Agriculture’s “4.0” transition increasingly relies on artificial intelligence (AI), IoT sensing, robotics, and decision-support. This review synthesizes Q1/Q2 scholarship, multilateral policy, and national AI strategies to assess how AI is changing farm stewardship and what guardrails align innovation with equity and sustainability. Methods combine a systematic literature review, comparative policy analysis (FAO, OECD, India’s #AIForAll, Rwanda AI Policy), NLP-assisted meta-synthesis of agri-AI discourse, theological analysis of stewardship texts (Gen. 1:26–28, Gen. 2:15), and case illustrations (precision irrigation, UAV spraying, mobile advisory). Results show AI improves resource-use efficiency and foresight (e.g., precision irrigation; targeted drone spraying) while introducing risks of dependency, opacity, and data-extractive business models. We propose a multi-level governance scaffold—farmer-centric data rights, explainability thresholds, context-appropriate human oversight, and compute-energy budgeting—mapped to Responsible Innovation (AIRR) and Value-Sensitive Design. We translate stewardship into measurable design constraints (e.g., water-withdrawal and biodiversity “red lines,” local-language interfaces, offline capability). Policy implications include numbered-style impact assessments, mandatory farmer representation on regional AI councils, and adoption equity metrics. Properly governed, AI can act as a tool of care for households, communities, and creation rather than a driver of technocratic consolidation.