The integration of artificial intelligence with blockchain-based smart contracts addresses fundamental limitations of traditional deterministic contract execution. While smart contracts have enabled trustless automation on blockchain networks, they remain inflexible when confronted with dynamic real-world conditions. This article proposes an AI-enhanced smart contract architecture focusing on three key applications: AI-assisted resolution of resource usage disputes, energy-efficient transaction scheduling to minimize the blockchain carbon footprint, and automated environmental compliance verification. Implementations demonstrate the technical feasibility through Solidity-based smart contracts interfacing with AI oracles that bridge on-chain execution with off-chain intelligence. Privacy-preserving mechanisms are further developed using zero-knowledge proofs to maintain data confidentiality while enabling AI-powered decision-making. Despite significant potential benefits, several challenges are identified, including oracle vulnerabilities, AI model reliability and bias, computational overhead, and regulatory considerations. This research contributes to the advancement of decentralized governance by creating more intelligent, adaptable, and secure smart contract ecosystems, with applications spanning decentralized finance, supply chain management, and legal frameworks. Future directions include decentralized AI model training, enhanced privacy-preserving techniques, and the development of appropriate regulatory frameworks to support widespread adoption. This framework offers a pathway for more efficient economic management of natural resources and transparent carbon trading markets.