Multi-access edge computing (MEC) is about moving computing power closer to where data is created and where decisions need to be made. Instead of sending everything back to a distant cloud or data center, MEC processes information at the “edge” of the network—near devices, sensors, and users.

In the video with IndyCar champion Will Power, racing is used as an analogy: just as decisions in a race need to happen right where the action is on the track, MEC brings compute resources closer to the “track” of your applications. This helps reduce the time it takes for data to travel back and forth, which in turn lowers latency and improves responsiveness.

Latency is the delay between sending a request and getting a response. When data has to travel long distances to a centralized cloud or data center, that delay increases.

By placing compute resources at the edge of the network, closer to users and devices, multi-access edge computing shortens the path that data needs to travel. This can significantly reduce latency and deliver faster response times.

Using the IndyCar analogy, it’s like having your race engineer right in the pit lane instead of in a remote location. The closer they are to the car and the track, the faster they can react to what’s happening in real time.

MEC makes the most impact in scenarios where real-time or near real-time responses are important. Any environment where “the action” is happening quickly and decisions need to be made on the spot can benefit from compute being closer to the source.

In the racing analogy with Will Power, every millisecond matters. Similarly, in digital applications—such as connected vehicles, industrial automation, or immersive media—bringing compute closer to where data is generated helps teams react faster, optimize performance, and reimagine how they deliver experiences.