The rapid development of generative AI systems such as ChatGPT has intensified interest in artificial intelligence (AI) across business and industry. Yet, selecting suitable AI algorithms remains challenging, particularly for non-experts facing a complex methodological landscape. This paper introduces the AI-Compass, a structured framework that guides users in selecting appropriate AI algorithms based on functional paradigms (e.g., clustering, anomaly detection, NLP) rather than learning methods. By combining functional classification with paradigm-specific decision diagrams, the AI-Compass offers a transparent, traceable process for algorithm selection. The framework aims to help close the gap between theoretical AI models and industrial practice, enabling data-driven decision-making even for non-specialists.
AI-Compass: Functional Paradigm-Based Algorithm Selection Framework
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