In AI project practice, specific requirement blocks often emerge that go beyond traditional functional, non-functional, or purely data-related categories. Key areas include Data & Data Quality, Model & Algorithms, Integration & Operations, Users & Domain, and Security & Ethics. Each of these categories brings unique challenges that should be addressed early in the project. Data & Data Quality AI thrives… Continue Reading Key Requirement Categories in AI Projects
For years, Spirit in Projects has supported companies and public sector clients in designing, tendering, and implementing AI systems. One thing has been consistently confirmed: A structured, data-driven, and value-oriented process model is the key to success—regardless of whether the project follows V-Modell XT, Scrum, or a custom hybrid approach.Many AI projects fail not because of the technology,… Continue Reading Requirements for AI Systems: How a Well-Designed Process Model Leads Projects to Success
At Spirit in Projects, we have spent years helping companies define requirements for complex IT systems and professionally prepare tenders. In recent years, a clear trend has emerged: Artificial intelligence (AI) is being integrated into more and more projects—and brings with it unique challenges. When it comes to AI systems, defining the right requirements from the outset is… Continue Reading Requirements for AI Systems: Why They Differ from Classical Software Systems
