Will AI Make Your Medical Device Obsolete Before It Hits the Market?
Worried AI will make your medical device obsolete? Discover why traditional devices remain viable—and learn how to incorporate AI in your development process.
Every medical device entrepreneur has been there—you’re in the midst of development, navigating the complex process of bringing your idea to life, when you see another “AI in healthcare” headline. The questions start flooding in: Will AI make my device obsolete? Should I pivot to AI now? Am I too late?
These are fair questions. The pace of AI in healthcare is incredible, with new applications popping up daily. For medical device innovators investing years and significant dollars into development, the fear of being left behind by AI technology is crippling.
But here’s the truth: AI is changing healthcare, but it’s not making traditional medical devices obsolete. In fact, understanding where AI is in medical devices right now will give innovators a sense of relief in their development timelines.
The State of AI in Medical Devices
Let’s look at where AI is actually at in medical devices. The FDA has approved over 1,000 AI-enabled medical devices to date—a big number that might seem scary at first. But dig deeper, and you’ll see that these approvals are concentrated in a few areas, mostly radiology and cardiology.
Why these areas? The answer is in the nature of these fields. Radiology and cardiology deal with image and pattern recognition—tasks that are AI’s sweet spot. MRI analysis, CT scan interpretation, and ECG rhythm assessment are perfect applications for machine learning algorithms because they involve processing huge amounts of standardized visual or waveform data.
But if you step outside these areas, the picture changes fast. AI integration in other types of medical devices is limited. We’re seeing interesting developments in hearing aids and sound-processing devices, but most medical devices don’t have AI at their core. It’s not because there isn’t innovation—it’s because many medical devices solve problems that don’t require AI to work.
Think of devices like insulin pumps, surgical instruments, or orthopedic implants. These may eventually benefit from AI, but their core function relies on mechanical, chemical, or biological mechanisms. The value they provide isn’t dependent on AI, and in many cases, adding AI would only complicate the device and its regulatory pathway.
And the transition to AI-enabled devices in new areas will be gradual. Unlike software updates in consumer tech, medical device changes require extensive testing and validation to ensure patient safety. This slow pace is necessary—and it’s a stable environment for current device development.
The Regulatory Reality
When it comes to AI in medical devices, the regulatory landscape tells a story—and it’s a good one for device developers. The FDA has been open to AI-enabled devices but also cautious. This slow pace is for public safety and your development timeline.
Consider the FDA’s recent draft guidance for AI-enabled medical devices. This is progress but also shows the complexity of AI in regulated medical devices. The FDA must ensure that AI-enabled devices are safe and effective throughout their lifecycle, including after AI models have been updated or retrained. This is a new regulatory challenge that will take years to work through.
For traditional medical device developers, this is a development window. Even as AI technology moves fast, the FDA’s review process ensures that any AI-enabled competing devices will go through the same scrutiny as your device. We can only hope the FDA uses AI to speed up its review process, but that’s probably years away as they’ll need to validate that it doesn’t compromise public safety.
Think of it this way: software companies can push AI updates weekly, but medical device manufacturers must validate every change. A simple AI update to an existing device could take months or years of testing and documentation. This isn’t bureaucratic red tape—it’s patient safety.
At Concise Engineering, we’ve seen many new engineering firms entering the space post-COVID, wanting to add AI to their devices. However, they underestimate the regulatory complexity this adds to their project. What seems like a simple AI feature can add months or years to development and make the path to market approval much harder.
This doesn’t mean you should never add AI to your device. It means you should be strategic about when and how you do it. The key is to know where AI adds value to your device’s core function versus where it just adds complexity.
Strategic Opportunities
AI might not be the core of your device’s function, but it can still be valuable in your development process. The key is to find strategic opportunities where AI can help—rather than complicate—your path to market.
First, consider how AI can support your development process without being part of your final product. Today’s AI tools can help with documentation prep, generate initial design concepts, and even support risk analysis. These can speed up your development timeline without adding regulatory complexity to your device.
For example, AI can help with documentation by drafting initial versions of standard operating procedures, testing protocols, or user manuals. Human experts will always need to review and refine these documents, but AI can speed up the first draft stage. AI visualization tools can also help you explore design variations quickly during early conceptualization phases.
If you are adding AI to your device itself, focus on areas where it provides clear, measurable benefits. The most successful AI integrations in medical devices typically fall into:
Image processing and analysis (like in radiology apps)
Sound processing and filtering (like in advanced hearing aids)
Pattern recognition in physiological data (like cardiac monitoring)
Predictive maintenance and device optimization
But remember adding AI should solve a specific problem or improve device performance. We’ve seen many startups add AI because they think it will attract investors. This approach usually backfires and adds development cost and time without proportional benefit.
At Concise Engineering, we recommend asking three questions before adding AI to your device:
Does AI improve patient outcomes more than traditional approaches?
Can you validate and document the AI’s decision-making process to meet regulatory requirements?
Does the benefit of AI outweigh the added complexity in development and approval?
The device manufacturers we work with that are most successful use AI strategically—not as a core feature but as a tool to enhance parts of their device or development process. This balanced approach allows them to benefit from AI while keeping a clear path to market.
Looking Ahead
The future of medical devices is about knowing when and how to use AI. Looking ahead, we expect to see a gradual and thoughtful integration of AI into medical devices over the next 10 years—not the overnight revolution many fear.
For device manufacturers, this means you have time to focus on what matters most—solving real medical problems. While AI will continue to evolve, the fundamental needs of healthcare providers and patients will remain constant. A well-designed device that solves those needs will remain valuable regardless of AI trends.
That being said, staying up to date with emerging technologies is important. We expect to see AI impact several areas in the next few years:
Drug development and testing
Organ-on-a-chip technology
Biological modeling and simulation
Manufacturing optimization
Quality control processes
These will improve how we develop and manufacture devices before they change the devices themselves. This gives you an opportunity to improve your development process without changing your core device design.
The Takeaway
It’s understandable to fear being left behind by AI, but that fear shouldn’t freeze your development. The medical device industry’s regulatory framework and focus on patient safety means valuable innovations will find a place in the market, whether they have AI or not. Remember: being successful is more important than being first. By solving real medical problems and staying up to date with emerging technologies, you can create a device that will last regardless of what AI does.
Instead of worrying about AI making your device obsolete, focus on solving your target medical problem. If you’re not sure how emerging technologies will impact your development timeline or want to explore how to use AI in your process, we can help. Contact our team at Concise Engineering to talk about your device and development strategy.
Justin Bushko
President, Concise Engineering
Next Steps
We hope you find this newsletter valuable and insightful.
If you have any questions, if you have feedback or would like to explore any specific topics further, please feel free to reach out to us.
Please email me at jbushko@concise-engineering.com or to book a call with me, click this link.
Stay tuned for future editions where we'll continue to share valuable information and industry updates.