When it comes to industrial automation, the first word that should come to mind is “opportunity,” because that’s exactly what it provides for manufacturing operations, whether it is a two-person shop or a 2,000-person plant.
Another word associated with it is “productivity,” or the ratio of output to input. Automation is a beneficial input.
Nowadays, for various reasons, the availability of skilled – and even not-so-skilled – personnel has decreased. And U.S. tariffs are making material inputs – with steel, aluminum, and copper facing rates of 50% – more expensive, so the ability to enhance output is essential.
Few disagree with the importance of automation for manufacturing competitiveness: 92% think that’s the case, according to a recent survey of 214 U.S. manufacturers conducted by IndustryWeek and Vention, an automation company that provides a cloud-based industrial automation platform for manufacturers.
However, the survey also found that only 37% of manufacturers have automated at scale. Yes, more manufacturers have some automation here or there in their plants, but the number of those who have gone beyond individual projects to embedding automation into their operations is comparatively small.
The good news is that 73% plan to increase their automation investment over the next three years.
This isn’t necessarily the future of industrial robots. BMW tested Figure 01 in its plant in Spartanburg, South Carolina. (Image courtesy of BMW)
This Is Not New
What is surprising – and somewhat disappointing – is that robots aren’t more widespread in the United States, despite being pioneered domestically and being a fundamental yet flexible automation technology.
The first industrial robot, from Unimation, was installed in a General Motors trim plant in New Jersey back in 1961.
That was the very first. Anywhere.
Robot use has increased in the decades since. According to the International Federation of Robotics, in 2023, the automotive industry had 135,461 robot installations worldwide. Likewise, robots have increased in electrical and electronics (125,804 installations) and metals and machinery (76,831) industries.
Still, robot density in the United States, as measured by the number of robots installed per 10,000 employees, is behind many countries.
The number of robots per 10,000 employees, according to the IFR:
Republic of Korea – 1,012 robots
Singapore – 770 robots
China – 470 robots
Germany – 429 robots
Japan – 419 robots
Sweden – 347 robots
Denmark – 306 robots
Slovenia – 306 robots
Switzerland – 302 robots
United States – 295 robots
This shows there is opportunity for U.S. manufacturers to increase their productivity and thereby become more competitive at home and in the world market.
The AI Element
One of the major developments changing the deployment of robotic automation is artificial intelligence (AI).
According to Vikas Butaney, senior vice president and general manager of Cisco Secure Routing and Industrial IoT:
“We’re seeing companies bring AI to life in impactful ways: from deploying machine vision to ensure product quality in manufacturing, to rolling out AI-powered automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) that are reshaping material handling and logistics, to leveraging agentic operations that drive more autonomous, adaptive, and efficient workflows across industrial environments.”
Butaney and his colleagues saw that as part of Cisco’s 2026 State of Industrial AI Report, a global survey conducted in 19 countries and across 21 industry sectors, including manufacturing. And the study shows that the No. 1 reason, with 63%, for the adoption of AI in manufacturing is improving productivity.
Of course, AI isn’t necessarily automation, as it can be used for planning, logistics, and other functions.
Yet nowadays, AI and robots are becoming more closely aligned.
Closing the Sim-to-Real Gap
On March 9, 2026, Marc Segura, president of ABB Robotics, announced, “Today, using NVIDIA accelerated computing and simulation technologies, we have removed the last barriers to making industrial and physical AI a reality at a global scale by closing the sim-to-real gap.”
In other words, ABB is integrating Nvidia Omniverse libraries into its RobotStudio, a robotics programming, design, and simulation suite. Omniverse is a platform of libraries, microservices, and real-time 3D technologies that can be used to robustly and accurately create and simulate industrial twins. AMT – The Association For Manufacturing Technology is working with Nvidia on Omniverse implementation in manufacturing operations, including deployment with MTConnect.
Deepu Talla, Nvidia vice president of robotics and edge AI, said, “The industrial sector needs physically accurate simulation to bridge the gap between virtual training and the real-world deployment of AI-driven robotics at scale.”
If you’re going to create a simulation for training robots to perform tasks, making it as close to physical reality as possible is important.
ABB claims manufacturers will see significant benefits by using RobotStudio HyperReality to create production lines:
Setup and commissioning times can be reduced by up to 80%
Costs can be reduced by up to 40% (because there is said to be such fidelity with the physical world, physical prototypes aren’t necessary)
Time-to-market for complex products can be reduced by 50%
Talla explained:
“If you look at robotics and automation for the last 50 years or so, it’s been deployed mostly in the high-volume, low-mix applications – things like the automotive industry and high-volume electronics. But much of the world is in small and medium enterprises.”
He said that a problem is that setting up and programming the robots can be too expensive for the smaller operations, particularly because they tend to have a high mix of tasks rather than the repetitive production characteristic of larger operations.
The solution?
“The only way to solve that is to use a reasonably good enough general-purpose AI brain, and that’s what we’re able to do with the latest-generation AI technology,” Talla said, adding, “And before you actually go and deploy this in the factory or your manufacturing facility, you want to be able to test it in simulation because it’s faster, safer, and cheaper.”
Working with Nvidia, ABB Robotics is creating more accurate and realistic simulations for training robots. The scene above is what could be created with its simulation system; below is the Nvidia-powered version. (Image courtesy of ABB)
Can It Be Done?
All of that said, simulation, AI, and the like may appear beyond the competence of small or medium-sized manufacturers. Foxconn using this tech is one thing – but it’s another for less-capitalized shops. So, MT Magazine asked whether shops would need to find hires from Stanford University or the Massachusetts Institute of Technology to use this tech.
Talla answered with an analogy – the release of ChatGPT in November 2022:
“Two fundamental things happened, right? The first one, of course, is that the model was general purpose – that it could do multiple tasks.
“Before ChatGPT, you had AIs for specialists in one specific task. ChatGPT changed that with being a good generalist model. The second thing was, of course, it was so easy to use for anybody literally on the planet. That’s the same idea we have for robotics experience.”
He said that the object will be to go from traditional robot programming to teaching or instructing them what to do – and doing so in a way that will be accurate in the physical world.
Do You Need a Humanoid?
Another development in the automation world is the introduction of humanoid robots. Although Tesla’s Optimus may be the most famous, there are several, including the Figure series from Figure AI, Apollo from Apptronik, and Digit from Agility Robotics.
FANUC is among the largest industrial robot companies in the world. Mike Cicco is president and CEO of FANUC America Corp. Although the company doesn’t offer bipedal, human-shaped robots, Cicco said that if the need is for two arms working together, they can provide that – in fact, one control can orchestrate four arms. If the situation requires a robot that can move on the factory floor, they have that, too: mount a robot (or two) on a mobile robot, and it can go where it is needed.
Cicco explained that some people are interested in the humanoid robot because they may have a task where there is high absenteeism, so swapping out a person with a robot to do the task seems to make sense.
Cicco thinks the better approach is: “Look at what the problem is and not how a person currently does it. Solve the problem in the most effective way possible – not try to recreate exactly what a person does, step by step.”
One of the things they’re finding as they develop applications is using collaborative robots (cobots) to work alongside people – with the robots providing supplemental assistance – leverages the talent and capabilities of the individuals.
Help Wanted — and Needed
In many ways, it comes down to people. In an address about U.S. manufacturing presented in February, Carolyn Lee, president of the Manufacturing Institute (MI), stated:
“Manufacturing has been facing a structural talent shortage for many years, one that could leave us with 1.9 million unfilled manufacturing positions by 2033, according to the MI’s research with Deloitte.”
She added:
“Tomorrow’s manufacturing workforce will need digital fluency, comfort with data, and the ability to work alongside intelligent systems. People often ask me whether AI is coming for manufacturing jobs. Here’s what I believe: AI won’t take your job. But jobs will go to people who know how to use AI. People who can leverage new technologies into the way they operate – who can use it to help them solve problems, make better decisions, and get more done – will succeed in the job market and power the future.”
The “intelligent systems” she mentions are undoubtedly based on robotic automation powered by AI and the like. And while 2033 and the impending labor crunch may seem like a long way off, rest assured – it isn’t.
If the objective is to have a mobile robot rather than thinking a humanoid is the answer, a more conventional robot mounted on an autonomous mobile robot or an automated guided vehicle can be a more effective approach. (Image courtesy of FANUC America)
To read the rest of the State of Automation Issue of MT Magazine, click here.
