The facilities data gap holding higher education back

Higher education facilities teams are being asked to solve an impossible equation: lower operating costs, improve campus experience and modernize aging infrastructure without unlimited budget or staff. The result is a growing need for smarter, more predictive facilities strategies.

To better understand how higher education organizations are responding, we analyzed survey responses from higher education leaders and facility managers (FMs) in our 2026 AI & Digitalization in Facilities Management report. The findings reveal a sector trying to find the sweet spot between investments that directly enhance the campus experience and investments in the supporting systems that make that experience possible.

Three findings from the report show why connected facilities data is becoming essential to campus competitiveness.

1. As costs rise, energy performance has become a top priority

Rising costs and shrinking budgets are driving a strong focus on efficiency and energy performance across higher education.

• Higher education leaders say “cost” is the area that they most need improved visibility
• Budget constraints, rising energy costs and aging infrastructure are the top three challenges impacting the ability of higher education FMs to effectively manage their facilities

College and university leaders and FMs that are searching for ways to reduce costs have set their sights on energy performance.

• Energy use and efficiency is the number one area where FMs want more data and insight
• When asked to pinpoint one new capability that would make their operations more resilient and efficient, “energy optimization” is the top pick among higher education FM respondents

That demand for cost control is already influencing technology plans. Higher education leaders who expect to expand AI use in the next year rank energy performance as a leading use case, while FMs point to energy tracking, optimization and control as one of the most important applications for smart building and AI tools. 

Energy performance and cost control are no longer just operational concerns – they are shaping strategic decision-making and technology investment across the higher education sector.

2. Higher education institutions are connecting the dots between operational reliability and occupant experience

Colleges and universities continue to prioritize investments that enhance occupant experience to support student satisfaction, faculty productivity and institutional competitiveness.

• Enhancing occupant comfort and wellness is the most-cited use case among higher education FM respondents who plan to implement a workplace management or smart building solution in the next year (tied with energy efficiency)
• When asked to select one new capability that would make operations more resilient and efficient, 24% of higher education leaders said “improved occupant experience,” compared to 16% of non-higher education leaders

At the same time, predictive maintenance appears high on the list of future investment priorities for higher education FMs. This signals a recognition that transitioning from reactive to predictive maintenance not only cuts costs and waste, but can enhance occupant experience. It does this by reducing downtime, improving reliability and minimizing disruption to the campus environment.

• When asked which technology they plan to implement in the next year to assist with the operation and maintenance of facilities, AI-driven predictive maintenance was by far the top response among higher education FMs

College and university leaders place less emphasis on predictive maintenance investment, suggesting a stronger focus on broader institutional priorities beyond facilities operations.

• 34% of higher education leaders say their organization is currently using AI to enable predictive maintenance, compared with 42% of non-higher education leaders
• 33% of higher education leaders plan to implement AI-driven predictive maintenance within the next year, compared with 46% of non-higher education leaders

Higher education institutions see predictive maintenance as a new capability that would improve facility performance, though current adoption lags behind other industries. Instead, higher education leaders and FMs are placing an emphasis on occupant experience, signaling a people-focused approach to campus planning.

3. Data gaps are limiting visibility and slowing decision-making

Access to timely, reliable data is critical to control costs, maintain infrastructure and improve performance. However, many colleges and universities lack the tools needed to generate these insights. A case in point is in analytics and sensor technologies, where higher education lags behind other industries.

• 47% of higher education leaders use workplace analytics tools, compared with 69% of non-higher education leaders
• 31% of higher education leaders say their organization uses workplace sensors, versus 47% of non-higher education leaders

Because colleges and universities are lagging behind other industries when it comes to analytics, the practices higher education leaders use to collect performance data are less advanced:

• 26% of higher education leaders rely on manual data collection, compared with 19% of non-higher education leaders. Manual data collection was the leading response when higher education leaders were asked how they collect data to measure the performance of their work arrangement
• 22% of higher education leaders use real-time analytics, versus 33% of non-higher education leaders

Higher education institutions understand the importance of data-driven decision-making, but competing priorities are slowing investment in the analytics and smart building technologies needed to enable it.

What this means for higher education facilities strategy

The higher education findings from the 2026 AI & Digitalization survey highlight a sector that is navigating a series of competing priorities.

Budget constraints and the demands of addressing a huge backlog of deferred maintenance are forcing higher education institutions to be cautious about how they adopt workplace management and smart building technology. Higher education FMs and leaders perform a delicate balancing act between:

• Focusing on cost control and energy performance
• Investing in occupant experience to remain competitive
• Managing aging infrastructure with limited resources
• Gradually building toward more data-driven operations

The campuses that gain an advantage will be the ones that connect facilities data to the decisions that matter most: where to reduce cost, where to prevent disruption and where to improve the daily campus experience. 

FAQs

Why is predictive maintenance important for higher education facilities?

Predictive maintenance helps higher education facilities teams identify potential equipment issues before they lead to outages, costly repairs or disruptions to the campus experience. By using connected data, analytics and AI, colleges and universities can move from reactive maintenance to more proactive operations.

How can higher education institutions use AI to improve campus operations?

Higher education institutions can use AI to optimize energy performance, support predictive maintenance, improve occupant comfort and make smarter decisions about space, assets and infrastructure. These capabilities are especially valuable as campuses balance rising costs, aging infrastructure and growing expectations from students, faculty and staff.

What data do colleges and universities need for smarter facilities management?

Colleges and universities need timely, reliable data from building systems, sensors, analytics tools and workplace management platforms. When this data is connected and easier to interpret, facilities leaders can better understand energy use, equipment performance, space utilization and opportunities to improve campus resilience.