Utilities have the assets, the safety case and the workforce gap. What has stalled robotics adoption for a decade is not whether the robots work. It is the balance sheet, the procurement cycle and the absence of anyone in-house who knows how to run a fleet of them.
Robotics as a Service moves robots from a capital purchase to a subscription. The provider supplies the equipment, the software, the maintenance, the upgrades and sometimes the trained operators. That solves the capital problem, and it solves the expertise problem. It does not solve all of them, and for a meaningful set of utility tasks buying the robot outright is still the cheaper answer. This article covers how we mapped the market, what we found when we studied it, and where the service model actually holds. The five startups to know have signed agreements where the utility never buys the robot, and no two are structured the same way.
Who does robotics for utilities matter to?
| Who | The decision in front of them |
|---|---|
| Electric, gas and water asset owners | Ageing infrastructure and a shrinking inspection workforce, against a reliability obligation that does not move. Which tasks can be automated, and on what commercial model? |
| Utility procurement and asset management | Whether to run a hardware procurement cycle or buy a service. The answer differs by task, and getting it wrong is expensive in both directions. |
| Small utilities | Capabilities that a capital budget cannot justify on its own. RaaS is often the only route to advanced inspection at this scale. |
| Large utilities | Multi-site deployment without a lengthy hardware procurement, by shifting to service procurement instead. |
| Corporate venture and innovation teams | Which robotics suppliers to pilot, and which will still be trading when the pilot becomes a rollout. |
| Investors and O&M contractors | Which RaaS revenue is durable and which gets insourced by the customer once volumes rise. |
Why have utilities been slow to adopt robotics?
Utilities run pipelines, substations, reservoirs, treatment plants, power lines and underground networks that all require continuous inspection, maintenance and repair. They are doing that against ageing infrastructure, workforce shortages, safety risk in hazardous environments, regulatory pressure on reliability and a standing requirement to cut operating cost.
Robots are well matched to that work. Drones inspect transmission lines and wind turbines, ground robots handle substation and pipeline rounds, underwater robots examine dams and reservoirs, and autonomous vehicles map sewer networks. The tasks are dangerous, repetitive or simply hard for a person to reach.
Adoption still stalls, and it stalls on four things: high upfront investment, uncertain return on investment, integration with legacy infrastructure, and limited internal expertise in robotics and automation. Both large and small utilities hit the same wall for different reasons. Large utilities have complex internal buying procedures, deep legacy systems to integrate with, and organisational inertia. Small utilities have limited budgets, small technical teams, and no way to justify capital expenditure on a specialised robot that will be used intermittently.
What does Robotics as a Service actually change?
RaaS attacks the capital barrier directly. Instead of buying robots and building an in-house capability, a utility accesses robotic systems through subscription or service agreements where the provider carries the equipment, software, maintenance, upgrades and sometimes the operators.
Two things follow that matter more than the accounting treatment. The provider spreads equipment cost across multiple clients and projects, so utilisation rates improve and the unit economics work at volumes a single utility could never reach alone. And because providers standardise their platforms across industries and infrastructure types, they achieve economies of scale that an in-house programme cannot.
Two caveats sit against that, and both get lost in vendor material. A full robotic service, where the provider operates the robot as well as owning it, is simpler for a utility with a thin technical team than a RaaS subscription, where the client usually operates it. And RaaS carries less risk than ownership but not none, because operational risk stays with whoever is running the robot. We score both service models against outright ownership on seven parameters in the research, and ownership wins on fewer of them than most utilities expect.
How we mapped the market
Every company we track in this market is classified on the same grid. One axis is the job the robot does: inspection, maintenance, repair, and a fourth group for work that falls outside those three. The other is the utility that owns the asset: electric, covering grid and power infrastructure alongside renewable, thermal and nuclear generation, then gas, water and waste. Each cell holds use cases that break down further. Power lines inspection contains grid vegetation monitoring. Wind turbine inspection contains blade inspection, tower and foundation inspection, and offshore wind inspection. That is the level a provider is classified at, so it sits against a specific job on a specific asset class rather than a sector label.
| Sector | Inspection and monitoring | Maintenance | Repair | Others |
|---|---|---|---|---|
| Electric: grid and power infrastructure | Power lines, substations, underground cable and tunnels, grid vegetation monitoring | Live-line maintenance | None classified | Grid construction |
| Electric: generation | Solar farms, wind turbine blades, wind tower and foundation, offshore wind foundations and subsea, hydropower, thermal plant, nuclear | Solar panel cleaning, solar vegetation management, wind turbine cleaning | Wind turbine blade repair | Solar piling |
| Gas | Gas pipelines, gas facilities, gas storage tanks, methane leak detection | None classified | Gas pipeline repair | None classified |
| Water | Water pipelines and sewers, water treatment plants, water leak detection | Sewage cleaning | Water pipeline repair | None classified |
| Waste | None classified | None classified | None classified | Waste sorting |
Twenty-nine use cases in total. Behind each one, the research holds the robot types actually in use, how often the work runs, how mature and how standardised it is, and whether the commercial model is settled. That is the level a procurement or technology decision gets made at, so it is worth seeing what one sector looks like filled in.
One sector in full: water
Water is the clearest illustration, because its five use cases span the whole activity range in one place: routine inspection, continuous monitoring, maintenance and on-failure repair. The other three sectors are structured the same way.
| Use case | Robots in use | How often it runs | What shapes adoption |
|---|---|---|---|
| Water pipeline and sewer inspection | CCTV crawler robots, dominant; autonomous inspection robots emerging | Recurring | One of the most mature robotic use cases in the water sector |
| Water leak detection | In-pipe acoustic robots, sensor-equipped mobile robots | Continuous monitoring | Detects leaks and pressure anomalies as they occur |
| Water treatment plant inspection | Ground robots on rounds, drones on elevated assets, ROVs inside tanks, basins and reservoirs | Frequent and operationally necessary, because plants run continuously | Multiple asset types on one site. ROVs allow internal inspection without draining the system |
| Sewage cleaning | High-pressure jet robots, teleoperated cleaning robots | Recurring | Removes grease, debris and sediment from pipes |
| Water pipeline repair | In-pipe systems sealing leaking joints, injecting resins and applying liners | On failure | Repairs from the inside, and avoids excavation |
What we learned studying the space
The dividing line is whether the robot observes or intervenes. Applications focused on monitoring and data collection are well suited to service-based models, because the tasks are periodic and require limited integration with operational processes. Where robots interact directly with operational systems, as in maintenance and repair, they need deeper integration and greater customisation, and adoption has been slower as a result. That single distinction explains most of what follows.
The map is lopsided in exactly the way that predicts. Of the twenty-nine use cases, eighteen are inspection or monitoring, five are maintenance, three are repair and three sit outside all three. Repair is the thinnest column on the whole grid, with one use case each in electric generation, gas and water, all of it on-failure work demanding precision under uncertainty. Commercial maturity tracks the same line.
Source: Net Zero Insights, Robotics-as-a-Service for Utilities Market Snapshot.
RaaS reinforces this pattern rather than flattening it. It accelerates inspection, where adoption was already easiest. It enables more flexible on-demand use in maintenance. And it has the potential to make advanced repair economically reachable eventually, by spreading the cost of capabilities no single utility could justify buying.
Rent or buy is not a market-level answer, it is a task-level one, and the research settles it for nine of the twenty-nine use cases. Two of them give the shape of it. Ground robots walking a substation are usually owned, because the assets are fixed and the inspection is continuous and critical. Underground cable and tunnel inspection is usually rented, because it is infrequent, confined and needs specialised equipment and expert operators. Frequency is the dimension that flips the answer most often, with technical maturity, how standardised the asset is and the expertise the job demands behind it.
The finding utilities react to hardest is the one that cuts against the pitch. Providers standardise their platforms across industries and infrastructure types to reach the economies of scale that make a subscription cheaper than ownership. That same standardisation limits how far they can adapt to a highly specific legacy utility system. The thing that makes RaaS affordable is the thing that makes it hard to integrate, and no amount of contracting gets around it.
What does robotic inspection deliver against manual inspection?
The figures below are the ones most often quoted in the market. They come from drone service providers and practitioners rather than from peer-reviewed work, so treat them as indicative of what vendors are claiming rather than as settled numbers.
| Metric | Reported value |
|---|---|
| Cost reduction versus manual inspection | 30 to 50% |
| Time reduction | 75% |
| Increase in issue detection | 48% |
| Capital expenditure avoided | Around $250,000 |
The detection figure is the one worth dwelling on. A 48% increase in issues found is not a cost saving, it is a change in what the utility knows about its own network. On an ageing asset base that is usually the more valuable outcome, and it is the one that does not show up in a procurement business case built purely on cost per kilometre.
How big is the market?
Two things are being sized here and they are often conflated. The first is the RaaS business model across all industries. The second is robotics for utilities specifically, whether owned or rented.
| Market | 2025 | Forecast | CAGR |
|---|---|---|---|
| Robotics as a Service, all industries | $2.11B to $2.40B | $9.83B to $12.4B by 2035 | 16.63% to 18.00% |
| Inspection robots | $5.62B | $29.82B by 2034 | 20.38% |
| Robotic preventive maintenance | $7.43B | $22.07B by 2035 | 11.50% |
| Pipe inspection robots | $5.50B | $23.60B by 2035 | 17.60% |
| Power grid inspection robots | $1.17B | $3.50B by 2035 | 11.70% |
| Smart gas leak detection robots | $1.34B | $2.71B by 2030 | 15.00% |
The comparison worth making is between the RaaS market and the equipment markets it sits inside. Robotics as a Service across every industry is roughly $2B today. Inspection robots alone are $5.62B, and robotic preventive maintenance is $7.43B. RaaS is a small and fast-growing slice of a much larger installed base, which tells you the default in utilities is still ownership.
Ownership stays the default until something forces the pace, and that is what regulation is starting to do. Nothing in law mandates a service model, but the EU Methane Regulation and the EPA’s Methane Emissions Reduction Program and Waste Emissions Charge both require leak detection and repair with a reporting trail, which turns a discretionary inspection programme into a compliance obligation. Recurring, dispersed and sensor-heavy is exactly the shape of work a service model suits, and it lands hardest on gas networks.
Who can actually take that work on is a different question, and the contracts answer it better than the pitches do. We track 85 companies against this map along with the agreements they have signed. A handful of utilities are buying more than once, and Veolia has done it three times through three different suppliers on three continents.
