Systems Engineering Education in the Age of Agentic AI: A Scenario-Based Outlook on Relevant Systems Engineering Skills of the Future

Agentic Artificial Intelligence (AI) is rapidly transforming how systems engineers create engineering artefacts, interact with tools, and manage complexity. This presentation uses a scenario-based approach to explore how the working reality of systems engineers may evolve over the short, mid, and long term, and what this implies for future systems engineering skills and education.
In a short-term scenario, AI primarily lowers barriers to tool interaction by simplifying access and usage. While tool-specific expertise becomes less critical, structured thinking and systems reasoning remain essential. In a mid-term scenario, AI increasingly acts as a content creator, generating requirements, architectures, and analyses that engineers must critically assess, refine, and contextualize. Engineering depth shifts from creation to validation. In a long-term scenario, AI-enabled toolchains orchestrate entire engineering workflows based on stakeholder needs, producing end-to-end results that systems engineers primarily evaluate, govern, and integrate.
Building on these scenarios, the presentation discusses implications for systems engineering education in large industrial environments. Topics include accelerated ramp-up of new engineers, and the growing relevance of orchestrating workflows, critical judgment, intent specification, and socio-technical oversight. The goal is to stimulate discussions on how systems engineering education must adapt to remain effective in an increasingly agentic and non-deterministic engineering landscape.