The industrial automation industry is moving into a new stage as artificial intelligence becomes increasingly connected with physical manufacturing systems. Instead of remaining primarily a software or data-analysis technology, AI is now being integrated with robots, controllers, machine vision, industrial networks and production processes.
Several developments this week provide a clear indication of this shift. IMTS 2026 in Chicago is putting industrial AI and intelligent automation at the center of its manufacturing technology program, while new robotics platforms are increasingly being designed with AI integration and connectivity as part of their core architecture.
IMTS 2026 Puts Industrial AI on the Factory Floor
The International Manufacturing Technology Show (IMTS) is taking place in Chicago from September 14 to 19, bringing together technologies covering CNC machining, automation, robotics, additive manufacturing, software and artificial intelligence.
One of the notable additions this year is the Industrial AI Arena, which focuses on practical applications of AI in manufacturing. The program covers areas including quality and inspection, process optimization, downtime reduction, cybersecurity, safety and demand forecasting.
IMTS is also holding a dedicated Industrial AI Conference on September 16. The conference is designed around practical factory applications rather than general AI concepts, with sessions addressing predictive maintenance, quality, edge and cloud computing, and different approaches to implementing AI in manufacturing operations.
The emphasis is significant because manufacturers are increasingly looking beyond experimental demonstrations. The key question is becoming how AI can solve specific production problems while working within existing industrial environments.
Robotics Platforms Are Becoming More AI-Ready
A major announcement at IMTS this week came from Universal Robots, which introduced its Gen 7 automation platform on September 14.
Rather than presenting Gen 7 simply as a new robot model, Universal Robots describes it as a broader automation platform combining robot hardware, controllers, software, interfaces, cables and ecosystem technologies.
The platform is designed to support advanced end-of-arm tooling, cameras, physical AI and modern industrial networking. Its architecture is intended to reduce the number of external components and simplify the integration of intelligent automation applications.
The new platform also includes the g-Series robot family, the CB7 Core controller, TP7 Core teach pendant, SP7 Smart Panel and PolyScope X software. The CB7 Core controller, for example, includes multiple Ethernet ports and configurable digital inputs and outputs, providing additional connectivity within the automation architecture.
This illustrates an important direction for the industry: intelligence is increasingly being built into the automation platform itself rather than being treated as a separate layer added later.
Physical AI Is Bringing Software Intelligence Into Industrial Equipment
The development of physical AI is another important part of this transition.
In traditional industrial automation, software typically operates within defined control logic. Sensors provide information, controllers process the information and actuators perform predetermined actions.
AI-enabled systems can introduce another layer of adaptability. Cameras, sensors and other devices can provide information that AI models interpret, while robots and automated equipment respond to changing physical conditions.
IMTS is showcasing AI-enabled robotics applications covering machine tending, bin picking, vision guidance, adaptive automation and mobile transport. These applications demonstrate how AI can help automation systems handle environments that are more variable than traditional fixed-cycle applications.
The technology is particularly relevant to high-mix manufacturing, where production requirements may change frequently. IMTS has highlighted AI-enabled robotics as a way of reducing programming requirements and enabling more adaptive production through perception, planning and sensor-guided operations.
Manufacturing Data Is Becoming Another Important Part of Industrial AI
AI adoption in manufacturing is not limited to robots.
A significant challenge for manufacturers is the large amount of information accumulated over years of production. Engineering drawings, equipment records, procurement information and other manufacturing data may exist in different formats and systems.
Recent developments from CADDi illustrate this direction. The company uses AI to make manufacturing drawings and procurement data searchable by characteristics such as shape, text, dimensions and part names. Its platform is intended to make information embedded in existing manufacturing data more accessible for engineering and procurement activities.
This is important because manufacturing AI depends not only on computing power, but also on the quality and accessibility of industrial data.
As manufacturers attempt to apply AI to maintenance, production planning, engineering and procurement, previously isolated information is becoming a potential source of operational intelligence.
Traditional Automation Hardware Remains Part of the Transition
The increasing use of AI does not mean that conventional automation components are disappearing.
In fact, intelligent manufacturing systems still depend on physical equipment to collect information and control machines. PLCs, I/O modules, industrial communication devices, sensors, drives, motor control equipment and power-related components continue to provide the connection between software intelligence and physical production.
This creates an important distinction between the development of new automation technologies and the operation of existing factories.
New production lines may be designed around increasingly connected automation architectures. Existing factories, however, often contain equipment installed over many years and from different generations of automation platforms.
For these facilities, modernization may involve adding new digital capabilities while continuing to operate established control hardware.
Automation Modernization and Spare Parts Will Continue to Overlap
As industrial systems become more connected, maintenance and procurement requirements are also becoming more complex.
A production line may combine modern robots and vision systems with established PLCs, remote I/O modules, drives, relays and industrial communication equipment. When a component fails, the production impact can extend beyond the individual device because it may affect an interconnected section of the manufacturing process.
For maintenance and procurement teams, reliable access to replacement components therefore remains an important part of automation modernization.
The industry is not moving from traditional automation to AI in a single step. Instead, manufacturers are gradually adding intelligence to existing production environments while replacing, upgrading or expanding individual components as required.
The Next Stage of Automation Will Be More Integrated
The latest developments from IMTS and the wider automation industry point toward a more integrated manufacturing environment.
AI is becoming connected to robotics. Robotics is becoming more closely integrated with vision and industrial networking. Manufacturing data is becoming more accessible through AI-based tools. At the same time, established automation hardware continues to provide the physical control layer underneath these technologies.
This means that the next stage of industrial automation is likely to involve cooperation between multiple technology layers rather than a single technology replacing another.
For manufacturers, the practical focus will remain on improving production flexibility, reducing downtime, increasing equipment utilization and making better use of existing industrial assets.
As AI moves closer to the factory floor, the ability to connect new intelligent technologies with reliable automation infrastructure will become increasingly important.