Seizing the Agentic Advantage: The Use Cases Rewiring Digital Engineering

Engineering organizations are approaching a new phase of digital transformation in which agentic AI systems could extend beyond basic content and coding assistance to coordinate end-to-end engineering workflows across CAD, CAE, PLM, simulation, testing, manufacturing, and business operations. Rescale argues that early adopters can create a compounding advantage by capturing institutional knowledge, reducing iteration costs, and accelerating learning across programs, provided agents are grounded in company-specific engineering practices, solver preferences, quality standards, and review processes. Proposed uses include automating simulation studies and surrogate-model development, coordinating multi-physics analyses, identifying the downstream effects of design changes, assessing compliance and design quality, correlating simulation with physical tests, generating RFQ responses, detecting manufacturing risks, and supporting life-sciences and chemical scale-up. The approach relies on an engineering knowledge layer, workflow orchestration tools, integrations with engineering software and computing resources, and built-in governance such as approval gates, audit trails, domain-specific evaluation, and human oversight. Rather than immediately pursuing full autonomy, organizations are encouraged to begin with a high-value, measurable workflow and gradually expand delegation as confidence in agent performance grows.

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