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This study introduces and confirms a novel architectural framework for integrating AI into intelligent commerce, specifically showing its transformative impact on the financial, retail, and supply chain sectors. Moving beyond a conceptual review, we propose the \\\"Data Nervous System\\\" framework and outline a quantitative method for its empirical evaluation. This framework positions AI as a dynamic \\\"data nervous system\\\" that ingests real-time signals, augments human decision-making, and drives strategic outcomes. We address the prevalent fear of AI as a replacement by presenting a nuanced perspective: AI’s primary role is augmentation, yielding significant business outcomes such as a 31% increase in retail sales conversions, a 200% improvement in fraud detection accuracy, and a 40% reduction in excess inventory. This research shows key challenges to AI adoption, including poor data quality, legacy infrastructure, and ethical concerns like bias and transparency. The findings support the conclusion that AI is a transformative enabler of adaptive systems in commerce, contingent upon strong data governance and a human-centered design approach to foster synergistic human-AI collaboration.