N. Raghuraman's Column: What do you need to do today to be part of the 2030 workforce?

Your colleague on the assembly line of GE Appliances' 1.1 million square foot cooking-appliance plant in the US could be a form of physical AI. Don't mistake it for a two-legged human-like robot. I'm talking about industrial automation and physical AI, where machines are getting better at feeling, reacting, and completing complex physical tasks. Six-axis robotic arms flip giant stoves, glue glass cooktops to metal frames, and program control boards. Humans and machines are in a race to build a unit every 15 seconds, working together. The entire operation is monitored and data is constantly transmitted from the system to the managers, so that every possibility of productivity can be harnessed. You may be wondering what's new in this? An analytical person could argue that manufacturing, especially low-margin consumer-goods businesses, doesn't even have much of a choice other than high-speed production. It's probably necessary to build a unit every 15 seconds. And then how interesting can it be for a human to work in this AI-dominated environment? But it's not as boring as you might think. In an eight-hour shift, a person has to be fast and focused, but his job is not necessarily to repeat the same physical movement over and over again. Take the factory mentioned above. If the camera catches a glitch, such as a gasket not in the right place, the AI-driven inspection system can immediately stop the assembly line and alert human supervisors by playing rock music. This completely changes the nature of the work. Employees are no longer people looking at the conveyor belt without thinking. They have become the active first responders of a dynamic system. They are fast becoming 'robot wranglers' – people who monitor robotic cells, monitor systems, fix technical glitches and optimise the performance of machines. The change is that now instead of repetitive work, the technology that does this work has to be managed. Gone are the days when employees had to lift heavy metal chassis for hours or perform tiring awkward wrist-movements. When machines handle a large proportion of physical strain, humans can be more mentally alert and focus on analysing problems and making decisions. Modern plants will also need more flexibility. Employees can be rotated between different stations and responsibilities. A worker handling an automated glass-cooktop assembly cell in the morning can monitor autonomous material-handling vehicles in the afternoon. This is where the job scenario of 2030 gets interesting. If the factory of the future needs a technology problem solver, what should you do today – if you want to be a part of such factories in 2030? 1. Learn the basics of AI and automation. You don't have to be an AI scientist, but you should understand how sensors, machine vision, robotics, automation systems, and AI-based decision-making work. 2. Develop data literacy. A future worker has to be comfortable reading the dashboard, understanding basic statistics, recognizing unusual patterns, and using data to make decisions. If a machine says something is wrong, instead of waiting for the engineer, the worker should know what that information means. 3. Early knowledge of Python, PLC programming, robotics software or even industrial control systems can make a worker far more valuable in an automated factory. 4. Strengthen troubleshooting and problem-solving skills. The machine can recognize a glitch, but humans will still be needed to understand why it happened, what to do next, and make sure it doesn't happen again. The idea is that by 2030, the most employable factory worker will probably not be the person who can do the faster work with his hands. He can be someone who can understand the machine, question its data, fix its glitches, and teach it to do a better job. The future smart worker will have to be replaced, before the factory can replace him.