Robotics and advanced manufacturing is one of those sectors that gets described in the future tense so often that it can be easy to miss when the present tense actually arrives. For years, the story was about what automation would do once it was affordable, reliable, and intelligent enough. That conversation has quietly shifted. For investors evaluating industrial automation investment in 2026, the companies doing the building, the enabling, and the deploying are no longer hedging.
For this piece, we pulled recent calls and conference presentations from five companies that together give you a cross-section of the entire supply chain: NVIDIA, whose physical AI platform is now explicitly designed for robotics at industrial scale; Cognex, the world leader in machine vision with sensors in nearly every automated production line on earth; Rockwell Automation, whose $8 billion industrial automation business functions as a real-time read on manufacturing capex appetite globally; Teradyne, which owns Universal Robots and tests the semiconductors that power AI systems; and Intuitive Surgical, the surgical robotics company whose thirty-year installed base and AI roadmap show what a mature robotics platform looks like when the flywheel is fully spinning.
The picture that emerges is not a forecast. It is a dispatch from a sector in the middle of something.
NVIDIA is the enabling layer for all of it. Jensen Huang’s GTC keynote in March was the most explicit framing yet of the physical AI thesis: the atom-related industries requiring robots, autonomous vehicles, and intelligent machines represent $50 to $70 trillion of the world’s economy, he said, dwarfing the digital AI opportunity. Huang stated at GTC that NVIDIA has three computers purpose-built for robotics — covering training, simulation, and the compute that runs inside the robot itself — and that 110 robots were on the show floor, with partnerships spanning ABB, Universal Robots, KUKA, and nearly every major robotics company. NVIDIA is the company that sets the macro thesis and contextualizes everything else.
Cognex sits at the factory floor level, where machine vision systems guide every robotic arm, inspect every part, and read every barcode in advanced manufacturing. The CEO’s Raymond James presentation in March contained something that had not been true for several years: every one of Cognex’s five end markets is returning to growth simultaneously. Their presentations are unusually candid about where automation is actually happening versus where it is being discussed.
Rockwell Automation is the bellwether for industrial capex. At $8 billion in revenue and present across nearly every major manufacturing vertical, their order book is as close to a leading indicator as this sector has. The BofA Global Industrials Conference in March gave us the clearest read on where manufacturers are actually committing capital versus where they are still waiting for trade and geopolitical stability to commit.
Teradyne owns Universal Robots, the collaborative robot (cobot) market leader, and also tests the AI chips that power everything from NVIDIA’s GPUs to the semiconductors inside robotic systems. Their Cantor Fitzgerald presentation in March carried a signal that is easy to miss in the AI coverage: the company that tests the chips running the robots is also at the dawn of a cyclical recovery in industrial and automotive — a grounded counterweight to the more expansive AI framing.
Intuitive Surgical is the proof of concept. Their Q1 2026 earnings call showed 17% procedure growth, a platform with nearly 1,500 da Vinci 5 systems in the field, and a CEO describing an AI roadmap that moves explicitly from data to insights to augmented dexterity to aspects of automation. They are thirty years into building what a mature robotics platform looks like. The rest of the sector is watching.
The most important signal across these five transcripts is not a number. It is a change in how management teams are framing the relationship between artificial intelligence and the physical world.
The language is now architectural. Companies are not describing what robots will do. They are describing the systems they are building right now to make it possible.
Jensen Huang’s GTC keynote was the clearest articulation of this. The progression he described — from generative AI to reasoning AI to agentic AI — terminates not in a smarter chatbot but in a physically embodied agent. His framing: digital agents became physical agents, which are robots. The NVIDIA infrastructure — the training computers, the simulation environments, the onboard robotics compute — is not a product roadmap slide. It is infrastructure that ABB, Universal Robots, KUKA, and dozens of other companies are actively building against today.
Intuitive Surgical’s CEO described the same arc from the other end. Dave Rosa laid out the AI roadmap as a layered progression: high-quality data from surgeries, insights derived from that data, delivery of those insights in consumable form to the surgeon, then augmented dexterity, and ultimately aspects of automation. The phrase “aspects of future automation” appeared in prepared remarks, not analyst Q&A. That is threshold language from a company that has been building toward this for thirty years.
These two companies — one building the enabling infrastructure, one operating the most mature robotics platform in any industry — are using the same architectural framing from opposite ends of the supply chain. That kind of convergence tends to precede inflection.
Cognex CEO Matt Moschner said something at the Raymond James 47th Annual Institutional Investors Conference in early March that is worth sitting with: for the first time in many years, every one of their five end markets is returning to growth simultaneously. Logistics, automotive, electronics, packaging, and semiconductor — all of them.
That matters because Cognex is not a company that tells you what customers intend to do. They tell you what customers are actually buying. Their systems go into factories when automation projects are funded and installed, not when they are announced. A broad-based recovery across all five verticals at the same time is a different signal than one sector recovering while others lag.
The customer acquisition data reinforces this. Cognex added 9,000 new customers in 2025, up from 3,000 in 2024. That is a 3x acceleration in the rate at which new manufacturers are adopting machine vision — which is to say, the rate at which the next layer of industrial automation is being deployed. Moschner attributed this to the sales force transformation and to products that are genuinely easier to deploy, but the signal is directional regardless of attribution.
The supply chain geography angle is underreported in most automation coverage. Moschner described customers choosing Cognex specifically because they need a vendor with global presence as they shift manufacturing locations — Asian manufacturers moving to South America, U.S. producers moving to Europe. Cognex’s global service and support footprint is being cited as a competitive differentiator for companies navigating reshoring and friendshoring. The industrial automation investment is following the manufacturing footprint shift, not leading it.
The AI transition in machine vision is also crossing a threshold. Cognex launched four AI-first products in 2025, including OneVision, described as the first cloud training service for industrial AI models in the industry. The CEO framed AI not as a feature add-on but as an existential imperative — the company’s survival as the technology leader depends on being the leader in AI for industrial machine vision. That framing, from a 45-year-old company with historically dominant market share, is its own signal.
Rockwell’s BofA Global Industrials Conference presentation in March is the most useful corrective to the physical AI narrative. Rockwell CFO Christian Rothe described a company that had a genuinely strong Q1 — double-digit top-line growth against a full-year guide midpoint of 4% — but was explicit that broad-based capital spending has not yet recovered.
Investor Relations head Aijana Zellner put it directly: customers need more stability on the trade front and the geopolitical front before they commit to large capital outlays. The orders are real, the greenfield wins are real, the brownfield productivity investments are real. But the broad-based capex cycle that would confirm a full recovery has not arrived.
The most strategically interesting signal from Rockwell is what they are doing with their own factories. The company — whose entire business is selling automation to manufacturers — is now automating itself. They piloted autonomous operations in Singapore, scaled it to their Twinsburg, Ohio facility, and announced a purpose-built 1 million square foot greenfield facility in New Berlin, Wisconsin designed explicitly for autonomous operations, not just automation. The CFO said the goal is autonomy. That is a company eating its own cooking in a way that is also a proof of concept for every customer conversation they have.
The labor shortage framing is consistent across the transcript and is described as structural rather than cyclical. Customers do not have the in-house talent to maintain and optimize their industrial automation investments. That is driving Rockwell’s services business and is the demand tailwind that persists regardless of the broader capex cycle.
The EV handoff is worth noting. The electric vehicle battery buildout stalled, but the automation spend redirected rather than disappearing — into battery energy storage systems and integrated energy management. The demand followed the energy transition, just not via the route that was anticipated. Rockwell’s e-commerce and warehouse automation segment was up 60% in Q1, partially driven by data center control systems appearing as a new line inside that business. The intersection of AI infrastructure buildout and industrial automation is showing up in Rockwell’s results before most people are tracking it.
Teradyne’s Cantor Fitzgerald presentation in March contained a sentence that is easy to miss in the context of a semiconductor equipment discussion: CEO Greg Smith described industrial and automotive as being at the dawn of a cyclical recovery. Inventory levels are down. Companies are talking more optimistically. A modest recovery is expected.
That matters in this context because Teradyne also owns Universal Robots, the cobot market leader, and is therefore directly exposed to the industrial automation investment demand that Cognex and Rockwell are describing from their respective vantage points. A cyclical recovery in industrial and automotive semiconductor testing is a leading indicator for the same recovery in cobot deployment — the factories that build the chips also buy the robots.
The AI compute testing story is the other thread. Smith described a structural dynamic that is easy to underappreciate: as AI accelerators move to the most advanced semiconductor process nodes, yields drop, die counts per package multiply, and test coverage requirements go up dramatically. The result is that you need far more test capacity to produce the same number of good chips. His framing: if you need to test four parts to get one good part, you need an enormous amount of wafer sort capacity. That is a direct read on how the AI infrastructure buildout creates demand up the entire semiconductor supply chain, and by extension, up the robotics supply chain.
The co-packaged optics transition is a signal worth tracking for the next cycle. Smith described CPO as reaching the beginning of commercial scale deployment by end of 2026, with geometric growth from there. He was explicit that this is a test market still in its infancy — laboratory-grade instrumentation rather than production-grade — and that the TAM will evolve as the technology matures. Teradyne acquired Quantifi specifically to build the production-oriented optical test equipment that will be required.
Intuitive Surgical’s Q1 2026 earnings call showed 17% total procedure growth. Da Vinci 5 utilization is running approximately 11% higher than its predecessor. Revenue grew 23% against 17% procedure growth, a dynamic the CFO described as innovation-led revenue performance — meaning the platform is generating more revenue per procedure because the new system is genuinely more valuable.
The tariff signal is present but modest: 100 basis points of gross margin impact in the full-year guide, with higher freight and semiconductor memory costs identified as growing headwinds. The company absorbed these in Q1 without a guidance reduction and raised its procedure growth forecast for the full year.
The AI roadmap described by CEO Dave Rosa is the most detailed public articulation of what AI-augmented robotics actually looks like in deployment. The progression starts with data — surgical video, kinematic data, force feedback data, connected electronic medical records. That data becomes insights. Those insights are delivered to the surgeon in the operating room, starting with anatomy identification and tissue plane visualization. Over time, those foundations support augmented dexterity. Eventually, aspects of automation.
Rosa described the installed base of da Vinci 5 systems — now nearly 1,500 systems, used by almost 13,000 surgeons — as the foundation that strengthens differentiation over the next three to five years. The flywheel: more procedures generate more data, more data enables better AI models, better AI models drive higher utilization, higher utilization drives more system placements. The AI layer is now being explicitly built on top of a platform that has been compounding for thirty years.
The China and Japan dynamics are a useful read for the broader robotics sector. China shows what happens when domestic competition, policy-driven pricing pressure, and reimbursement uncertainty combine: procedure growth below the corporate average, low tender activity, no clarity on reimbursement policy until 2027. Japan shows what happens when reimbursement policy moves in the other direction: seven new procedures granted robotic reimbursement starting June 2026, incremental financial support for high-volume robotic programs. Policy is a larger variable in robotics adoption than most coverage acknowledges.
Labor scarcity is the durable demand driver. Every one of these five companies cited it in some form. Cognex’s customers are automating because they have quality and throughput problems that cannot be solved by hiring. Rockwell’s customers lack the skilled labor to maintain and optimize what they have already installed. Intuitive Surgical’s after-hours procedure growth — up 31% year-over-year for appendectomy and cholecystectomy — is partly a story about hospitals using robotics to extend the productivity of surgical teams across more hours. Teradyne’s cobot business exists because small and mid-sized manufacturers cannot hire at the scale they need. The framing that automation is a response to labor cost is incomplete. It is more accurately a response to labor unavailability.
Tariff exposure is present but not yet in guidance. Intuitive Surgical quantified it at 100 basis points of gross margin impact. Rockwell is passing tariff-related costs through a price increase in April. Teradyne’s semiconductor customers are dealing with it at the materials level. None of these companies issued guidance revisions driven by tariffs in this cycle. The language is quantifying and monitoring rather than revising. Watch for Q2 to be the first cycle where that changes if policy firms up.
The supply chain geography shift is creating automation demand. Cognex is being chosen specifically because manufacturers moving production between geographies need a vendor with global presence. Rockwell is seeing greenfield wins as companies build new facilities in North America, which it describes as its fastest-growing market in 2026. The reshoring and friendshoring cycle is now showing up as actual orders in industrial automation investment results. The factories being built to reduce geopolitical supply chain risk are being built with automation from the start.
“We are completely resetting and starting the largest build-out of human history. And most of the world’s industries — building AI factories, building chip plants, building computer plants — are represented here today. Robotics: $50 trillion industry in manufacturing.”— Jensen Huang, NVIDIA CEO · GTC Keynote · March 16, 2026
Intelligence sourced from public earnings calls and investor conference presentations. All market sizing figures are direct management statements. Not investment advice.
AI refers to artificial intelligence embedded in robots, autonomous vehicles, and intelligent machines — as opposed to software-only applications. Jensen Huang’s GTC keynote framed the atom-related industries requiring physical AI as a $50 to $70 trillion opportunity, dwarfing the digital AI market. For manufacturing investors, this signals that the infrastructure buildout phase — sensors, compute, simulation environments — is already underway.
Cognex’s data offers the clearest answer: all five of their end markets are returning to growth simultaneously for the first time in years, and new customer additions accelerated from 3,000 in 2024 to 9,000 in 2025. Rockwell Automation confirms the recovery is real but notes that broad-based capital commitment has not yet arrived — customers are waiting for trade and geopolitical stability before committing to large outlays.
Tariff exposure is present across the sector but has not yet triggered guidance revisions. Intuitive Surgical quantified the impact at approximately 100 basis points of gross margin. Rockwell is passing tariff-related costs through an April price increase. Q2 earnings will be the first cycle where tariff impacts are more likely to show up in guidance if trade policy remains uncertain.
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Five companies across the robotics supply chain are sending unusually direct signals about industrial automation investment in 2026 — here’s what their earnings calls reveal.
