For companies like Rockwell, this evolution represents an opportunity to integrate edge AI capabilities throughout its product portfolios. The business outcomes from properly managed edge computing are substantial, including affordable access to data, faster software deployments, future-ready analytic platforms, improved security posture, better scaling of digital transformation initiatives, and reduced TCO.
The Edge AI Foundation says CIOs and enterprises want automation and smart devices at the edge. “Edge AI is all about running AI workloads where the data is created, and the gravitational pull toward the edge means lower cost, lower power, more impact, typically, and that can also mean enhanced privacy, latency, flexibility, and clearing,” says Pete Bernard, the nonprofit’s CEO, noting that CIOs are in charge of figuring out the information strategy. “You want to move your compute as close as possible to where the data is created, avoid ingress and egress fees to clouds as well as OpEx costs, and have more control over your processing in general.”
As platforms and technologies continue to mature, we can expect AI to become increasingly embedded in physical systems across industrial environments.
