We’re living in the age of the artificial intelligence (AI) boom. This technology is bolstering rapid advancements in automation, including industrial automation; industrial automation had a market size of $221.64 billion in 2025, and that is expected to surpass $300 billion by 2030. In order to keep up with competitors, implementing manufacturing process automation is essential – and it’s equally important to stay on top of emerging automation technologies so you don’t get left behind in the long run.

The experts at Isthmus are here to keep you up to date. In this blog, we’re sharing the top five automation in manufacturing trends we project for 2026.

Cobots

What it is: Cobots, or collaborative robots, are robots that work alongside humans. In manufacturing, they are commonly used in many different areas like assembly, machine operation, packaging, and quality control. The goal of cobots is to free human workers from repetitive or hazardous tasks, empowering the human workers to move to more valuable positions. Cobots also increase the quality and throughput of the final product by removing human error and physical limitations.

Why it’s trending: As cobots in manufacturing become increasingly ubiquitous, their designs are becoming increasingly refined. Newer models are more lightweight and easy to reposition and reconfigure, allowing for greater flexibility in their functionality. Furthermore, cobots are being integrated with AI that empowers them to perform predictive maintenance, better optimize their movements, and learn by demonstration rather than complex and time-consuming programming.

Automated Guided Vehicles

What it is: An automated guided vehicle (AGV) is a computer-controlled driving robot that transports materials on the factory floor. AGVs move along preset paths set with magnetic tape, wires, laser, or vision systems. Much like with cobots, AGVs allow workers to move from repetitive transport tasks to value-add positions while improving the overall efficiency and safety of your operation.

Why it’s trending: New AGVs are equipped with AI tools like computer vision and sensor fusion. Now, AGVs can break free from preset pathways and move autonomously. AI-powered AGVs can streamline their routes, predict maintenance needs, and perform more complex tasks by continually learning from experience. Autonomous Mobile Robots (AMRs) are undergoing similar upgrades.

Robotic Process Automation & System Integration

What it is: Robotic process automation (RPA) is a type of software that uses bots to perform digital tasks in place of humans. RPAs perform within set rules and inputs to ensure they operate as expected. They can perform several key manufacturing tasks, like real-time stock tracking, quality checks, and reporting. RPAs are part of a larger robotics system integration plan, in which an automation engineer connects the hardware and software components of an entire manufacturing process into one unified and efficient automated process.

Why it’s trending: We are starting to see RPAs, and robotics system integrations as a whole, merge with AI and machine learning. These AI-enhanced RPAs can learn and automate end-to-end workflows rather than the singular repeatable tasks they were previously capable of. The completed integrated system includes autonomous, AI-enabled hardware, software, and robotics systems.

Industrial IoT Platforms

What it is: Industrial internet of things (IIoT) platforms connect, manage, and analyze the data that comes from the devices, sensors, and machines in your production process. They bridge your digital systems to the shop floor. IIoT systems provide real-time insight into your operations and optimize your production process.

Why it’s trending: AI can now empower IIoT platforms to perform edge computing, in which an IIoT platform processes data locally (rather than on the cloud). IIoT platforms with edge computing can produce and analyze real-time data faster, take on more complex tasks autonomously, and create digital twins of physical equipment or processes. These digital twins act as virtual test models to improve the overall performance and predictive maintenance of their physical counterparts.

Machine Vision Systems

What it is: A machine vision system utilizes a combination of cameras, software, and processing hardware to automate visual industrial tasks like inspection, sorting, guidance, and quality control. They are a much more efficient and accurate replacement for tasks that heavily rely on human vision inspection.

Why it’s trending: In 2026, we’re seeing AI and deep learning enhancements that allow a vision system to identify more discrete or minute objects without extensive programming. Now, a machine vision system can learn from all of its prior experiences and improve as it continues working.