Key Takeaways:
Half. That is the proportion of facility management professionals expected to retire within the next five to 15 years. Nearly 40 percent of facilities managers in the United States are already over the age of 55.
These numbers should stop every facility executive in their tracks.
We are not just losing headcount. We are losing the people who know why the third-floor air handler needs a specific start-up sequence, which steam traps fail every spring and what the original engineer meant by that cryptic note in a 30-year-old set of drawings. When they walk out the door, decades of institutional knowledge go with them, most of it undocumented.
This is not a problem we can hire our way out of. But it is one we can begin to address, if we are willing to think differently about the tools available to us. Artificial intelligence (AI) is emerging as one of the most practical tools: not as a replacement for skilled staff, but as a workforce multiplier that captures knowledge, sharpens decisions and extends the capacity of the teams we have.
In higher education, the workforce challenge is compounded by aging building portfolios, compressed operating budgets and an enrollment cliff that limits new revenue. Gordian’s State of Facilities in Higher Education report has documented a shrinking facilities workforce for over a decade. At the same time, operating budgets have declined, and staffing levels have struggled to keep pace with the maintenance demands of infrastructure that, on many campuses, dates back to the mid-20th century.
The result is a widening gap between what our teams are expected to maintain and the resources available to do it. AI does not close that gap entirely, but it offers a meaningful way to begin.
AI offers its most immediate and perhaps most underappreciated value: not as an automation engine, but as a knowledge preservation tool.
Facilities teams can use AI-enabled documentation tools to record step-by-step maintenance procedures, annotate system-specific quirks and build searchable knowledge libraries. A senior technician can walk through a system, narrate what matters or their thought process, and AI can convert that into a structured, accessible procedure.
Over time, this creates a living operational playbook. It accelerates onboarding, reduces reliance on individual memory and ensures that critical operational knowledge survives workforce transitions. AI is not replacing the experienced technician. It extends their impact long after they have moved on.
Many facilities organizations are data rich but struggle to translate the data into actionable insights. AI changes that. Instead of reacting to a chiller failure on the hottest day of the year, AI can flag early indicators such as vibration anomalies, temperature drift or increases in temperature related work order requests. This allows teams to intervene before a system failure occurs.
Beyond predictive maintenance, AI supports optimized scheduling based on actual asset condition and enables continuous energy optimization by adjusting building systems in response to occupancy, weather and real-time performance data. The result is less downtime, longer asset life and maintenance resources directed where they matter most.
If you are a facility manager reading this and thinking, “This sounds promising, but where would I even begin — and when would I find the time?” you are asking exactly the right question.
Facility managers do not have the luxury of setting aside a week to learn a new tool. A typical day may start with a system failure, move to a budget meeting and end with a project walkthrough. There is no slack in that schedule for “practice.” That is precisely the point: the most effective way to learn AI is not to practice with it separately, but to begin using it for the work you are already doing.
Start with the friction you already feel, such as:
At the University of Maine System, facility leaders are already doing this. Some have set up AI to deliver a daily summary of unread emails, not just a list, but a triaged overview with proposed next steps and draft responses ready to review. Others use it to schedule meetings on the fly, run cost comparisons between repair options or troubleshoot equipment issues in real time while standing in front of the unit. None of these required an implementation plan. They started with a single task and built from there.
These are not separate projects added to your plate. They are the same tasks, completed faster. The five minutes you save drafting a memo today becomes the hour you save analyzing a capital plan next month. Each use builds familiarity. Each success builds confidence. And over time, what began as a small time-saver becomes a fundamentally different way of working.
One of the most underestimated applications of AI in facility management is communication. Facility leaders understand the technical details behind why a project is necessary. Senior leaders, including campus presidents and boards of trustees, often do not. Bridging that gap can be one of the most challenging parts of the job. AI can help by translating technical complexity into clear, accessible information that supports better decision-making.
At the University of Maine System, we recently used AI to help our board of trustees visualize a proposed facade replacement on one of our campus buildings. Instead of asking board members to approve funding based on written descriptions alone, we used AI-generated imagery to show what the building could look like after the project was complete. This shifted the conversation from abstract discussion to a shared understanding of the potential outcome.
AI can also translate technical diagnostics into plain-language summaries, draft stakeholder communications, and synthesize condition data, cost estimates and operational impacts into cohesive narratives. In capital planning conversations, where competing priorities and limited funding are the norm, the ability to present a clear, visual and data-supported case is a genuine advantage.
The opportunities are real, but so are the risks. Facility leaders considering AI adoption should focus on three areas:
For organizations just beginning their AI journey, the most effective approach is to start small. Focus on targeted applications that deliver immediate, visible value, such as documenting standard operating procedures, analyzing work order trends or streamlining routine communications. From there, expand into predictive maintenance, integrated analytics and capital planning support.
This incremental approach allows teams to build confidence, demonstrate return on investment and develop governance practices before scaling more broadly. Just as importantly, facility leaders set the tone that AI is a tool to support staff, not replace them. In an industry already facing workforce challenges, transparency around expectations, benefits and limitations is essential to building trust.
AI will not solve every challenge facing facility management. Aging infrastructure, funding constraints and workforce shortages will continue to require strategic leadership and sustained investment.
But the most immediate opportunity is clear. As experienced professionals retire, the risk is not just losing positions but losing the knowledge that keeps buildings operating safely and efficiently. AI provides a practical way to capture that knowledge, translate data into actionable insight and reduce friction in everyday operations.
The organizations that succeed will not be those that adopt AI the fastest, but those that use it to ensure that what their teams know today is not lost tomorrow.
Gretchen Catlin is the chief facilities and general services officer for the University of Maine System, where she oversees facilities management, capital planning, procurement, risk and safety and space utilization across a seven-university system and law school. Her work focuses on addressing workforce and infrastructure challenges through practical applications of artificial intelligence to improve knowledge transfer, decision-making and operational performance. Gretchen currently serves on the Elevate board and is a former Building Operating Management cover subject.
