AI is transforming tasks in real estate and facilities management. Organizations are using traditional AI for predictive maintenance, reducing carbon footprints, improving space utilization, and optimizing cleaning schedules. AI also enhances decision-making through comprehensive analytics on consolidated facility information.
The leading organizations are insisting that related facility management data (capital planning, lease, space, sustainability, maintenance, and operations management) is readily and easily accessible to ensure AI can be fully exploited. This accessibility can be enabled by leveraging more holistic facility management solutions that are architected on a shared data repository. Facility Managers can and should heavily influence the architectural direction of their organization’s solution, advocating for a comprehensive IWMS.
The future with Generative AI holds immense potential for revolutionizing core activities in facilities management. For instance, imagine if your system could continuously compare lease profiles across markets, alerting to better opportunities, validating these against current agreements, determining trade-offs, calculating financial impacts, and making informed recommendations.
This capability could extend to capital planning, space optimization, maintenance, and sustainability initiatives as well. However, the effectiveness of GenAI will be even more dependent on the accessibility of data. Organizations with siloed systems and independent data repositories will be at a disadvantage compared to those with a unified data management approach.
Overcoming data silos is required given that success in facilities management hinges on seamless access to comprehensive and integrated data. Adopting a ‘single source of truth’ will enable organizations to fully harness GenAI’s capabilities, driving efficiency and innovation across all aspects of facilities management.
Tempering enthusiasm with reality is required given the potential of GenAI is vast. We must ensure GenAI is well-behaved and transparent. Validating the origin and governance of data is essential to fully embrace its power with confidence. As with many ‘game-changing’ technologies organizations will likely proceed with a level of caution – prioritizing trusted vendors, conducting validations and extended proof-of-concepts, and initially requesting known sources of generated responses.
Embracing the future of AI in facilities management looks promising. Leveraging Generative AI’s advanced capabilities can lead to unprecedented efficiency, cost savings, and strategic advantages. The key to unlocking this potential lies in a robust, integrated data framework and a commitment to transparency and governance. Transparency and governance levels will likely vary by industry as well as task. There will likely be different levels of standards established – individual company standards, community standards, professional organization standards, and regulatory standards. Organizations may establish process committees to document acceptable levels of transparency and may require assurances from solution providers detailing information governance.
In summary, the journey to fully realizing AI’s potential in facilities management is just beginning, but this technology is too promising to wait for the dust to settle. Facility Managers need to engage in AI discussions and embrace the opportunity for improving facility management. Start leveraging traditional AI to improve decision making today. Start learning about and investigating Generative AI for improving management tomorrow.