Reasoning Across Engineering Artifacts with AI
Scaling Expert Systems Thinking in Medical Device Development
📅 INCOSE Healthcare Conference 2026 · April 28-30, Minneapolis, MN
For systems, software & quality engineering teams in medtech
Why this session matters
Medical device development requires consistent reasoning across interconnected artifacts—requirements, risk controls, and verification—spanning hardware, firmware, and software. As systems grow, maintaining alignment between design intent, ISO 14971 risk controls, and verification evidence becomes increasingly difficult.
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Experienced systems engineers manage this by reasoning across abstraction layers—decomposing requirements, identifying implicit risk controls, and ensuring verification covers both normal and edge conditions. This expertise is largely tacit and hard to scale.
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This session presents an AI-assisted approach using structured, multi-dimensional representations of engineering artifacts—linking system hierarchy, behavior, hazards, and verification—to enable cross-artifact reasoning at scale.
What you will learn
Using medical device examples, we show how it can:
- Generate design artifacts aligned with best practices
- Detect inconsistencies across requirements
- Surface missing or implicit risk controls
- Evaluate verification coverage
- Identify gaps across requirements, risk, and testing
Attendees will learn how AI can “reason across engineering artifacts”—not just generate content—to scale expert-level systems thinking in complex, regulated environments.
