The Inevitable Robotization

While some may argue that overall unemployment is rising - and that we already have enough workers - this assumption does not hold true across all industries. In fact, certain sectors are experiencing labor shortages where automation and robotics are the only path to scaling operations.

Take welding, for example. The American Welding Society (AWS) says the U.S. needed over 400,000 welders in 2024. A big reason? Retirements. About 21% of welders are over 55 now, and the younger generation isn't stepping in fast enough. Welding is critical for manufacturing, especially with all these new infrastructure projects kicking off across the country.

And it's not just welding - this is happening across other industries. Construction alone required more than 500,000 workers in 2024. The World Health Organization (WHO) estimates a shortage of 4.5 million nurses and 0.31 million midwives by the year 2030.

The good news is that working robotic solutions already exist to fill some of these gaps:

BUT, while robots are increasingly taking over repetitive tasks, they won't replace every welding or construction job. There are still plenty of situations where it doesn't make financial sense to buy an expensive robot.

Similarly, I'm skeptical about robotization in places where human-to-human interaction is essential. For example, a waiter in a luxury restaurant is unlikely to be replaced anytime soon.

Speed and Precision

Labor market issues are just one piece of the equation that drives robotization forward. Just take a look at the products we use every day - they're getting smaller and more complex every year. Think of microprocessors and other electronics. We're becoming more and more dependent on these technologies, and we constantly need more of them. Every year, there's a new version of our smartphones, and we rush to upgrade 😊.

Sure, human hands can craft the most beautiful and delicate things. But when it comes to combining extreme precision with high speed, it's nearly impossible for us to keep up with machines. That's why, like it or not, as technology evolves and products shrink in size, the amount of work for robots continues to grow. They can execute the same operation with extreme precision and speed, over and over again, without fatigue or variation.

Check out this video:

Speed and precision are two of the biggest reasons why robotics adoption is gaining momentum - particularly in sectors like electronics, aerospace, and advanced manufacturing, where flawless execution and consistency at microscopic scales are critical.

Safety and the "Dull, Dirty, Dangerous" Work

Another major driver is that some of the jobs are also inherently hazardous. Industrial painting, for instance, exposes workers to toxic fumes and chemicals. Metal finishing and polishing generate fine dust particles that can seriously damage the lungs. Understandably, this makes such jobs less attractive to potential workers. Moreover, companies must invest heavily in safety equipment, protective gear, and regulatory compliance to ensure worker safety. Robots don't suffer from injuries or lung damage and can safely operate in harmful environments - allowing companies to save money.

Imagine a small furniture paint shop where a robot works 24/7, painting parts one after another as they move along a conveyor belt while another robot packs them.

The Role of AI

Until recently - and even now - most robots have operated using rigid algorithms. This works fine in large-scale manufacturing, where each robot has a narrow task that it repeats hundreds of times throughout the day and it's not expected - or even possible - to switch tasks on the fly.

But for small businesses or workshops, investing tens of thousands of dollars in a robot that can only do two or three specific tasks isn't practical. Asking it to perform something new often means bringing in a costly specialist to reprogram it - an expense many small businesses simply can't justify. That's why, for owners of small factories or logistics centers, it's often still easier and more cost-effective to hire people to get the job done. But AI is about to change that.

Recent breakthroughs in small language models (SLMs) and vision language models (VLMs) are laying the groundwork for more flexible robots and cobots. These advances allow robots to recognize objects or scenarios they've never seen before and adapt accordingly.

In the near future, this could mean small business owners will be able to buy robots with human-like flexibility capable of understanding voice commands like "move the pallets in the morning" and "pack the boxes in the afternoon," without the need for reprogramming.

Finance

For small and medium-sized businesses, robots are still a significant financial commitment. A single industrial robot can cost anywhere from $25,000 to $100,000, not including costs for integration, setup, and training. The total cost of ownership over a robot's life — including maintenance, software updates, and potential downtime — can be even higher.

The main financial benefits of robotics usually come from economies of scale and long-term deployment. For instance, in high-volume production environments where a robot performs the same task thousands of times a day, the return on investment is clear. But for a small workshop that needs flexibility, that same robot may sit idle or require expensive reprogramming to switch tasks—eroding the value.

However, new business models like "Robotics as a Service" (RaaS) are emerging, where companies can lease robots instead of buying them outright.

Conclusion

The trend is clear: barriers are slowly being removed, and broader adoption is becoming more realistic for businesses of all sizes.

That said, recent tariff policies could have a real impact on the trajectory of robotization. On one hand, increasing tariffs on imported robotics components could make automation more expensive, potentially slowing down adoption. On the other hand, these same policies might stimulate domestic innovation, encouraging local production of robotics hardware and creating a more resilient, homegrown automation ecosystem. Of course, the reality will probably be somewhere in the middle.

At the end of April, I'll be attending DeviceTalks and Robotics Summit in Boston, and I'd be happy to continue this conversation ...