$Stakeholder perspectives on the future of trucking in an automated world

As artificial intelligence (AI) becomes embedded into vehicle automation and fleet operations, the U.S. trucking industry faces opportunities and challenges. These technologies promise safety and efficiency gains, but also raise underexplored questions regarding workforce transitions, training, and regulatory frameworks. This study investigated how stakeholders across the U.S. trucking industry perceive the integration of AI systems, including advanced driver assistance systems (ADAS) and automated commercial motor vehicles (ACMVs), and the implications for safety, operational practices, and workforce adaptation. Semi-structured interviews were conducted with 33 U.S.-based participants representing five stakeholder groups: truck drivers, trucking companies, truck driving schools, technology developers, and policymakers. Data were thematically analyzed and mapped onto the sociotechnical systems framework (environment, organizations, workers, tasks, and tools & technologies). Six themes emerged: (1) Feasibility of AI-Enabled Systems, spanning regulation, training and licensing, infrastructure, and human–technology teaming; (2) Benefits such as increased safety, efficiency, workload balance, and industry appeal; (3) Workforce Impacts related to job availability, role transitions, and satisfaction; (4) Technology Perceptions characterized by trust and skepticism; (5) Industry Practices including recruitment, training, and fleet management; and (6) Innovation involving automation progress, and deployment. Most subthemes were shared across all five groups, while others were raised by a subset or a single group, revealing both convergence and divergence in how stakeholders understand AI integration. Stakeholders identified AI’s potential to improve safety and efficiency, but raised concerns about job displacement, regulatory gaps, and human oversight. This study provides insights for system design, human-technology interaction, training, workforce adaptation and regulatory frameworks.