• Amazon has a growing fleet of warehouse robots to enhance safety and efficiency.
• In an internal document, Amazon said these robots are critical to flattening its hiring curve.
• Amazon automation could save the company $10 billion annually by 2030, Morgan Stanley estimates.

When Amazon unveiled its Vulcan touch-sensing warehouse robot last week, it framed the technology as a way to make frontline jobs safer and easier.

What the company didn't mention is a broader ambition: using Vulcan and its expanding fleet of warehouse robots to reduce its need to hire a lot more humans.

An internal document obtained by Business Insider describes Amazon's long-term vision of automating many warehouse tasks. The document, dated late last year, said Vulcan and similar robots are "critical to flattening Amazon's hiring curve over the next ten years" as the company builds "the world's most advanced Fulfillment Network."

This suggests Amazon is trying to use automation to slow the rate of new hiring, rather than replace existing workers. People in senior positions at the company who are familiar with the matter say the automation push is also a response to growing costs and possible labor shortages in Amazon's warehouses.

The document, marked "Amazon Confidential," was produced by Amazon's retail team to review various important projects. It also outlined several AI initiatives designed to further optimize warehouse efficiency and employee productivity.

'Higher-value tasks'

The company still plans to "have a lot of people for a long period of time," an Amazon spokesperson told BI, adding that many future roles would involve "higher-value tasks."

"Our robotics solutions are designed to automate tasks in an effort to continue improving safety, reducing repetition, and freeing our employees up to deliver for customers in more skilled ways," the spokesperson said. "Since introducing robots within Amazon's operations, we've continued to hire hundreds of thousands of employees to work in our facilities and created many new job categories worldwide, including positions like flow control specialists, floor monitors, and reliability maintenance engineers."

The spokesperson also cautioned against drawing conclusions from a specific internal company document.

A leader in automation

Amazon has been a leader in warehouse automation for years, having acquired Kiva Systems in 2012 for roughly $775 million. The company has consistently streamlined its operations through technology, integrating more than 750,000 robots to work alongside over 1 million frontline employees in storing, picking, packing, and shipping goods.

For roughly a decade, Amazon's head count grew massively, even though it was embracing automation. But this has gone into reverse in recent years.

After doubling its workforce to 1.6 million between 2019 and 2021, Amazon's head count declined to 1.55 million last year.

Humans working alongside robots

Amazon introduced Vulcan last week as its first tactile robot. It's capable of sensing and adjusting the force needed to pick products from crowded bins and tall baskets, improving safety and speed.

According to the internal document obtained by BI, Amazon's robotics team is working on at least two AI models intended to be building blocks for new applications that "will significantly enhance the efficiency and responsiveness of our robotics systems." The company is also working on a new AI model called "Tetris," aimed at reducing variable labor and transportation costs, the document said.

In the document, Aaron Parness, the director of applied science at Amazon Robotics, emphasized robots' role in enhancing efficiency and safety to ultimately enable the company to fulfill more orders and deliver more shipments.

"We've always envisioned a solution that's robots and humans working side by side," Parness wrote. "And we think the sum of the two together is better than the parts alone."

He added that automation helps Amazon retain frontline employees in a competitive labor market by improving the work environment and offering new technical career paths in maintenance and operations.

"You have to be competitive for workers," Parness said, "so that people will want to work and stay at Amazon."

A potential solution for labor shortages

Some Amazon employees told BI that machines such as Vulcan are designed not only to enhance productivity but also to help address a growing labor gap.

One employee said the company had set aggressive targets to automate much of the warehouse workload over the next decade to drive down costs. Amazon is also extensively researching how to upskill the current workforce to move them into more maintenance-related jobs, this person added.

With Amazon's continued growth, finding enough workers has become increasingly difficult, another Amazon insider told BI. If the company doesn't automate more, it will struggle to keep up with demand, this person added.

A $10 billion opportunity

Vulcan is one of several systems Amazon has introduced in recent years, including robotic arms such as Robin and Sparrow that sort orders and mobile units like Proteus that transport packages across warehouses.

Amazon's automation strategy could save as much as $10 billion annually if 30% to 40% of US orders are fulfilled through next-generation facilities by 2030, Morgan Stanley estimates.

"We expect Amazon to continue to expand its warehouse network (to support growth) while also upgrading the footprint toward next-gen robotics in new builds and retrofits," Morgan Stanley analysts wrote in a research note earlier this year.

Amazon CEO Andy Jassy reaffirmed the company's commitment to automation during a February earnings call, saying its robotics investments aim to boost safety, productivity, and cost efficiency.

"We've already seen substantial value from our robotics innovations," Jassy said.

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• Predictive maintenance can help manufacturers save on costs by spotting equipment issues early.
• Companies like Aquant and Gecko Robotics provide AI-powered tools that inform maintenance decisions.
• This article is part of "How AI Is Changing Everything," a series on AI adoption across industries.

Equipment failures have long haunted manufacturers — and they come at a staggering price.

A 2024 Siemens report estimated that unplanned downtime costs the world's 500 biggest companies up to $1.4 trillion a year combined. Breakdowns in machinery can then affect consumers through product shortages, higher prices, and lower-quality goods.

Major companies like IBM and Amazon have long relied on a strategy known as predictive maintenance to try to keep their industrial operations running smoothly. Predictive maintenance tech combines hardware and software to monitor the health of industrial machinery and identify issues, such as overheating components or pressure leaks, before they escalate. Sensors collect performance data from equipment, and software then analyzes that data to pinpoint problems.

The need for the technology is expected to rise: Fortune Business Insights projects the global market for predictive maintenance to climb by 26.5% a year, reaching $70.73 billion by 2032.

This is where AI comes in. Advancements in AI, including generative AI and AI-powered robotics, could contribute to that growth. As AI capabilities evolve, manufacturers are integrating advanced algorithms into their maintenance systems, betting that smarter, faster predictions will improve business operations and savings.

That is, if growing pains don't get in the way.

AI and robots are enhancing predictive maintenance

Manufacturers' older systems that are designed to identify potential machinery breakdowns often overwhelm maintenance teams with false alarms, triggering unnecessary part replacements and wasted labor. Now, some startups such as Aquant are banking on AI to spot issues both faster and more accurately.

Aquant said its AI-powered algorithms can analyze past maintenance data to determine whether a maintenance action is necessary. For example, cross-referencing technicians' notes and industry benchmarks can help identify redundancies.

Its platform then analyzes machines' live sensor data — such as vibrations, sounds, and temperature shifts — alongside historical records from customer relationship management systems and other information repositories.

Proprietary algorithms sort through the information to "find the needle in the haystack" and diagnose issues that need addressing as well as the causes, said Assaf Melochna, Aquant's president and cofounder. The platform, which is also designed to filter out false positives, then recommends specific actions, such as shutting down the machine, to prevent failure, Melochna explained.

By focusing on factory machinery components that affect uptime, Aquant says its AI platform is helping clients such as Coca-Cola, HP, and Hologic cut downtime and avoid unnecessary repairs, saving up to 23% a year in service costs.

AI can also make inspections safer. Gecko Robotics builds wall-climbing robots, drones, and robot dogs equipped with ultrasonic sensors, high-resolution cameras, and light detection and ranging technology.

These robots are designed to inspect critical infrastructure like dams, power plants, and oil and gas facilities, collecting detailed data on pipes, tanks, vessels, and other industrial equipment. Gecko's AI platform, Cantilever, analyzes the data to detect corrosion, erosion, and cracking before failures occur.

The combination of the data obtained by the robots and the AI platform to analyze it helps give Gecko's clients, including Siemens Energy and the US Air Force, a real-time, predictive view of asset health, said Jake Loosararian, Gecko Robotics' cofounder and CEO, adding that this makes it easier to plan maintenance before problems escalate.

Generative AI is coming to maintenance

Some companies are layering conversational AI onto their maintenance tools.

Since 2006, Waites Sensor Technologies, a predictive maintenance firm, has installed more than 500,000 vibration and temperature sensors across Amazon, Tesla, DHL, and other facilities.

Rob Ratterman, the cofounder and CEO, told BI that Waites had more recently integrated large language models into its predictive systems to let technicians query their systems directly. Waites' LLMs are trained on machine manuals, repair history, and sensor data collected by the company's sensors.

Using devices like on-site computers, maintenance personnel can ask Waites' systems which machines are most likely to fail, what past repairs were needed, and what maintenance tasks should be prioritized. Technicians, for instance, can ask the chatbot questions like, "What are the most problematic pieces of equipment?" to identify issues, or "How do I relubricate a bearing?" to find instructions in a machine's manual.

By simplifying access to maintenance insights, LLMs can help teams make faster, data-driven decisions without needing to dig through complicated dashboards or reports, Ratterman explained.

With advancements in AI, predictive maintenance is now evolving into prescriptive maintenance, Kevin Tucker, an advisory practice lead at Info-Tech Research Group, told BI.

While predictive maintenance identifies a problem, prescriptive maintenance will tell you what to do to solve that particular issue. The more data predictive maintenance systems capture and analyze, the more accurate their predictions become, enhancing their abilities to make informed decisions.

"It's kind of like following your GPS in the car," Tucker said, underscoring the potential for prescriptive maintenance to act as a trusted guide.

Upfront costs and fears around AI can hinder adoption

While it has upsides, AI-driven predictive maintenance isn't easy to implement.

One major hurdle is cost. Installing smart sensors, integrating AI platforms, and upgrading legacy equipment requires major upfront investments, said Jorge Izquierdo, the VP of market development at The Association for Packaging and Processing Technologies, a trade organization.

Izquierdo called predictive systems the "lowest hanging fruit" for smart manufacturing in the packaging industry, but Tucker said incorporating new technologies into legacy systems might be hard to prioritize. After all, returns on investment aren't immediate, and system complexities — including data silos and the different softwares manufacturers use across the business — could make integration even harder.

"You're probably going to get your return on investment in a year and a half to two years out," Tucker said.

Loosararian emphasized that it's tough for companies, especially those running on tight budgets, to allocate resources toward implementing new technology on a large scale. "Innovation budgets run out pretty fast," he said.

Workforce skills gaps pose another roadblock. Predictive maintenance demands new expertise in data analysis and AI tools management — skills that many traditional maintenance teams don't have and may be resistant to learn.

That resistance is compounded by the concern that predictive maintenance systems, especially with advanced AI capabilities, may replace maintenance technicians' and inspectors' jobs. But some manufacturing leaders say the technology can support, not replace, maintenance personnel.

Craig Malloy, the CEO of Arix Technologies, a company behind robotic and AI systems that detect corrosion in industrial pipes, said its AI tools help free up time for maintenance personnel to focus on decision-making and long-term planning. "The goal is smarter, safer, more effective inspections — not fewer people," Malloy told BI.

Loosararian added that arming the workforce with AI tools can be one step toward addressing the growing labor shortage in US manufacturing.

Predictive maintenance leaders who spoke with BI agree that AI advancements are still in their early stages of transforming maintenance systems. But manufacturers willing to invest and stick through the growing pains could be the difference between thriving and falling behind.

As Malloy said: "AI has completely changed the game."

Most robots rely on complex control systems, AI-powered or otherwise, that govern their movement. These centralized electronic brains need time to react to changes in their environment and produce movements that are often awkwardly, well, robotic.

It doesn’t have to be that way. A team of Dutch scientists at the FOM Institute for Molecular and Atomic Physics (AMOLF) in Amsterdam built a new kind of robot that can run, go over obstacles, and even swim, all driven only by the flow of air. And it does all that with no brain at all.

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Sankaet Pathak is back—and this time, he’s building robots. Just months after the fintech firm Synapse collapsed under his leadership, Pathak is now behind a new startup called Foundation Robotics Labs. The company is reportedly trying to raise $100 million at […]

The post Former Synapse CEO resurfaces with new humanoid robotics startup aiming for $1B valuation first appeared on Tech Startups.

• Elon Musk may have become bored with the solved problem of manufacturing EVs.
• Musk's focus shifted from EVs to AI, robotics, and politics, leaving Tesla's core business untethered.
• A Tim Cook-style CEO could take Tesla operations to new heights, similar to Apple's post-Jobs success.

This "open letter" might be fake. It could be real. I don't know, but it reminded me of a column I've been wanting to write.

The letter is purportedly from disgruntled Tesla employees who want Elon Musk to stop being CEO so the company can go back to selling lots of electric vehicles. His DOGE bender has damaged Tesla's brand so much that he should step back, according to this alleged letter.

Even if this is a made-up missive, it raises an interesting question: Why would the CEO of the world's most valuable car company wander off for months to pursue political dalliances when the electric vehicle battle has just entered a new, crucial stage?

The answer may be simple: Elon is bored making cars.

He spent the last decade working his butt off to pull Tesla out of near bankruptcy and turn it into the dominant EV company of the Western world. There was a lot of innovation and many sleepless nights.

But now, one could argue, EV manufacturing is a solved problem. Tesla has gigafactories and other giant facilities around the world churning out hundreds of thousands of vehicles a year. The next stages are all about refining these processes and scaling efficient production — and, yes, persuading people to buy the products.

This isn't really Elon's jam. He likes to invent new things, not tweak existing products. This story from The Information put it well when it described why Musk rejected his lieutenants' advice to pursue a cheaper EV, and instead went all-in on artificial intelligence, autonomous vehicles, and robots.

This quote, from a person familiar with the situation, stands out: "I think Elon is just uninterested in making a [Volkswagen] Golf-type car. It just doesn't wake him up in the morning. He was, 'Let somebody else do it.'"

What type of new CEO would Tesla need?

So, who else would do this at Tesla, and what would this mean for the future of the company?

If Musk were to relinquish the CEO role, I think he'd need a Tim Cook-style executive to take the reins.

Cook is a supply chain genius who took over Apple when Steve Jobs died in 2011. At that time, I was a tech reporter at Reuters, and many experts were predicting doom for Apple.

Like Musk, Jobs was a mercurial tech founder who was loved for his visionary inventions and feared for his brutal approach to people management. (Jobs also pulled Apple back from near bankruptcy.)

In 2011, investors just couldn't imagine how Apple might continue to thrive without this creative driving force.

In one way, they were right to worry. Since then, Apple has not launched many truly new and inventive products. The car project failed. The Vision Pro goggles have stumbled out of the gate (and followed Meta's Oculus anyway).

In another way, though, Cook has taken Apple to new heights that were unimaginable 14 years ago. And he did it by taking another solved problem — smartphones — and perfecting it over and over and over again.

Since 2011, Cook has obsessed over minute iPhone product tweaks, redesigned the chips in-house, switched out and negotiated (hard!) with hundreds of suppliers, and carefully evolved one of the world's largest supply chains in the face of pandemics and dictators.

I asked Apple for comment on Monday and didn't get a response. I also emailed Elon and asked him if he wants to spend the next 10-plus years of his life tweaking Tesla's EV operations. I didn't get a reply, not even a poop emoji.

Apple's now a $3 trillion company

The value Cook has added since 2011 is astounding. Late that year, the company was worth about $350 billion. Apple is now valued at $3.2 trillion.

By iterating intensely on an existing product — grinding costs lower and efficiency higher — this CEO has generated almost $3 trillion in shareholder value, and made Apple the most valuable company in the world.

When Apple became the first company to pass $1 trillion in 2018, I edited a story by Mark Gurman that marked this moment. The piece quoted Tony Fadell, who helped Steve Jobs create the iPod. Instead of harping on about Jobs's legacy, Fadell focused mostly on Cook.

"Tim and team have done a masterful job of continuing to develop Steve's vision while bringing operational and environmental excellence to every part of Apple's business to achieve their unheard-of scale while continuing to grow unprecedented margins in the consumer electronics business," Fadell said.

Tesla's '2011 Apple' moment

I think Tesla could be at a "2011 Apple" moment right now.

Musk hasn't died, but his passion for EV manufacturing may have faded.

Like Apple back then, many Tesla investors can't image the company without Musk as CEO. But he could, in theory, step back from day-to-day leadership duties while continuing to work on newer, cutting-edge projects in the background, such as the Optimus robot.

Meanwhile, a Cook-style executive could take the CEO role and start hammering away at the solved problem of Tesla's core EV business. This could also reduce the brand damage done by Musk's political foray.

Apple shows what's possible in a scenario like this: Almost $3 trillion in market value created from basically doing an existing thing better and better.  

I asked Grace Kay, Business Insider's hot-shot Tesla reporter, who might be a good candidate to replace Musk as CEO. She suggested Omead Afshar, a low-profile, mild-mannered executive who once ran a major Tesla manufacturing operation and has become a trusted confidant of the visionary founder.

Sound familiar?

If you want to know more about Omead Afshar, check out Grace's amazing profile. 

Neuralink, the brain implant startup founded by Elon Musk, is planning to raise around $500 million in fresh funding at a pre-money valuation of $8.5 billion, Bloomberg reported, citing people familiar with the deal. The round, still in its early […]

The post Musk’s brain implant startup Neuralink eyes $500M raise at $8.5B valuation for brain-computer interface expansion first appeared on Tech Startups.

• Robots that look and move like humans are getting a lot of buzz.
• Companies, including Amazon and GXO, are already testing humanoid robots in their warehouses.
• But humanoids are expensive and complex, and the tech used to power them is still nascent.

Tech companies and investors are pouring billions of dollars into a future in which human-like robots work alongside people in warehouses, hospitals, restaurants, and homes. The goal is that humanoid robots that can carry objects and walk on two feet could help to fill labor shortages across industries and take on tasks that might be harmful to humans.

While the idea of having a robot do chores around the house might sound appealing, humanoids most often start their "careers" in warehouses and manufacturing facilities.

That's because humanoids — and robots in general — tend to work best in structured environments, CB Insights' senior lead analyst Benjamin Lawrence told Business Insider.

"A lot of factories and warehouses are very similar, so you can set up replicating tasks much more easily," he said.

"When you think of a home, for example, you need to make sure that the humanoid is safe with grandma, with the kids, with the pets, that it doesn't step on the dog's tail. You need to make sure that the humanoid is aware that there's a candle burning on that table and doesn't accidentally knock it over and cause a house fire."

Some experts are skeptical about a future filled with humanoid robots. They're expensive and complex to manufacture, and outside a handful of highly publicized tests, they're still largely unproven.

But investor interest is taking off, with companies making humanoid robots raising a collective $1.2 billion in venture funding in 2024, according to CB Insights. The sector is on track to more than double funding to $3 billion this year. Agility Robotics is raising $400 million at a $1.75 billion valuation, The Information reported earlier this month. Apptronik, which makes the Apollo humanoid robot, announced a $350 million Series A funding round in February.

Big Tech companies are also betting big on humanoids — some by supplying their foundational models to robotics manufacturers, like Google DeepMind is doing with Apptronik, and others by making both the models and the hardware themselves, like Tesla is with its Optimus robot. Big Tech views humanoids as the natural next step in AI, as the industry's interest has gone from generative AI to agentic AI and then on to physical AI. Advances in natural language processing have also made training robots simpler.

"The ChatGPT moment for general robotics is just around the corner," Nvidia CEO Jensen Huang said during his keynote speech at CES in January.

'We're not 10 years away, that's for sure'

Many of the early users of humanoids are auto manufacturers. There's already quite a bit of automation in car plants, so moving on to humanoids is a natural progression, Lawrence said.

Ford was Agility's first customer, buying the first two Digit robots in 2020. The two companies had previously partnered on a last-mile delivery project. Elon Musk has said Tesla will have "genuinely useful humanoid robots in low production for Tesla internal use" this year and available to other companies at a price tag of $20,000 to $30,000 in 2026. BMW piloted humanoid robots made by Figure, using them to insert sheet metal parts into a car's chassis. And, Hyundai acquired Boston Dynamics, a leader in humanoid robotics, from Softbank for $1.1 billion in 2021.

Retailers are also testing humanoids in their warehouses. Amazon is testing Digit, the humanoid robot made by Agility, in addition to the robots it manufactures in-house. Logistics giant GXO is also testing Digit and humanoids from Apptronik and Reflex Robotics.

"We are going really broad and aggressive on the category," Adrian Stoch, GXO's chief automation officer Adrian Stoch told BI in a recent interview. "It's because of where we see this going."

Just how close humanoid coworkers are to becoming a reality in warehouses is still uncertain.

There are a few roadblocks. The first is price, with a single humanoid robot costing several tens of thousands of dollars (though several manufacturers in China, including Unitree, have recently revealed models at a significantly lower price point).

The second potential roadblock is the technology itself.

"You need to have humanoids that are highly adaptable to every different warehouse, to a range of language commands, and to be able to infer those commands and work within the existing structure," Lawrence said. "It's just very difficult to do that."

The current tests are relatively small. For example, GXO has more than 1,000 warehouses and employs more than 150,000 people, yet it has just two Digit units moving heavy boxes to a conveyor belt in one facility.

"We're not at wide-scale deployment and commercial viability yet, but we're not 10 years away, that's for sure," Stoch said.

When is the human form right for the job?

There's also the question of whether robots that can walk on two feet and manipulate objects with two hands are ideal for completing tasks.

Robotic arms that can pick up and place items are now common in warehouses. There are also automated guided vehicles, or AGVs, that transport items around warehouses using predefined routes on a line or wire, and autonomous mobile robots, or AMRs, that can get around on their own. Boston Dynamics has also made a robotic dog that can do things like read meters and detect leaks.

"There are very few use cases where the best robotic form is something that looks like you," Forrester analyst Paul Miller said.

He added that the work a human does could likely best be replicated with a combination of technologies, not just a robot that happens to have a similar look to a human.

"A human worker in their job does a lot of different tasks. Some of those tasks are best performed by a human being. Some tasks are best performed by software," Miller said. "Some of those tasks are best performed by a physical automation, some kind of robot."

"It's about working out how you break those tasks up."

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Several years ago, Harvard University roboticist Robert Wood made headlines when his lab constructed RoboBee, a tiny robot capable of partially untethered flight. Over the years, RoboBee has learned to fly, dive, and hover. The latest improvement: RoboBee has learned how to stick the landing, thanks to biomechanical improvements to its landing gear modeled on the crane fly, which has a similar wingspan and body size to the RoboBee platform. The details of this achievement appear in a new paper published in the journal Science Robotics.

As previously reported, the ultimate goal of the RoboBee initiative is to build a swarm of tiny interconnected robots capable of sustained, untethered flight—a significant technological challenge, given the insect-sized scale, which changes the various forces at play. In 2019, Wood's group announced its achievement of the lightest insect-scale robot so far to have achieved sustained, untethered flight—an improved version called the RoboBee X-Wing. In 2021, Wood's group turned its attention to the biomechanics of the mantis shrimp's knock-out punch and built a tiny robot to mimic that movement.

But RoboBee was not forgotten, with the team focusing this time around on achieving more robust landings. “Previously, if we were to go in for a landing, we’d turn off the vehicle a little bit above the ground and just drop it, and pray that it will land upright and safely,” said co-author Christian Chan, one of Wood's graduate students. The trick is to minimize velocity when approaching a surface and then quickly dissipating impact energy. Even something as small and light as RoboBee can generate significant impact energy. The crane fly has long, jointed appendages that enable them to dampen their landings, so the insect served as a useful model for RoboBee's new landing gear.

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• Trump's trade war has increased demand for robotics and automation.
• Robots-as-a-service company Formic said its customers have stepped up their use of robots this year.
• Automation can help companies to save money amid uncertainty.

Automation company Formic said that its customers stepped up their robot usage this year as tariff announcements sent global supply chains into chaos.

Formic automates packing and palletizing — or placing packages on a pallet — for automotive, industrial, food, beverage, and consumer packaged goods companies. It operates on a "robots-as-a-service" model, meaning that customers lease Formic's robots and pay a monthly rate based on how much they use them. Its robots are deployed in more than 100 factories in the US and have stacked and packed more than 1.2 billion products.

Between January and February, Formic's customers increased their robot usage by more than 17% overall, Chief Marketing Officer Shawn Fitzgerald told Business Insider. Its food and beverage customers stepped up their usage by more than 13%. He said the usage numbers seemed particularly notable given that February has fewer business days than the other months of the year.

It's likely that brands were using robots to get ahead of any tariff-related price increases.

President Donald Trump made his first in a series of tariff announcements on February 1, placing tariffs on goods from China, Canada, and Mexico, and closing the de minimis tax loophole.

"This data suggests everyone sat down with each other and said, let's step on the gas as much as we can in February, and let's make as much as we possibly can at the price points we are at right now," Fitzgerald said.

Formic customers' robot usage dipped in March, but the numbers are showing signs of a rebound so far in April, the company said. This month has seen the return of global trade chaos as Trump announced a large set of tariffs on April 2 — which he called "Liberation Day" — then later paused those tariffs except for those on goods from China.

Fitzgerald said that working with Formic helps companies to get more predictability in their costs amid uncertainty.

"If you do unfortunately have to go to overtime, robots love first, second, and third shift and overtime all the same. They do not care," he said.

Using automation to 'fill in some of the gaps'

Formic's customers include Rumiano Cheese Company, a cheese-making and packaging company based in Willows, a small town in the Sacramento Valley of California. Automation is top of mind for the 106-year-old company — even more so as tariffs have posed a threat to their profits this year. Rumiano imports cheeses from Italy and exports products to Mexico, China, and the Dominican Republic through a third party.

Rumiano is installing a Formic robot that can pick up 30-pound boxes of cheese and move them from the production line to pallets to be shipped out to customers. But Formic's robots are just one of several automation solutions Rumiano has explored. It also uses a machine that puts stacks of cheese in the proper place so they can be packaged.

"We've had more AI and robotics conversations in the last two months than we've probably had in the year prior," said Patrick Henson, the vice president of operations at Rumiano.

Employees who previously stacked cheese by hand have been reassigned to other tasks in the facility.

Working with robotics and data partners is key for the small, family-owned company.

"We don't have teams of data scientists or anything like that," David Wolper, director of planning at Rumiano, said. "We are looking to partners to help us grow with AI tools to help us really dig into data so that we can make sure we're spending money on the right things, we're producing the right products, we're doing everything as efficiently as we can to help save costs."

Tariffs have created obvious challenges for brands, but supply chain optimization has been a hot topic for several years. It's an area where robots and software can help, Forrester analyst Paul Miller told BI.

"Since Covid there has been this broad idea about shortening supply chains, improving resilience, improving adaptability, and part of that is bringing manufacturing capacity closer to the customer," Miller said. "If you're trying to bring that manufacturing capacity to California or Germany or Japan, the people are not cheap. You need to use automation to fill in some of the gaps."

Commerce Secretary Howard Lutnick alluded to this idea in several TV appearances he made after Trump announced his tariff plans in April.

On CNBC, he said US factories are "going to see the greatest surge in training for what we call tradecraft — teaching people how to be robotics, mechanics, engineers and electricians for high tech factories."

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