Canada’s marine manufacturing ecosystem is approaching a decisive pivot point. As vessel architectures, mission profiles, and sustainability imperatives become more complex, legacy production models are no longer fit for purpose. Artificial Intelligence (AI) and Machine Learning (ML) have moved from experimental to essential, forming the backbone of next-generation competitiveness in high-mix, high-precision marine environments. This presentation delivers a pragmatic, industry-grounded assessment of AI/ML deployment across Canadian marine manufacturing. It focuses on operational domains where measurable value is already being created: predictive maintenance that reduces unplanned downtime, AI-driven defect detection that elevates quality assurance, adaptive process control that stabilizes throughput, and digital twins that enhance lifecycle asset management for vessels and critical components. These technologies are materially shifting cost structures, improving repeatability, and strengthening reliability across platforms that must perform in demanding naval, commercial, and arctic conditions. Leveraging case-based insights - including digital quality assurance initiatives at Rainhouse Manufacturing Canada - we examine how mid-sized firms are overcoming constraints related to aging infrastructure, fragmented data environments, and workforce capacity. The analysis highlights how AI/ML is being integrated with sensors, edge processing, and cloud architectures to unlock traceability, compliance, and leaner production workflows across maritime supply chains. Global exemplars from Europe and East Asia are used to benchmark Canada’s trajectory, underscoring both emerging strengths and critical capability gaps. Particular attention is given to workforce enablement through simulation-driven training, human-machine teaming, and new hybridized technical roles that will define the smart shipyards and component fabrication facilities of the future. The presentation offers a clear, forward-looking blueprint: for Canadian shipbuilders, OEMs, and SMEs, AI and ML adoption is not a discretionary upgrade. It is a mission-critical enabler of industrial resilience, export competitiveness, and sovereign capacity in the Fourth Industrial Revolution.