Generative AI is changing medical device engineering in ways that extend beyond productivity. At HiArc, engineers are using AI to automate routine work while gaining the confidence and time to address technical challenges they might previously have avoided, tells Design News.
AI is particularly effective for well-defined tasks such as creating documentation, developing test plans, and writing scripts for instrument testing. In regulated medical device development, these activities consume substantial engineering resources. HiArc is exploring continuous compliance, using AI to generate draft documentation alongside software development. This reduces the delay between completed functionality and the documentation required to support it.
Engineers are also using AI to create new development tools. HiArc has experimented with SysML 2.0, an open systems modeling standard with a relatively limited tooling ecosystem. Rather than relying entirely on expensive proprietary products, engineers are building AI agents that generate diagrams from standardized system models.
Another pilot involved creating a generalized timing simulator for medical instruments. AI helped engineers develop the application in about half the time required by conventional methods. The resulting simulator can be adapted across products and expanded with visualizations showing the movement of chemicals through an instrument.
Despite these benefits, human judgment remains essential. Medical devices operate within tightly regulated environments where accountable people must make decisions. AI therefore serves as decision support rather than an autonomous decision maker. Existing safeguards, including testing, independent peer review, and quality assurance, can also be applied to AI-generated work.
As AI becomes more accessible, critical thinking may become increasingly important for engineers. They must understand when to trust AI, when to question its output, and how to validate designs rigorously.
The article argues that AI’s greatest contribution may not be simply completing existing work faster. Its larger value lies in enabling engineers to attempt more ambitious projects while preserving the expertise, judgment, and understanding required for responsible medical device development.
