5 ways AI reduces building operating costs and energy waste

Labor shortages, rising energy costs, net zero commitments and regulatory requirements have stretched facilities teams in ways never before seen. According to the 2026 AI & Digitalization in Facilities Management Report, when facilities managers were asked to rank their top three challenges impacting their ability to manage facilities effectively, a majority of respondents chose budget constraints, rising energy costs and equipment aging or deferred maintenance as their top concerns. Perhaps that is why 67% of FM respondents say their organization already uses AI to improve facility operations and maintenance.

While they are expected to do more with less, many FMs see AI as a tool to help them do their jobs better and make their systems more efficient. AI-powered building management has the power to reduce operating costs and energy waste by translating live building data into actionable insights, automating fault detection and enabling autonomous controls that minimize manual intervention.

Here are five ways facilities teams can improve building performance today with AI.

1. Unlock and translate building data into opportunities

AI aggregates internal and external building data – from space utilization to equipment performance to weather – and converts it into actionable insights and clear recommendations to increase efficiency and reduce waste.

Facilities teams can develop a better understanding of how their spaces are used and make targeted changes to use them more effectively. OpenBlue Central Utility Plant Optimization, for example, uses AI to monitor thousands of variables, gathering data every 15 minutes from connected equipment and external sources such as weather forecasts and utility rates. It then automatically generates and implements optimization decisions, reducing costs, improving resilience and maximizing sustainability. For one Las Vegas resort, AI-driven plant operations using OpenBlue achieved over 10% estimated annual energy use savings.

2. Reduce energy waste with generative AI recommendations

Generative AI closes the gap on energy waste by recommending the most impactful energy-saving projects for your building. Without the need for well-written prompts, AI-driven energy management solutions like OpenBlue Net Zero automatically collect data from multiple utility providers or meters and displays energy usage across an entire real estate portfolio in one dashboard. It uses that data to provide actionable insights that offer the highest savings potential.

With automated data collection, facilities teams enjoy reduced time and labor required to generate reports for management and compliance purposes.

3. Cut maintenance costs with automated fault detection

Automated fault detection and diagnostics reduce the time required to detect, analyze and address potentially critical and costly issues in HVAC systems, lighting, elevators and other subsystems integrated via building management systems (BMS). With data from connected equipment and systems, AI-driven solutions can detect faults early, proactively monitor potential issues and automate the escalation and work order process. By catching potential risks sooner, AI can help extend equipment life and reduce downtime.

OpenBlue Equipment Performance uses AI to deliver in-depth insights about the monetary impact of each fault, making it easy to determine which items to prioritize. Autonomous control capabilities help ensure key equipment settings are always within range and enable remote setpoint overrides when alarms occur through an integrated BMS or directly from equipment. For one global consultancy, these features reduced maintenance costs by 10% and drove a 20% improvement in operational productivity.

4. Track sustainability goals and lower emissions

AI can help teams stay audit-ready by automatically converting energy consumption figures into carbon emissions and GHG emissions metrics. Facilities teams can record their emissions-related projects and goals in the system, which will collect the relevant energy data and generate reports, flagging anomalies and providing recommendations for optimization.

With access to more granular, real-time data, facilities teams can spot energy inefficiencies, benchmark performance and reduce the burden of manually tracking progress against sustainability goals. AI’s powerful analytics can also measure potential savings over time by comparing a building’s baseline performance with targets. Using OpenBlue Net Zero, a government agency accelerated its progress to net zero with improved visibility into emissions and renewable energy performance, always-on monitoring and on-demand ESG reports.

5. Move toward autonomous building operations

AI enables facilities teams to manage their portfolio with less manual intervention than ever before. AI-driven equipment performance software offers both advisory control, which provides recommendations for optimization, and autonomous control, which adjusts equipment operations based on real-time data inputs. Autonomous controls can guarantee that critical setpoints stay within a desired range or safeguard indoor air quality.

Facilities leaders can adjust automation setpoints based on certain aims, such as fault diagnostics, saving energy or accelerating potential cost savings. It also provides detailed information about equipment performance and trends, from a broad view down to individual pieces of equipment.

As AI continues to evolve, it will play an increasingly central role in transforming building management. Facility leaders who embrace this technology are the ones who will stay competitive and meet the demands of modern building operations. By using AI, they can significantly improve energy efficiency, operational performance and occupant satisfaction, ultimately driving progress towards smart, safe, healthy and sustainable buildings.

FAQs

How quickly can AI-powered building management deliver ROI?

AI-powered building management platforms like OpenBlue can begin identifying energy-saving opportunities immediately by analyzing live weather and occupancy data against chosen baselines. Customers have reported up to 30% reduction in energy spend and up to 20% reduction in maintenance spend, with returns accelerating as the system learns building-specific patterns over time.

What's the difference between advisory and autonomous building controls?

Advisory mode provides AI-generated recommendations that building operators review and act on manually. Autonomous mode allows the system to execute approved actions automatically – such as adjusting HVAC setpoints based on fault diagnostics or energy-saving targets. OpenBlue lets you switch between modes for each parameter, so you control the level of automation.

Can AI help track and report on building emissions goals?

Yes. Solutions like OpenBlue Net Zero provide data-driven guidance to uncover energy conservation measures (ECMs) and track energy conservation projects. The platform offers proactive recommendations to manage decarbonization strategies and support progress toward net zero targets.