As automation-equipped (Advanced Driver Assistance Systems and Automated Driving Systems) trucks progress toward deployment, they introduce changes to safety management, human-truck interaction, and workforce sustainability. Yet despite this rapid development, there is limited data on the perspectives of different stakeholders affected by trucking automation. 

To address this gap, we convened a multistakeholder workshop at the 2025 AAA Foundation for Traffic Safety's Safe Mobility Conference, examining the current state of trucking automation by analyzing human-technology interaction and workforce training needs. Using Braun and Clarke's six-phase framework, we conducted a thematic analysis on audio recordings and participant notes from 11 stakeholders.

Four themes and nine subthemes emerged from the data. Our findings show that trust in AI systems evolves with experience and driving conditions, and that misaligned training, expertise, and regulation introduce risks such as cognitive overload and skill erosion. Driver responsibilities are also shifting from vehicle operation to automation supervision, with uneven impacts across industry sectors. Coordinated investment, driver-centered design, and structured certification pathways are still needed to build the conditions for safe human-AI teaming. We recommend systemic policy and training changes that consider truckers' perspectives, differences between small and large companies, changes in the workforce, and the misalignment and risks of implementing technologies to support the efficiency and safety of automation-enhanced truck use. Our research will help improve the safety in human-system interactions, inform technology, training, and workforce transition recommendations, and inform policy design for improving the future of trucking automation.