AI has surpassed one billion users and is now embedded across major industries, yet critical risks continue to need resolution. This course examines AI’s current trajectory, including its rapid adoption, six major sector impacts, and six structural obstacles that limit its safe and scalable deployment. Through a live production case study, learners explore how blockchain infrastructure can enable verifiable, accountable, and secure AI systems, and how these capabilities support the emerging economy of autonomous agents.
Course overview
Understand AI’s promise, including its six critical sector impacts, alongside the six major obstacles currently limiting its ability to scale safely and reliably.
Analyze the regulatory and competitive landscape, including the implications of upcoming frameworks such as the EU AI Act and increasing enterprise pressure to implement verifiable AI systems.
Identify how blockchain capabilities map directly to AI challenges, including immutable logging for auditability, zero-knowledge proofs for verifiable computation, decentralized identity for agent authentication, and smart contracts for automated execution.
Evaluate a live production case study of the Masumi Network, including its architecture, transaction model, and real-world performance metrics.
Assess why Cardano’s EUTXO model, deterministic execution, and native asset support provide a technically robust foundation for agent-based AI systems.
Examine the projected emergence of autonomous AI agents, estimated to reach 1.3 billion actors by 2028, and the infrastructure required to support trustless machine-to-machine interactions.
Determine how organizations can translate these insights into actionable strategies for integrating blockchain within AI-driven initiatives.