This research investigates the strategic integration of artificial intelligence (AI), human intelligence (HI), and blockchain technology as enablers of agribusiness model innovation (ABMI) aimed at achieving net-zero carbon transitions. Utilizing Actor-Network Theory (ANT) as the analytical framework, the study explores how these technologies function as pivotal actors to overcome traditional limitations in agribusiness, including inefficiencies in resource management, inadequate transparency, and challenges in carbon accounting. A pseudonymous Taiwanese agribusiness, referred to as “AgriNPUST,” serves as the central case study to illustrate the transformative potential of these integrations. The findings outline three distinct pathways for leveraging AI and blockchain within ABMI: auxiliary acts, where AI enhances HI by automating repetitive or data-intensive tasks; autonomous acts, where AI independently manages complex operations, such as optimizing supply chain logistics; and enhanced acts, where AI, HI, and blockchain work collaboratively within decentralized ecosystems to drive innovation and sustainability. Blockchain emerges as a cornerstone, ensuring transparency, traceability, and trust through the creation of immutable records for carbon accounting and supply chain management. A three-phase process model is proposed, comprising problem identification, interest reconstruction, and ecosystem establishment, demonstrating the synergistic role of AI and blockchain in enabling systemic innovation. The study underscores the importance of blockchain in fostering stakeholder collaboration, enhancing compliance with carbon neutrality goals, and scaling sustainable solutions. By combining theoretical insights with practical recommendations, this research highlights the role of emerging technologies in reshaping agribusiness practices.