AI Innovation Architecture: A Systems Approach

This article presents a comprehensive approach to designing an AI-based innovation architecture. It emphasizes that AI, like electricity, is a new critical infrastructure, and its implementation requires systematic planning to avoid common pitfalls and deliver real business value. It discusses key methodologies and tools, such as Google Ventures' Sprint, SZI-PB, and the PDCA cycle, which support iterative development and rapid experimentation. The author emphasizes the importance of precise performance measurement using KPIs, maturity audits, and risk management, including ethical aspects. The goal is to build stable and cost-effective AI systems that truly drive digital transformation.