In many real-world scenarios, cloud-centric AI systems are not viable due to latency, bandwidth, cost, or infrastructure constraints.

This makes it necessary to rethink how intelligence is executed and how data flows across the system, moving processing closer to where data is generated. In this context, the combination of edge computing and connectivity enables a new class of distributed intelligence, where processing and communication are tightly integrated.

This keynote will explore how Edge AI can support faster decision-making, lower latency, improved privacy, and greater operational resilience by processing data locally while remaining connected to the broader IoT ecosystem.