Information Preservation Theory: Intent Preservation and Information Decay Reduction in Artificial Intelligence

Artificial intelligence is often described as a tool for automation, productivity, and optimization. This paper proposes a different interpretation: AI derives much of its value from suppressing information decay between intent, observation, and execution. Across software development, financial markets, industrial systems, and logistics networks, valuable actionable information is continuously lost through communication barriers, cognitive limitations, processing delays, and environmental complexity. Using Persistence Science and the Odero Axiom, this paper models such losses as a form of system decay. It argues that artificial intelligence functions as an information preservation mechanism by transforming human intent and environmental signals into executable actions before their value degrades. Vibe coding serves as a primary example, where natural-language intent is converted directly into software artifacts with reduced actionable-information loss. Organizational knowledge preservation, scientific discovery, AI trading, cybersecurity, predictive maintenance, and logistics are presented as manifestations of the same principle. The paper introduces Information Preservation Theory and defines actionable-information decay as the loss of information capable of producing a system response. An Information Preservation Ratio is proposed to quantify retained actionable information, together with a general relationship linking preserved actionable information to AI-generated value. The framework further connects actionable-information decay to the broader Decay Index architecture of Persistence Science. The resulting theory suggests that a substantial component of artificial intelligence value arises from preserving actionable information between intent, observation, decision, and execution. The framework predicts that domains characterized by high levels of information decay, communication complexity, and decision latency will exhibit the greatest returns from artificial intelligence adoption.