Over the past year, community colleges and research universities alike have launched ambitious AI initiatives, positioning themselves as innovation leaders. However, amid aging infrastructure, labor constraints, tightening budgets, and complex enrollment pressures, higher education leaders face a critical question: “How can institutions of higher education deploy artificial intelligence (AI) to deliver durable operational value, not short-lived experimentation?”
At the same time, using AI to improve operational efficiency, accelerate sustainability goals, and strengthen campus safety is increasingly viewed as a strategic priority. Many campus leaders express enthusiasm about AI’s potential, while also citing practical barriers, such as limited in-house expertise and the challenge of integrating new tools with legacy systems.
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These realities point to a timely truth: to harness AI’s full potential for campus safety and facilities management, leaders must build the right foundation for thoughtful, strategic deployment. With a significant portion of the facilities workforce nearing retirement in the coming years, aligning AI exploration with purpose-built strategies is essential for institutions seeking long-term impact amid persistent resource constraints.
Setting the Foundation for Campus Wide AI Integration
When deployed with intention, technology can be a powerful tool for doing more with less. But without the proper foundation, AI initiatives risk remaining siloed, temporary, or ineffective.
Higher education institutions are no strangers to this challenge. U.S. campus buildings average 50 years in age and reflect a patchwork of construction eras, renovations, and system upgrades. This complexity, often compounded by multiple, fragmented building management and security systems, can stand in the way of campus wide AI integration.
To move from pilots to lasting value, campus leaders should start with a top-down assessment of the facilities and operations landscape. This process begins by clearly defining the goals driving AI deployment, such as lowering energy costs, improving indoor air quality, strengthening threat detection, or accelerating response times, then identifying the structural gaps and operational risks that could impede progress.
Comprehensive building and system audits can help colleges and universities establish equipment condition and remaining useful life, identify disconnected or duplicative systems, define performance baselines to measure improvement, and clarify where data quality, coverage, or governance is insufficient.
From AI-enabled energy management and air-quality sensors to smart-building controls that optimize performance at the room level, facilities leaders have no shortage of technology options. However, realizing value from any system requires a clear, evidence-based understanding of campus infrastructure along with a practical plan for integration, cybersecurity, and ongoing maintenance.
Prioritizing AI Applications for Sustainability and Operational Efficiency
Even with a strong understanding of infrastructure gaps, deciding where to begin is not always straightforward. Facilities management is only one part of a broader campus ecosystem balancing academic priorities, student needs, compliance requirements, and financial constraints.
For that reason, facilities leaders should prioritize AI deployments that support long-term institutional objectives, deliver measurable impact with manageable upfront investment, and create a scalable foundation for future expansion.
A strong starting point is sustainability and utilities optimization. Institutions aiming to meet sustainability benchmarks over the next two decades must reduce energy-related emissions across campus. Installing AI-enabled sensors to track water, lighting, and power consumption in high-use facilities is an integral starting point. Research supports this strategy: one study found that building management systems were responsible for a 42% reduction in operational emissions.
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These early efforts can also serve as “quick wins” for stakeholder buy-in, especially when results are communicated through clear operational metrics, such as reduced energy intensity, fewer comfort complaints, faster response times, and improved uptime for critical systems.
In addition, AI-enabled building controls can support facilities teams by predicting occupancy patterns to fine-tune schedules and setpoints, flagging early maintenance risks before failures occur, improving reliability for classrooms, labs, and residence halls, and strengthening emergency preparedness through better situational awareness.
In an environment where staffing constraints are a persistent challenge, these tools can help teams allocate time more effectively, maintain service standards, and support training through modern workflows. APPA is curating programming and events that feature case-study based and roundtable discussions on how facilities teams can practically apply AI in their operations.
Driving Collaboration Between IT, Operations, and Facilities Management
Sustained AI impact depends on collaboration across facilities management, IT, and campus operations. Together, these teams can adopt a shared playbook for resource optimization using advanced analytics not only to reduce costs, but also to create more resilient, responsive learning environments.
IT leaders play a critical role in ensuring AI systems align with institutional standards for data governance and access controls, privacy and monitoring policies, vendor risk management and cybersecurity requirements, and system interoperability and enterprise architecture.
As AI-enabled monitoring tools become more common in physical security and building operations, this oversight is essential to mitigating risk and protecting campus communities.
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Cross-functional coordination can also help close the skills gap by sharing expertise, standardizing processes, and reducing information silos. To support this exchange, APPA is launching a community platform where facilities leaders can continue conversations beyond events and programs, including a dedicated segment focused on AI in Facilities. In practice, AI-enabled building monitoring can enable cross-department teams to integrate insights into campus planning, supporting stronger capital prioritization, clearer deferred maintenance narratives, and better long-range investment decisions.
Finally, collaboration helps reduce system fragmentation. By identifying overlaps across technology stacks and aligning procurement with integration requirements, institutions can establish a clean implementation baseline for AI-enabled workflows such as digital maintenance logging, condition-based work orders, and task management. With integrated systems, facilities teams can reduce administrative burden, access information faster, and devote more time to higher-value priorities.
Educational institutions continue to face intensifying pressures: funding constraints, rising operating costs, enrollment volatility, aging infrastructure, and staffing shortages in critical functions like facilities management. In this environment, AI can deliver meaningful benefits, but only when deployed with clear intent, measurable goals, and the operational foundations to sustain it.
Ultimately, long-term AI adoption is not about layering new applications onto outdated systems. It is about building the infrastructure, governance, and cross-functional alignment required to deploy technology at scale. When institutions approach AI with sustainability and adaptability in mind — using data-driven decision-making throughout the process — campus infrastructure is better positioned to support safe, efficient, and thriving communities for students, faculty, and staff.
Lalit Agarwal is President and CEO of APPA.
Note: The views expressed by guest bloggers and contributors are those of the authors and do not necessarily represent the views of, and should not be attributed to, Campus Safety.
