Building management is entering a new era, shifting from traditional controls toward intelligence-driven operations. For years, we saw experimentation and testing of AI for basic functions and single-use tools. They were deployed on a limited scale, often focused on one asset or task at a time—successful in proving the concept but falling short of delivering the operational efficiencies building operators truly need.
The next evolution is AI and automation at scale. Across industries—from data centers to healthcare facilities—there is a consistent theme: the need for intelligent, integrated systems that help simplify work for operators and improve performance. Burdened by complexity, time-consuming manual processes and labor shortages, operators need tools that bridge data across their facilities, automate routine tasks, and support teams with clear, actionable insights. In 2026, these capabilities will no longer be considered premium features; they’ll become baseline expectations.
Building a Foundation for Interoperability
To reach this point, better interoperability is essential. As buildings generate more information, operators need systems that can interpret data using shared standards and ontologies. Until recently, equipment relied on proprietary software and closed data models, which made it extremely difficult to integrate. Fragmentation has inhibited continued innovation. Now, with the surge in AI and IoT devices, connected frameworks are dismantling these barriers, enabling insights to flow freely across disparate assets and allowing automation to deliver more informed actions.
Smart tools demonstrate how integrated architectures are beginning to reshape the industry. The platform’s unified data fabric and ontology model normalize information from various sources, avoiding the need for custom integrations or extensive engineering support. This creates a consistent operational view for teams while reducing onboarding complexity and accelerating time to value.
With a more standardized data structure, operators can move beyond reactive decision-making. They gain the ability to evaluate multi-system performance in a single interface and leverage AI and automation to coordinate end-to-end actions that previously required considerable manual intervention. As these frameworks mature, expect interoperability to become a deciding factor in vendor selection by late 2026, with industry groups pushing hard to formalize standards that make integration seamless.
Driving Operational Efficiency Through Automation
The move toward AI-enabled building management systems will support improved building efficiency in several areas. By consolidating data from equipment—such as temperature and energy consumption—these platforms can analyze performance and, over time, predict failures before they disrupt operations. Predictive analytics will allow maintenance teams to detect disruptions well before they materialize.
Earlier warnings enable timely service scheduling, limited occupant impact and help extend the life of critical equipment. Verizon, for example, is deploying AI-powered building management to help predict critical building and system issues before they become serious and costly. AI-supported platforms can help technicians avoid unnecessary trial and error, shorten repair cycles and reduce overall operating costs.
With greater connectivity, also comes greater visibility. Real-time access to data means that operators are no longer making decisions based on historical reporting. Instead, they can see how the building and critical systems are functioning in real-time. This allows them to make adjustments to maximize energy usage, which has long been one of the highest operational costs. According to the U.S. Department of Energy, 30% of energy used in commercial buildings is going to waste.
This level of insight is invaluable for those managing a portfolio of buildings or large campuses such as Vanderbilt University, which is using an AI platform to enhance building system efficiency across its campus and help reduce energy consumption, particularly in older buildings. For hotels, centralized monitoring and building automation can significantly optimize energy consumption and can reduce HVAC energy usage by up to 25%. In 2026, energy optimization will evolve from a best practice to a formal performance metric.
Making Building Operators More Efficient
Labor shortages will remain a persistent pressure point for facility teams, with many organizations facing difficulty in hiring or retaining experienced operators. As this pressure continues, AI will become a critical support layer across building operations.
AI is emerging as a frontline assistant, helping to evaluate conditions, surface issues that demand attention, and suggest appropriate next steps. This provides operators with timely guidance during periods of high workload or reduced staffing.
Technicians can benefit from structured recommendations that help them navigate unfamiliar situations, especially those that are earlier in their career. Meanwhile, more seasoned professionals can achieve scale, helping them to oversee larger teams and more complex portfolios without compromising performance. AI acts as a force multiplier for teams at every skill level.
As demands for uptime, efficiency, and occupant comfort increase, operators will increasingly rely on platforms that can proactively respond to issues and coordinate appropriate actions. By the close of 2026, expect predictive maintenance and automated energy adjustments to operate quietly in the background as standard practice—transforming what was once considered cutting-edge into everyday reality.
In the new year, we'll see continued innovation in the industry, which will be central to creating safer, more efficient, and more resilient environments.
