Pick-and-pack robots, welding cobots, and other smart factory technologies are changing the nature of the skills gap inside of the manufacturing and warehousing industries.
- Companies like Amazon are continuing to rev up robotics within their factories. Amazon aims to automate 75% of its operations, replacing up to 600,000 warehouse jobs by 2033 through advanced robots and cobots.
- This wave of automation is reshaping the broader manufacturing sector, which faces a growing talent shortage (up to 1.9 million unfilled roles by 2033). As some jobs are automated, the skills needed for factory work are changing — some automation improvements lead to deskilling, while others create a need for new skillsets.
- Factories are now smart, connected ecosystems that integrate AI, cobots, digital twins, and IoT systems. This Fourth Industrial Revolution marks a leap toward self-optimizing, data-driven production that blends human collaboration with intelligent automation.
Welcome to the future of warehousing and manufacturing — or should we say, the automated present? Yes, we’ve made it: to an era of smart robotics that is simultaneously deskilling some roles and upskilling others. And it’s broadly reducing the number of workers required to achieve the same, and higher, levels of production.
Amazon, the US’s second largest private employer, is aiming to automate 75% of its operations with both robots and cobots. In the process, it’ll also drive down the need for new workers: about half a million jobs will be replaced by robots.
Amazon’s automation team expects that the company will be able to avoid making over 100,000 new hires by 2027. By 2033, the combination of new automation tools and sales estimates that are double Amazon’s current orders would translate to almost 600,000 positions that would not need to be filled.
Amazon announced a newer, more capable warehouse robot, Blue Jay, in mid-October 2025. Vulcan, another robot released this past May, represented a leap forward in pick-and-pack robots because of its touch sensitivity. And a number of previously-introduced robot models have helped with Amazon’s warehouse tasks over the years.
Amazon warehouses leaning into automation exemplifies broad shifts to more automation in other industries, too. In some cases, like for manufacturing, widespread automation could help combat a forecasted mass shortage of talent.
And automation could also be good for employees stuck working jobs that fall into the three Ds: dull, dirty, and/or dangerous — like straightening candlewicks, lifting pallets, tightening bolts, and other repetitive or strenuous tasks.
In fact, the introduction of robots has decreased the rates of worker injury. Pick-and-pack robots, for example, can help by completing more dangerous and strenuous procedures, allowing workers to stay in the “power zone,” roughly between mid-thigh and shoulder height, where back strain is the least risky.
Yet automation is also shaking up the manufacturing industry, which is currently contending with worker shortages and attrition.
Part of the reason for worker shortages is an outdated perspective of these jobs as dirty, which is less and less the case due to the introduction of robotics and automation. But it’s also due to a lack of individuals pursuing education for these roles — roles that often need precise knowledge that can’t be applied or acquired elsewhere.
And this knowledge base, too, is changing. In manufacturing, human-assisted automation — like welding cobots — are helping workers work faster and with less of a need for technical skill, but learning to use robots also requires its own training, putting a spin on the traditional skills gap.
Nearshoring demands
Recent pressures for nearshoring, such as tariffs, are putting pressure on manufacturers to increasingly automate facilities to make up for a labor shortage.
However, while robots may address the labor shortage for entry-level roles, they create another demand — for skilled engineers.
A third of engineering roles go unfilled each year. According to the U.S. Census Bureau’s Quarterly Survey of Plant Capacity, about 20% of US manufacturing plants that weren’t at full capacity in 2024 cited insufficient labor/skills as the key constraint.
As a result, the labor market can’t support the mass reshoring that current policies are pushing, without significant investment in both labor and automation.
Demand for tech jobs
A report from Deloitte and The Manufacturing Institute estimates a need of almost 3.8 million net new employees in manufacturing by the year 2033. About half of these jobs could stay empty if the talent gap isn’t closed.
The demand spans both skilled and unskilled labor, yet the fastest-growing needs are in advanced technical areas like simulation and simulation software, enterprise information management, and cloud computing. As factories grow more digitized and automated, companies also need “robot wranglers” — workers who can oversee and maintain intelligent systems.
Compounding the challenge, factors like tariffs and the trend toward nearshoring may have further reduced hiring in some sectors, leaving manufacturers caught between rising production goals and a shrinking pool of qualified workers.
Factories are way smarter now
Smart factories are quickly overshadowing the dirty, noisy, and inefficient factories of the past. These new facilities combine robotics, IoT sensors, cloud computing, and AI-driven analytics to create fully connected ecosystems where machines communicate with each other and with human operators in real time.
In these environments, data from every conveyor belt, robotic arm, and workstation is constantly collected and analyzed to predict maintenance needs, optimize workflows, and even reduce energy consumption.
Unlike traditional factories — often associated with repetitive, dangerous work — smart factories rely on automation to handle the dull and hazardous tasks, freeing workers to focus on oversight, problem-solving, and advanced technical operations.
Even small- and mid-sized manufacturers are embracing these technologies through Industry 4.0 initiatives, connecting machines via the industrial internet of things (IIoT) and using predictive analytics to make faster, data-informed decisions.
Industry 4.0
Industry 4.0, also known as the Fourth Industrial Revolution or 4IR, refers to the rapid technological transformation reshaping manufacturing in the 21st century.
Building on the Information Age of the Third Industrial Revolution, Industry 4.0 represents a new era in which artificial intelligence, the Internet of Things (IoT), and advanced robotics converge to create smarter, more interconnected production systems.
Popularized in 2016 by Klaus Schwab, founder and former executive chairman of the World Economic Forum, the term describes what he saw as a major shift in industrial capitalism — one marked by fundamental changes in global production, supply networks, and the automation of traditional manufacturing through smart technologies.
Core technologies in Industry 4.0:
- AI & machine learning (self-optimizing systems)
- Industrial IoT (Internet of Things)
- Cobots and advanced robotics
- Cloud + Edge computing
- Digital twins (virtual replicas of physical systems)
- Big data + predictive analytics
- Smart factories + connected supply chains
Cobots
The US cobot market size was estimated at $133.1 million in 2024 — and is expected to grow at a CAGR of 29.7% from now until 2030.
Collaborative robots, or cobots, as they’re called, work alongside human workers, taking on undesirable tasks and those that would most likely lead to staff injuries. They also represent a significantly lower cost for entry for manufacturing companies, since they’re cheaper than their bigger industrial robot counterparts.
Cobots are becoming increasingly easier to operate as well — some can be programmed from a tablet, or even a phone.
As a result, robots can help address the labor shortage issue in manufacturing by taking on the most physically dangerous or repetitive tasks in a warehouse, enabling existing workers to be more productive and take on tasks that require more cognition or dexterity.
However, the reverse may also happen through the process of deskilling. Workers may lose out on skills that are developed by robots instead, and be stuck doing monotonous jobs. In fact, research going back at least to the 1940s linked automation to worse job quality and worker opportunity — think of conveyor-belt operations vs. skilled tradesmen crafting goods by hand.
The risk of deskilling is real — unless management and employee workforce planning teams do something about it.
The upside is that automation can just as often lead to upskilling, since workers gain opportunities to learn how to operate machinery and automated programs, or in the case of welding cobots, how to weld more easily.
Employees have just as much of an opportunity to take on more rewarding work, as long as the proper training and upskilling routes exist.
Digital twins
Factory digital twins are real-time virtual representations of a factory’s floorplan, equipment, and workflows. By mirroring the physical environment in a digital space, manufacturers can visualize operations as they unfold and make more cost-effective, data-driven decisions.
These models help teams gain a deeper understanding of complex physical systems, identify inefficiencies, and test process improvements before applying them in the real world.
With digital twins, manufacturers can run “what-if” simulations to predict the outcomes of new layouts, maintenance schedules, or production changes without disrupting current operations.
What does automation mean for the manufacturing workforce?
The relationship between the manufacturing and warehousing skills gaps and automation is complex. Automation both raises certain skill requirements, decreases others, and broadly changes the nature of the gap by deprecating certain skillsets and birthing new ones.
By automating the dullest and dirtiest tasks, robotics reduce the number of workers needed for repetitive, low-skill tasks — but can also make more difficult tasks, like welding, more manageable, with the right technical skillset.
As manufacturers adopt more smart machines and other Industry 4.0 tools, the new types of skills the workforce will edge toward include increased digital literacy, data interpretation, and machine-maintenance rather than just manual operation.
It’s important to point out that workers strongly prefer robots to take over the dull jobs, not the creative, interesting ones.
Take this example from nursing: while nurses’ unions in the US have protested the use of AI in formulating care plans and scheduling appointments, robots — the kind that chauffeur medicine from one end of a hospital to the other — are far more welcomed, according to a recent study.
When it comes to automation, cobots, and increased technology, it’s crucial employers address the human side of the equation.
That means designing training programs that prepare workers to collaborate with machines, not compete against them. It also means communicating how automation fits into a company’s long-term growth and workforce strategy, rather than presenting it as a threat.
And as these skillsets evolve, it’s important to use technology to find the workers who have those in-demand skills. eSkill’s pre-hire assessments have grown and changed considerably over the last 20+ years — leading to new assessments that measure the skills required as manufacturing industry requirements evolve.
Who knows? Maybe a “robot wrangler” eSkill test is closer than we think.
Employers who invest in upskilling, reskilling, and transparent workforce planning can turn automation into an opportunity — closing the skills gap while creating higher-quality, safer, and more fulfilling jobs for the next generation of manufacturing and warehousing talent.
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