TECH INSTINCT PODCAST | EPISODE 15
Rethinking Where Your AI Workloads Should Run
AI is easy to start in the cloud. But as adoption grows, the economics and infrastructure requirements can begin to change.
In this episode of Tech Instinct, MicroAge explores why organizations are taking a fresh look at where their AI workloads should run and why on-premises infrastructure is becoming part of the conversation again.
As AI moves from experimentation to broader business use, factors such as cost, data security, control, performance, and workload predictability can significantly influence infrastructure decisions. For some organizations, continuing to scale entirely in the cloud may make sense. For others, bringing certain workloads closer to the business can provide greater control and a more predictable operating model.
The conversation also explores why there isn’t a one-size-fits-all answer. The right AI infrastructure strategy depends on the workload, how frequently it runs, the sensitivity of the data involved, performance requirements, and how quickly demand may change.
If you’re a CIO, IT leader, or technology decision-maker evaluating how to scale AI while balancing performance, security, control, and cost, this conversation is for you.
