By Garrett Seeley
About a year ago, I had the opportunity to attend the MD Expo in Dallas. If you’ve never attended an MD Expo, I highly recommend doing so. These conferences offer a chance to engage with industry leaders, discover emerging trends and see firsthand what innovations are coming to HTM. In my experience, there’s no better way to learn about the “next big thing” shaping our industry. Over the past year, the buzzword dominating the expo floor has been “AI.” Well, AI is no longer on the horizon. AI is here. AI is starting to guide HTM repairs. AI will change the way we troubleshoot.
EVOLUTION OF AI IN TECHNICAL SUPPORT
Most of us are probably used to AI as an automated customer service agent. In back-office settings, AI can dramatically boost productivity while reducing staff requirements. It excels in automating repetitive software tasks and analyzing large datasets. I admit that is not good for the standard office worker. In technical domains like HTM, however, our requirements are far more complex and specialized. Here is where the current AI revolution truly enhances our work.
There is a key distinction to make: AI will not replace the critical hands-on skills of HTM professionals. The skilled judgment and technical ability of humans will remain essential, especially when servicing intricate medical devices. AI, when specifically tailored with HTM-focused data, can serve as a guide by offering recommendations during repairs. It will become the standard for our field, just as real-time traffic mapping is to the morning commute. In fact, it will become just as valuable.
HOW AI LEARNS FROM THE HTM FIELD
Leading companies are mining computerized maintenance management systems (CMMS) for real-world HTM repair data. The results are extensive databases of problem-resolution pairs. With access to hundreds of thousands of service records, AI algorithms can identify troubleshooting patterns and develop step-by-step solutions for a variety of failures. While the underlying machine learning processes are complex, the core principle is simple: AI can “learn” how experienced technicians resolved similar issues in the past. It uses this information to guide others. Given thousands of work orders and their solutions, the results are extremely useful.
Imagine an AI-powered support system that functions almost like having a veteran colleague at your side. Unlike repair manuals or traditional support hotlines, this AI system continuously improves by learning from every new interaction. It can understand spoken or written queries, interpret vague symptoms, ask clarifying questions and adapt its guidance. Rather than simply reciting procedures, it collaborates, drawing upon the collective experience of thousands of technicians. On top of these advantages, the more it is used, the better it will get.
IMPACT ON PRODUCTIVITY AND QUALITY
These systems are already in use in some technical fields and the value they bring is evident. For instance, automotive technicians who used AI-assisted troubleshooting reported an average of 15% fewer callbacks on first-time repairs (Source: www.aiventic.ai). Overall productivity increased, suggesting a 30% reduction in time spent on repairs. These numbers are not just statistics; they represent real world improvements in service quality, customer satisfaction and operational efficiency.
Think about it: what if you had access to an AI assistant that distilled the collective wisdom of 10,000 seasoned technicians? If it was ready to help 24/7, without any waiting on hold, is that valuable? Would you use it? Even if the AI occasionally points you in the wrong direction, wouldn’t it still be worth considering its advice as a sort of second opinion? In this way, AI acts as a valuable safety net, supporting even the most experienced professionals and helping to ensure no troubleshooting avenue goes overlooked.
BEYOND TROUBLESHOOTING
AI’s role doesn’t end with troubleshooting. Over time, as it accumulates more data, AI can use its knowledge to train others. For new or less experienced technicians, AI can offer hands-on guidance, explaining concepts step by step, suggesting best practices and even simulating repairs based on actual cases. The instructional content can be generated on demand and delivered in a variety of formats: text, audio or (eventually) custom video demonstrations.
Imagine onboarding a new technician with an AI that provides real-time feedback during their first repairs. What impact would be present with structured, interactive training modules that are tailored to each learner’s pace and needs? The potential to automate and personalize instruction means actual experience, which is the resource that’s the most difficult to pass on, can be preserved and transferred more effectively.
EMBRACING CHANGE, RETAINING EXPERTISE
For those hesitant about these changes, it’s crucial to remember: AI isn’t “inventing” technical knowledge but is instead distilling human experience. True Artificial General Intelligence (AGI), a machine with human-level reasoning, remains a hypothetical future. The current generation of AI excels at pattern recognition, guidance and information retrieval, but it cannot (and will not) replace the intuition, ethics or manual skill of HTM technicians. I realize that some may be skeptical or suggest that it would cause a dumbing down of the field, but have we seen that so far? Has computer-aided detection replaced radiologists or enhanced their abilities? If the field thought it didn’t help, why do they keep purchasing the systems? It is because it adds value.
In practical usage, AI is already being used as a tool in the form of GPS systems for navigation. Most of us use turn-by-turn navigation, even when we ignore its directions. Does that make us worse at driving? Similarly, AI will become an everyday companion in troubleshooting, improving confidence without controlling decisions. Those who learn to integrate AI into their workflow will gain a competitive edge, both in efficiency and in flexibility. They just will be able to do more tasks with confidence.
THE ROAD AHEAD
The adoption of AI in HTM is not about eliminating roles, but about enhancing what technicians can accomplish. As AI becomes more sophisticated, it will further close the skills gap and make training more accessible. This will help ensure that every technician can have expert guidance. The AI technology to assist maintenance is already reliable, effective and currently being used (Source: https://www.jenova.ai/a/auto-repair-mechanic). Its value will only grow as it continues to learn and adapt. The future of AI as a troubleshooting assistant in HTM is arriving faster than many anticipated. By embracing these tools, we can improve outcomes for healthcare organizations and, most importantly, for the patients.
