The Internet of Things - networks of sensors and connected devices embedded in buildings, cities, and infrastructure - generates enormous volumes of data that AI can use to optimise how systems operate. Smart buildings use AI to manage heating, cooling, lighting, and ventilation based on occupancy patterns, weather forecasts, and energy prices, reducing energy consumption and improving comfort. Water networks use AI to detect leaks, predict pipe failures, and optimise treatment processes. Transport infrastructure uses AI for traffic signal optimisation, congestion prediction, and incident detection. The value proposition is compelling: infrastructure represents massive capital investment, and even small efficiency improvements in how it operates translate into significant savings and environmental benefits. The challenges are around interoperability - infrastructure systems are often decades old, built by different vendors, and not designed to share data. Cybersecurity is also a serious concern: connected infrastructure systems are attractive targets for attackers, and the consequences of a compromised water treatment system or power grid are far more severe than a hacked website. Deploying AI in critical infrastructure requires robust security, redundancy, and careful testing.