Agents
P&G once tracked truck deliveries by phoning every driver; an AI agent now reschedules its warehouse and distribution-centre appointments with no human involved. Milwaukee Tool is implementing Oracle agents for supply planning, shipping and maintenance. Both were described at an IIoT World panel.
The agents that stick are scheduling and rebooking: bounded decisions with a clean audit trail.
Deployment
Data quality used to sit with data scientists: the model needed clean inputs, they cleaned them, and the organisation moved on. AI agents break that pattern. They consume data at machine speed with no human in the loop to fix what is broken, which moves readiness out of analytics and onto operations.
Before funding an agent pilot, settle who fixes bad data at 3am. The agent will not.
Deployment
Enterprises are placing AI inference servers closer to their data and users to meet performance and latency demands. RTInsights notes that the physical location of those servers frequently introduces data-sovereignty issues that the latency case alone does not address.
Edge inference solves latency and creates jurisdiction. Settle where data may legally sit before buying the box.
Workforce
EE Times reports from DAC 2026 on a shift from AI-assisted design tools toward AI-mediated engineering, centred on agents, engines and the question of trust, and argues the industry has reason for optimism about how that transition is going.
Design tooling is arguing about trust boundaries a year ahead of the plant floor. Watch how it settles.
Frontier
Arm used a large set of releases this week to stake a claim on being the agentic-AI computing platform for every use case. Embedded Computing Design frames it as a determination to own the substrate rather than as a single product launch.
A vendor announcement, not a deployment. File under roadmap risk for anything you specify on Arm.
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