Abstract:

Engineering practice is undergoing rapid restructuring as AI systems increasingly automate routine analytical, computational, and documentation tasks. Industries now require engineers who can supervise AI pipelines, validate model outputs, perform integrative design, and operate within human–machine collaborative environments. This study proposes a competency-centered curricular model designed to align engineering education with an AI-mediated professional landscape. The proposal is developed through an integrative synthesis of analyses on AI-driven changes in engineering workflows, skills transformation patterns, and emerging educational practices in engineering programs. Based on this analysis, the curriculum is structured around three interrelated transformations that redefine engineering formation. First, applied scientific foundations are reframed to emphasize modeling, simulation, and data analytics as core epistemic tools. Second, engineering practice is reconceptualized as AI-augmented design and decision-making, involving optimization engines, autonomous systems, and generative design environments. Third, professional competencies are foregrounded, with particular emphasis on uncertainty management, ethical judgment, and cross-disciplinary collaboration. The results of the proposed model suggest that engineering education must shift from task-based technical training toward the development of integrative and supervisory capacities. Future engineers will increasingly orchestrate AI systems rather than compete with them. The curriculum framework highlights the relevance of competency-oriented program design for preparing graduates to steer complex socio-technical systems in AI-intensive contexts.

Keywords:

Engineering curriculum, Iceberg index, engineering practice.