Innovation Project Selection and Evaluation Using Artificial Intelligence Models and Methods

This article examines the application of artificial intelligence (AI) models and methods in the selection and evaluation of innovative projects. With the increasing complexity of decision-making processes in innovation management, traditional evaluation techniques often fail to ensure objectivity, scalability, and predictive accuracy. The study analyzes machine learning algorithms, decision-support systems, and multi-criteria evaluation models used in project selection. The methodological framework is based on a systematic review of academic literature and empirical findings from recent studies. The results demonstrate that AI-based approaches significantly improve decision quality, reduce uncertainty, and enhance predictive capabilities. The article also discusses the limitations and challenges associated with AI implementation in innovation evaluation processes.

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