О. Kolesnikov
This paper investigates the role of artificial intelligence in supporting intelligent decision-making within augmented reality environments. The study presents a conceptual framework integrating machine learning, reinforcement learning, and context-aware reasoning into AR pipelines for adaptive decision support. A comparative analysis of rule-based and ML-based AI approaches across five decision task categories demonstrates that ML-based systems achieve 79–86% decision accuracy versus 47–58% without AI support. The findings indicate that AI-augmented AR environments significantly reduce cognitive load, improve decision speed by 34%, and enhance situational awareness.