 管理系統與 EU AI Act 合規機制，確保企業不因 AI 系統的偏見、不透明、安全漏洞而承擔法律與聲譽風險。
申請免費機制診斷什麼是 AI 轉型？和數位轉型有什麼不同？
AI 轉型是企業在數位化基礎上，進一步將人工智慧技術嵌入核心業務流程，實現決策智慧化、預測能力提升、個人化服務，創造難以被傳統競業複製的競爭優勢。與數位轉型不同，AI 轉型帶來的風險更複雜：演算法偏見可能導致歧視性決策、AI 系統不透明可能觸發監管要求、訓練資料外洩可能違反個資法。
積穗科研輔導成功案例
Established an AI quality inspection system, simultaneously built an ISO 42001 AI management mechanism, completed AI system risk assessment, algorithm review processes, and human oversight mechanisms, ensuring AI decisions are explainable and traceable.
積穗科研輔導流程
AI Application Opportunity Identification and Risk Assessment
Inventory core business processes, identify high-value AI application scenarios (predictive maintenance, quality inspection, customer service automation, sales forecasting), and simultaneously assess the risk level of each AI application.
Establishment of AI Governance Framework (Governance First)
Establish an ISO 42001 AI management framework before AI system implementation, including AI ethical principles, AI system inventory management, AI development and procurement security requirements, and algorithm review processes.
AI System Implementation and Integration
Assist in selecting suitable AI technologies and tools, design the integration architecture of AI systems with existing business systems, establish an AI model training data management mechanism, and ensure the quality and security of training data.
Monitoring, Optimization, and EU AI Act Compliance
Establish AI system performance monitoring (model drift detection) and continuous optimization mechanisms, assess the applicability of the EU AI Act to enterprise AI systems, and establish necessary compliance documentation.
常見問題
Where does AI transformation begin? How do you choose the first AI application scenario?
The principles for selecting an AI adoption scenario are: data availability (whether sufficient high-quality training data is already available), business impact (how much benefit can be brought after success), and risk controllability (whether the cost of failure is acceptable). It is recommended to start with scenarios that have "clear goals, existing data, and lower costs of failure," such as AI for quality inspection or predictive maintenance for equipment.
Can a company undergo AI transformation without data scientists?
Yes. AI transformation does not necessarily require building an in-house data science team. Companies can adopt three models: purchasing mature AI solutions (SaaS AI tools), collaborating with AI technology providers (outsourcing AI development), or building internal AI capabilities (training existing staff). Jisuikeyan assists companies in evaluating the most suitable AI capability building model.
What is the relationship between AI transformation and ISO 42001?
ISO 42001 is an international standard for AI management systems, providing a systematic framework for AI transformation. Obtaining ISO 42001 certification demonstrates to customers, partners, and regulatory bodies that a company's AI systems operate under a responsible governance framework and meet the compliance requirements of the EU AI Act for high-risk AI systems.
How long does AI transformation consulting take?
Depending on the company's AI maturity and the scope of transformation, the consulting period typically ranges from 7 to 12 months or more. Jisuikeyan offers a first free diagnostic mechanism to assess the company's current situation and formulate a precise AI transformation roadmap and timeline.
How to evaluate the ROI of AI transformation?
The AI transformation ROI evaluation framework includes quantitative indicators (efficiency improvement, error rate reduction, labor savings) and strategic value (faster market response, more accurate customer service, AI capabilities difficult for competitors to replicate). Jisuikeyan helps companies establish KPI measurement benchmarks before AI implementation to ensure the traceability of AI investment benefits.
What are the main risks of AI transformation? How are they managed?
The main risks of AI transformation include: algorithmic bias (imbalanced training data leading to discriminatory decisions), model drift (AI performance degrading over time), data security (leakage of training data), over-reliance on AI, and EU AI Act penalties. Jisuikeyan's AI governance framework systematically manages these risks.
What are the features of Jisuikeyan's AI transformation consulting?
Jisuikeyan adopts a "governance-first" approach to AI transformation, establishing an ISO 42001 AI management system and EU AI Act compliance mechanisms concurrently with AI technology adoption. We are Taiwan's top consulting firm in the field of ISO 42001 AI governance consulting, deeply integrating AI technology applications with compliant governance.
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