The use of artificial intelligence (AI) has great potential in energy management for CRE spaces. Unfortunately, using AI in your retail, business or office spaces can be somewhat frightening, and this is in addition to the technology investments and upgrades necessary to leverage it. CRE providers need to understand the challenges of using AI for energy management for CRE spaces, how it benefits tenants and a few best practices for deploying it successfully.
Challenges of Using AI in CRE Spaces
The difficulties of using AI in CRE spaces are relatively simple, including limited use of connected systems and sensors. Since AI is based on the use of data to make informed decisions, connecting assets and retrofitting the facility are the top priorities. Even once the systems and technologies are in place to collect data, Facility Managers may not know what to do with it. Data can be confusing, and the volume of data generated through sensors and systems is mind-boggling. Ironically, this is where the real value of AI in energy management for CRE spaces exists.
AI Will Enhance All Operations, Reduce Turnover and More
As explained by McKinsey&Company, the use of AI includes computer vision, robotics, advanced machine learning, natural language interpretation, and virtual assistants. These five forms of AI contribute to the value of a capable, intuitive energy management system, and by 2030, 70 percent of companies will have adopted at least one pillar of AI in their organizations.
Regardless of what type of AI is used in CRE energy management, AI will reduce the workload on existing staff members, proactively manage the budget, streamline and prioritize maintenance needs and reduce the risk of disruptions.
Best Practices for Deploying AI in Energy Management for CRE
According to McKinsey&Company, some of the best practices for deploying AI in energy management for CRE include:
- Determine actual versus projected time to ROI. The use of machine learning will have a significant impact on determining the actual versus planned time to ROI and savings possible through energy management initiatives. Although most system vendors recognize substantial savings are possible, all saving profiles are based on ideal operating conditions. Unfortunately, this means that actual savings may be less than those projected initially. In addition to collecting accurate, site-specific data, machine learning can ensure expected results come to fruition.
- Define true business problems that AI will solve. AI will not solve everything, and it is impractical to think AI will replace entire workforces within the facility management department. In other words, Facility Managers of CRE spaces should look for the problems that AI can solve. For instance, AI can refine maintenance schedules, but even robotics will eventually require maintenance too.
- Democratize data. The democratization of data is the foundation for the use of AI in CRE energy management. CRE providers should work to increase access and use of data throughout the facility management departments. This is essential to some types of AI, like virtual assistants and robotics.
- Expand the use of AI in your energy management program. A final best practice lies in need to continually expand the use of AI in the energy management program. While some organizations may have successfully deployed AI in all five forms, there will still be learning opportunities. Take advantage of them.
Tap Into the Value of AI Across Your Distributed Portfolio
Energy management for CRE spaces is suffering from shrinking budgets and fewer labor resources. The talent shortage in facilities management is growing worse, but the use of AI in energy management can help. Get your organization ready for an AI-based energy management future by visiting ENTOUCH online or calling 1-800-820-3511.