AI Resilience Report forBioengineers and Biomedical Engineers

Right now, AI is mostly augmenting biomedical engineers rather than replacing them. The heaviest AI use falls on the tasks that involve lots of data and paperwork — like tracking experiment results and staying up to date on research. In fact, Artificial Intelligence (AI) and computational modelling are jointly reshaping bioengineering and bioinformatics, moving biomedical research from descriptive observation toward predictive, mechanistic, and personalized understanding of living systems, according to a special issue of the IEEE Open Journal of Engineering in Medicine and Biology ^[1].

Engineers are combining machine learning with hybrid, physics-informed models, in-silico clinical trials, and patient-specific digital twins that simulate human structure and function across scales, from molecules and cells to tissues, organs, and whole-body behavior — powerful tools that speed up device design but still need engineers to validate them.

On the device-design side, drug and device developers report that ^[2] AI is also increasingly being used in later stages of development, particularly through digital twins. According to Dr Gen Li, Founder and President at Phesi, 2026 will mark a turning point for their adoption. Documentation-heavy tasks are also being reshaped: the FDA just released a discussion paper ^[3] on considerations for the regulation of generative artificial intelligence (GenAI)-enabled medical devices, seeking feedback from interested parties on risk assessment, premarket evaluation, postmarket monitoring, and other topics, signaling that generative AI is now common enough inside devices to need its own rulebook.

The tasks least touched by AI are the deeply human ones — consulting with chemists and biologists, and designing novel instruments — because they require creativity, judgment, and teamwork.

Adoption is moving quickly, but with guardrails. Economically, medtech companies are under pressure to cut costs: MD+DI reports that ^[4] 9 out of 10 senior HR leaders expect AI to reshape the job market in 2026, as companies face "a general need to cut costs," and that industry veterans warn "The people who are working now are not versatile enough for the future, which is being created by digital health and AI". That's actually good news for students entering the field — labor demand is still strong.

According to the U.S. Bureau of Labor Statistics ^[5], Employment of bioengineers and biomedical engineers is projected to grow 8 percent from 2025 to 2035, much faster than the average for all occupations. About 1,200 openings for bioengineers and biomedical engineers are projected each year, on average, over the decade.

At the same time, legal and ethical guardrails will slow blanket automation. The FDA's new proposed framework for GenAI devices ^[3] is built on a potential approach to premarket evaluation built on the concept of competency assessment, inspired at a high level by how physicians are trained and evaluated, consisting of non-clinical device benchmarking and clinical confirmation to evaluate whether a GenAI-enabled medical device performs as intended before reaching patients. Because patient safety is on the line, human engineers will always be needed to test, document, and defend these systems.

The bottom line: AI is becoming a powerful teammate, and biomedical engineers who learn to work with it — while keeping their skills in biology, ethics, and creative design sharp — will be in high demand.