“Compared to data centers and memory, this trade is still early”
More capable and efficient artificial intelligence (AI) will not just lower the cost of compute needed to run models. It will also drive increasingly sophisticated automation in robotics across industrial, humanoid and eventually even domestic applications.
In this interview, Zeno Mercer, head of robotics and AI research at VettaFi, maps out the disciplined approach required to capture pure-play robotics companies and why physical applications of AI are re-energizing interest in automation as an investment opportunity.
How does the ROBO Global Robotics & Automation Index provide exposure to structural trends and innovation across industrial manufacturing, logistics automation and autonomous vehicles?
Robotics is the technology of turning energy into physically controlled precise action. Industrial manufacturing and logistics automation are the proof of concept: this is where that technology, and the economics behind it, proved out first, and where it now enables the modern world to run as it does. That has been an established one of this index since it was launched in 2013, the first benchmark to track robotics and automation as a single, investable universe. VettaFi has carried it forward since acquiring ROBO Global in 2023, alongside AI strategies ROBO Global Artificial Intelligence Index and ROBO Global Healthcare Technology & Innovation Index.
Autonomous vehicles are an entirely different kind of exposure. Solving autonomy for one vehicle category, a car, a truck or a drone does not just produce a better vehicle. This enables a platform shift, the same kind a mobile phone triggered once it stopped being a phone and became a surface for businesses nobody had imagined yet. Robots are defined by the ability to sense, analyze and act. ROBO constituents sit across that whole enabling chain: the sensors and compute that sense and analyze, and the delivery robots, warehouse vehicles and humanoids that act on it.
What criteria determine whether a company is eligible for inclusion in the index?
The process for inclusion is systematic, with a research-driven overlay. Thematic revenue purity comes first: how clearly a company’s businesses ties to the subsector it would be assigned under our industry and subsector classification. That classification maps each candidate to where it actually sits in the robotics and automation value chain, and it is the backbone the rest of the scoring builds on.
From there, we weigh market leadership, and I want to be precise about that phrase: market leadership, not market capitalization. A company can be relatively small compared to many of today’s tech giants but still command an important part of the economy in an area that is blossoming, growing as the technology leader in its subsector. We look at the cadence and focus of its research and development spend, its product pipeline, its partnerships, its mergers and acquisitions and the strength of its management and leadership. Growth opportunity and underlying financial health round out the scoring.
On top of that scoring sit hard constraints: minimum market cap and liquidity thresholds so the index stays investable, and an ESG filter that screens out companies with unacceptable practices.
All of it runs through our industry advisory council using a top down, bottom up approach. Top down to map the full universe of subsectors. Bottom up to vet the individual company data. That combination keeps the process disciplined: broad enough to capture the full universe and rigorous enough to keep out companies that do not actually belong.
How are you adjusting the index’s subsector classifications to capture the rapid development of AI and humanoid technologies and how is this reflected in constituent selection and weighting?
Our subsector framework covers 100% of the robotics universe. On one side are enabling technologies: sensors, chips, microcontrollers, machine vision and actuation, the components that let any robot sense and move. On the other are industry-specific subsectors, healthcare (surgical robotics) and agriculture among them, where the end use case defines the category. We built it with long-term vision in mind, wide enough to hold categories that did not exist when we first drew the map.
The autonomous systems subsector lands differently. It is built to capture multi-domain, multi-form factor robotics with diverse applications, rather than one industry vertical, a home for whatever the industry decides to build a robot with next. It used to be small enough that a single name more or less created the category on its own.
Autonomous systems is now our fastest growing subsector, though still small relative to core industrial automation and logistics. It is our catch-all for drones, electric and autonomous vehicles, humanoids and multi-bot systems, so new entrants live in it rather than requiring a new bucket. Elements of AI and humanoid development also show up elsewhere, computing and AI, sensing, integration among them, but the fully embodied systems land here.
What is driving continued investor demand into ETFs tracking the index?
Demand is being driven by more than one factor currently. First, there is a basic recognition that most of GDP still runs through the physical world, not through software alone. As the pure AI trade starts to feel crowded, investors are rotating toward that side of the ledger and robotics and automation is where a lot of that capital is heading. Some are even looking to hedge against AI disruption itself, as robotics is seen as an ultimate beneficiary.
Some of it is simple normalization, too. Robotics saw relative and real underperformance and outflows before this cycle, so part of what looks like fresh demand is the sector recovering ground it had lost. Beyond that, some investors are drawn in by humanoids and new form factors. Others are underwriting reshoring and broader industrial automation, a steadier thesis with less noise around it.
Our own polling picks up both dynamics: enthusiasm varies by thesis, but appreciation and general understanding of the space are both rising as robotics becomes a more mainstream conversation. What is consistent is the stage. Compared to areas like data centers and memory, this trade is still early.
The ROBO Global Robotics & Automation ETF (ROBO), ROBO Global Artificial Intelligence ETF (THNQ), and ROBO Global Healthcare Technology & Innovation ETF (HTEC) seek to track the respective indices referenced in this article.
This article originally appeared on ETF Stream.
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The risks associated with investments in Robotics and Automation Companies include, but are not limited to, small or limited markets for such securities, changes in business cycles, world economic growth, technological progress, rapid obsolescence, and government regulation. Robotics and Automation Companies, especially smaller, start-up companies, tend to be more volatile than securities of companies that do not rely heavily on technology. Rapid change to technologies that affect a company's products could have a material adverse effect on such company's operating results. Robotics and Automation Companies may rely on a combination of patents, copyrights, trademarks and trade secret laws to establish and protect their proprietary rights in their products and technologies. There can be no assurance that the steps taken by these companies to protect their proprietary rights will be adequate to prevent the misappropriation of their technology or that competitors will not independently develop technologies that are substantially equivalent or superior to such companies' technology.
The risks associated with Artificial Intelligence (AI) Companies include, but are not limited to, small or limited markets, changes in business cycles, world economic growth, technological progress, rapid obsolescence, and government regulation. Rapid change to technologies that affect a company’s products could have a material adverse effect on such company’s operating results. AI Companies also rely heavily on a combination of patents, copyrights, trademarks and trade secret laws to establish and protect their proprietary rights in their products and technologies. There can be no assurance that the steps taken by these companies to protect their proprietary rights will be adequate to prevent the misappropriation of their technology or that competitors will not independently develop technologies that are substantially equivalent or superior to such companies’ technology. AI Companies typically engage in significant amounts of spending on research and development, and there is no guarantee that the products or services produced by these companies will be successful.
The risks associated with Medical Technology Companies include, but are not limited to, small or limited markets for such securities, changes in business cycles, world economic growth, technological progress, rapid obsolescence, and government regulation.
Diversification may not protect against market risk.
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