One of the most potent applications of AI is predictive maintenance, which mitigates physical damage before it occurs. For example, AI algorithms can forecast when a building’s boiler is likely to fail based on vibration data, usage rates, and environmental inputs. By servicing that boiler before it breaks down, owners avoid costly repairs—and eliminate the insurance claims that follow. The broader implications for loss prevention are significant:

• Water damage, one of the costliest claims in real estate, can now be mitigated by sensors that shut off valves when they detect abnormal flow.
• Fire risks are reduced through predictive analytics monitoring electrical loads or smoke detector telemetry.
• Tenant liability is minimized by tracking security footage and access controls to flag unauthorized activity.

Kris’s approach, which integrates these preventative technologies into the foundational risk management strategy, demonstrates a shift from insurance as a backstop to insurance as a partnership.