For years, predictive maintenance in HVAC has been one of those technologies that everyone talks about at trade shows but comparatively few contractors actually deploy in the field. A new 2026 survey from Fluke Corporation suggests that may finally be changing, and changing fast. The survey, covering maintenance and manufacturing professionals across the industry, found that predictive maintenance adoption doubled year-over-year, climbing from 9% to 18% — a genuinely significant jump for a technology category that has spent the better part of a decade stuck in early-adopter territory.
The driver behind that doubling is not a single breakthrough product or a sudden change in contractor appetite for new technology. It is the steady, compounding effect of increased investment in industrial AI and connected technologies across the HVAC equipment landscape, finally reaching a critical mass where predictive maintenance stops being a nice-to-have add-on and starts becoming a genuinely practical operational tool.
Why Predictive Maintenance Has Taken So Long to Catch On
Predictive maintenance, in its purest form, uses sensor data, equipment performance trends, and increasingly AI-driven analysis to identify likely equipment failures before they actually happen, allowing a contractor to schedule a repair proactively rather than responding reactively to a breakdown. The concept is not new. What has been missing, until relatively recently, is the underlying connected infrastructure needed to make predictive maintenance practical at scale rather than a boutique offering reserved for a handful of large commercial accounts with sophisticated building automation systems already in place.
Nayak, a voice cited in the underlying coverage of this survey, points directly to this infrastructure gap as the real explanation for why adoption has been slow to build. The rapid expansion of connected HVAC equipment and Internet of Things platforms over the past five years has made operating data far more accessible than it used to be, and that accessibility is precisely what has accelerated the development of genuinely useful predictive capabilities. In plain terms: predictive maintenance needed enough connected equipment already installed in the field to generate the data that makes prediction possible in the first place, and the industry has only recently crossed that threshold.
What Manufacturers Are Actually Building
The survey results land alongside concrete manufacturer investment that confirms this is not just a contractor-side trend but a coordinated industry-wide shift. Rheem, specifically, is investing heavily in expanding its connected ecosystem, with advancements in remote monitoring, AI diagnostics, and service tools rolling out over the next twelve to twenty-four months specifically designed to make installation and service work faster, smarter, and more proactive across both residential and commercial applications.
This kind of manufacturer-level investment matters because predictive maintenance capability is only as good as the equipment generating the underlying data. A contractor cannot build a predictive maintenance service offering around equipment that isn't instrumented to produce the operating data predictive algorithms need to work. As more manufacturers follow Rheem's lead in building connected diagnostics directly into their equipment lines, the practical floor for what predictive maintenance can deliver across an average residential or light commercial service base rises accordingly.
The Customer Experience Angle That Changes the Sales Conversation
One of the more interesting threads in the underlying research is the observation that predictive maintenance value increasingly gets measured through customer experience, not just raw equipment performance metrics. Homeowners and building operators are increasingly expecting better performance, greater efficiency, and more visibility into how their systems are actually operating — a shift that is pushing the entire industry toward smarter, more data-driven service models almost independent of whether predictive maintenance delivers a measurable reduction in breakdown frequency.
This reframes how contractors should think about pitching predictive maintenance and connected service offerings to customers. The pitch is not purely about preventing a compressor failure six months from now, an argument that can feel abstract and hard for a customer to value in the moment. The more compelling pitch, especially for younger or more tech-savvy customers, increasingly centers on visibility and control: the ability to see how a system is actually performing, get proactive notifications before a problem becomes an emergency, and feel a sense of ongoing engagement with a piece of equipment that has historically been a black box between annual maintenance visits.
Why This Matters for Contractors Building a Service-Based Revenue Model
Predictive maintenance adoption doubling from 9% to 18% in a single year is a meaningful signal for contractors who have been building, or considering building, a more sophisticated maintenance agreement and recurring service revenue model. Recurring service revenue has long been one of the most valuable, most defensible parts of an HVAC contracting business, precisely because it creates a durable customer relationship that survives beyond a single transactional installation or repair call.
Predictive maintenance capability strengthens that recurring revenue model in two specific ways. First, it gives contractors a genuine, differentiated reason for a customer to choose a maintenance agreement with connected monitoring and proactive alerts over a competitor's more basic seasonal tune-up offering. Second, and more operationally important, predictive data helps contractors actually deliver on maintenance agreement promises more efficiently, by directing technician attention toward systems showing early signs of trouble rather than spreading routine maintenance visits evenly across an entire customer base regardless of actual equipment condition.
