Early factory robots were not “intelligent” by today’s standards—they were fixed, repetitive, and often operated in cages—yet they enabled dramatic gains in output per worker.
The proliferation of AI now means these factory robots can become far more productive. With better vision systems and adaptive decision-making, machines are now able to adjust to variation, handle more tasks, and work safely alongside people.
Beyond the factory floor
Factories are where workers have historically experienced the most displacement from automation. Today, other sectors are beginning to experience the same technology curve—only faster.
Logistics and warehousing are leading the way. Amazon (AMZN) now operates more than 750,000 mobile robots across its fulfillment network, nearly triple the pre-pandemic level.
Recently leaked documents suggest AMZN, which is the second largest private employer in the U.S. behind Walmart (WMT), aspires to grow its e-commerce revenue significantly in the years ahead without growing its labor force. The main driver of this opportunity is the deployment of robots in its facilities.
Traditional retail is following the same trajectory. WMT uses autonomous inventory-scanning robots in hundreds of stores, and grocery chains are deploying robotic systems for restocking, aisle inspection, and micro-fulfillment centers that pick and pack online orders.
Transportation is becoming increasingly robotic as well. A self-driving car is effectively a robot on wheels. Ports, airports, and logistics hubs are already running fleets of autonomous machines.
Healthcare is emerging as another growth segment for robotics. Hospitals use autonomous robots to transport supplies, sterilize rooms with ultra-violet systems, and assist in surgical procedures.
Robots are being used in hospitality. Restaurants are adopting robotic fryers, dish-handling systems, and automated prep stations. Hotels and airports increasingly use service robots for cleaning, luggage handling, and guest support.
Even construction—naturally considered one of the hardest industries to automate—is beginning its transition. Robotics companies are rolling out autonomous layout systems, material movers, and robotic bricklayers that can operate continuously.
The pattern across all these sectors is the same: where the work is repetitive, physically demanding, or requires consistent precision, robots are gaining ground. And functions that were previously too complex for robots are becoming achievable.
As AI continues to improve and the cost of deploying robots inevitably declines, the range of complex tasks that robots can handle will widen rapidly—potentially with no real upper limit.
Robot personal assistants?
Elon predicts billions of humanoids in the future. It sounds crazy, but take into account that there are currently around 1.5 billion automobiles on the planet.
Elon has suggested that his Optimus robot could cost $20,000 to $30,000 per unit at full commercial production. This compares favorably to the average cost of a new car in the United States, which is approximately $50,000.
Automobiles also involve significant additional costs, such as insurance and fuel. AAA estimates the annual cost of owning a new car at approximately $12,000.
A start-up venture called 1x (which is backed on OpenAI, the creator of ChatGPT) is accepting refundable $200 deposits on “NEO the home robot.” The company intends to make NEO available for $500 per month or a one-time $20,000 payment.
Many families pay several hundred dollars per month for access to television programming, broadband, and wireless telephone service. They also pay much more than that for domestic help.
A legitimate economic case can be made for even a middle class household to purchase or lease a humanoid robot if it truly delivers a valuable service.
It may take decades to get to billions of humanoid robots, but as their capabilities advance and prices come down, household robots could conceivably become as ubiquitous as washing machines, flat screen televisions and cell phones.
Self-driving cars themselves might free up funds within the family budget to invest in humanoid robots by making car ownership a thing of the past.
Perhaps in the not so distant future, if you need to get somewhere, you will just inform your humanoid robot, who will then summon you a ride. No need to own your own car.
How to play it?
Robots in all their various form factors will proliferate. AI is dramatically expanding their capabilities and making them far more cost-effective to deploy.
Investors should view robotics as a durable long-term growth trend and should seek exposure to businesses that align with it.
The opportunity is not just in companies that will make robots. Below, we examine several stocks across sectors that capture different angles of the emerging opportunity in AI-powered robotics.
Is Tesla (TSLA) a buy?
TSLA is a stock that is not held within any of our Model Portfolios, although we are often asked about it.
TSLA is an extraordinary company that is at the forefront of robotics in the form of autonomous vehicles, its primary business today, and likely humanoid robots in the future.
The main reason TSLA is not in the American Resilience Model Portfolio, where it could conceivably fit, is its risk profile. TSLA has an extreme valuation as well as a high degree of key man risk in its reliance on Elon Musk.
TSLA is a Magnificent Seven stock and a top ten position within the S&P 500 Index, representing an approximately 2% allocation. Investors in the index, or other growth indexes like the Nasdaq-100, where TSLA represents an approximately 3.5% allocation, may already have material exposure to the stock.
TSLA is different from other Mag Seven names, however, because so much of its valuation rests on extremely ambitious growth expectations.
Reasonable arguments can be made as to why TSLA’s valuation metrics actually make sense. A high multiple is not inherently irrational or inappropriate.
But the stock still trades at approximately 180 times its 2026 consensus earnings forecast, versus approximately 21 times for the S&P 500.
From a valuation perspective, TSLA is also an extreme outlier versus its Mag Seven peers. Stocks like NVDA, Microsoft (MSFT) and Apple (AAPL) now trade at 40 times, 32 times and 32 times next year’s earnings estimates.
Even at such a stratospheric multiple of forward earnings, TSLA could be cheap.
The massive long-term growth in profits that is already priced into the stock could materialize if TSLA’s margin structure improves significantly as the autonomous vehicle business matures.
Additionally, TSLA’s various “call options” on other business segments, from robots to energy storage, could eventually blossom into highly profitable businesses.
It would not surprise us if TSLA did indeed become the leading manufacturer of robots in the world—a process that would play out over many years and decades.
But, for now, it is a very richly valued stock with many speculative elements. This is the sort of opportunity that investors need to assess individually, based in no small part on their confidence in Elon Musk.
Investing in the data center ecosystem
Robots represent the physical deployment of AI intelligence that is trained and powered within data centers. Therefore, investments in the different layers of AI infrastructure are indirect investments in robotics.
Robots are an important element of the AI theme, one that overtime will only become more relevant.
While AI stocks in general have recently come under some pressure, we continue to view many of them as core long-term positions in the context of an economic transformation that is still quite young.
NVDA as mentioned is the leading supplier of GPUs and, more generally, AI data center hardware and software that underpin the current rapid growth in robotics.
While its broader activities in AI dominate the investment case, NVDA aims to be the core compute and AI platform enabling the next wave of intelligent robotics.
NVDA is building a full-stack robotics platform that spans chips, software, simulation, and AI models. Its Isaac ecosystem lets developers train robots in virtual worlds and transfer those skills to real hardware.
NVDA is also developing robot foundation models like Isaac GR00T, giving robots human-like perception, reasoning, and task planning. Its Jetson edge chips power robots in factories, warehouses, hospitals, and service applications.
Following a surge after the company’s disclosure of tremendous growth in future orders last quarter, Oracle (ORCL) shares have retreated on fears around an AI bubble. This stock in particular deserves a close look in the current environment with investors shying away from AI-buildout names.
With regard to robotics specifically, ORCL plays an increasingly important infrastructure role as robots become cloud-connected, data-intensive systems. ORCL provides the backend that robotics firms use: high-reliability databases, cloud compute, AI services, and real-time data pipelines.
Similarly, Digital Realty (DLR) enables robotics by supplying the data-center infrastructure robots depend on. As robots produce huge video and sensor streams, DLR’s global campuses host the GPU clusters, storage, and low-latency networks required for AI training, simulation, and fleet coordination.
Logistics as a robotics play
Prologis (PLD) is the world’s leading owner of modern, high-throughput logistics facilities that increasingly function as the physical backbone for automated, AI-driven supply chains.
The company actually now benefits from growth in robotics in two ways.
PLD is a major beneficiary of the robotics boom because warehouse automation requires modern, power-dense, high-clearance logistics facilities—PLD’s core specialty.
As its customers (like AMZN) deploy autonomous mobile robots, AI-driven fulfillment systems, and automated storage, they increasingly need buildings that are optimized for electrification, fiber connectivity, and heavy equipment loads.
PLD is also pursuing select conversions of logistics assets into data center infrastructure. Modern data centers require large parcels close to cities, access to utility-scale power, and dense fiber connectivity—the exact locations where PLD has spent decades assembling and entitling logistics land.
PLD is early in this opportunity to convert warehouses and vacant land into “higher and better use” data centers, but investors are increasingly focused on it. The potential value creation from this additional growth driver, which was largely ignored twelve months ago, could already be as much as 10% to 15% of the current share price.
No robots without analog chips
One of the most interesting long-term plays on the robotics theme at the moment, especially for valuation-sensitive investors, is Texas Instruments (TXN), the world’s leading analog semiconductor company.
Robotics is ultimately about connecting two worlds: the continuous, physical environment we live in and the digital intelligence now emerging inside data centers. Analog semiconductors are the bridge between those worlds.
This is where TXN shines. As the world’s leading analog chipmaker, TXN produces the power-management systems, sensors, motor drivers, and signal-processing components that allow robots to perceive their surroundings, manage energy, and move with precision.
As automation spreads across logistics, manufacturing, and service industries, demand for reliable, industrial-grade analog components grows steadily. That makes TXN an underappreciated but highly durable way to invest in the physical expansion of AI-driven robotics.
TXN has in recent months significantly lagged other tech stocks. The business is contending with softness in industrial demand, especially in China, that remains a drag on near-term revenue and margins.
The company is also in the middle of a multiyear capacity expansion cycle, which is pressuring free cash flow until scheduled investments wind down as they will in the years ahead.
But these headwinds are cyclical, not structural. The long-term structural opportunity for TXN is in industrial automation and robotics, including self-driving vehicles.
