​Agentic AI Enters The Physical World

​Krish Ghosh is CEO/CTO of DreamzTech US.

So far, enterprise AI and agentic AI have focused mainly on things like chatbots, content creation, coding and knowledge assistance. Physical operations are the next logical space, and manufacturing companies and facility management firms are already deploying agentic AI in operational workflows. But the real world is less forgiving than those earlier applications, and companies need to approach implementation carefully.​

A manufacturing facility typically runs many separate systems, including ERP, CMMS, field service management and warehouse management, with data streaming in from RFID and IoT sensors. All of that data is fragmented, and when something breaks, a technician often has to manually open the maintenance manual, review previous job records, check the ERP and call their supervisor before they can decide what to do. That process can take hours.​

An AI agent can coordinate across all of those systems and respond in seconds. When a sensor detects an anomaly, it can pull the machine’s maintenance history, previous failures, relevant manuals, current parts inventory and available technicians with matching skills, then recommend the next action.​

Work that previously required four or five people manually collecting data and checking dashboards is now a single coordinated response.​

How To Set Up Agents That Work

One of the biggest mistakes I see COOs and plant managers make is trying to implement AI everywhere all at once. Instead, it’s important to choose a specific problem first, whether that means downtime, maintenance response, inventory discrepancies, service prioritization or asset visibility. You should define the business outcome and the KPIs you’ll track before you evaluate any technology.​

Human Oversight Is The Design

I’m optimistic about the future of AI in physical operations. It can be extremely valuable if done correctly, but it will only work if we take responsibility for setting it up carefully from day one.​