by Berend Booms, Associate Editor, Future of Assets
Reliability is one of my favorite topics in asset management. As a concept, it is often spoken about as if it were primarily a function of engineering. In practice, I think most of what we consider to be “reliability” is shaped by something that is more operational in nature: whether inspections happen when they are supposed to happen, whether early signals are recognized in time, and whether the data collected is trusted enough to act before it is too late.
Looking at the way assets are managed across plants, substations, terminals, and offshore facilities, a pattern begins to emerge. The gap between what we think we know and what we confidently act on is rarely caused by a lack of technology. It is shaped by distance, access, weather, risk, compliance, and the simple reality that skilled people cannot be everywhere at once. This is where robotics has started to find its footing.
The Current State of Robotics in Asset Management
Robotics in asset-intensive industries is neither experimental nor ubiquitous; it sits somewhere in between. The most mature deployments are not focused on autonomous repair or decision-making, but on extending presence, allowing broader and more consistent coverage. Robots are being used to move through environments, collect consistent data, and reduce the reliance on manual inspection and handling that is difficult to sustain over time.
It is therefore no surprise that inspection and monitoring dominate current use cases. Mobile robots follow repeatable routes, capturing thermal, visual, acoustic, and sensor data in a way that establishes a highly consistent baseline over time. The value they provide is not so much the movement itself, but the reliability of their observation: when inspection becomes consistent, any form of deviation becomes increasingly visible.
At the same time, battery life, connectivity, accessibility, and environmental constraints still limit where and how robots can operate. More importantly, robotics is not a silver bullet; rather, it introduces a familiar challenge in a new form. It is great that they are able to capture data so consistently, but data without context does not create clarity. Many organizations already struggle to make sense of their data; having more of it does not translate into better decisions or more effective action. Robotics starts to become meaningful when it integrates more closely into how decisions are made.
Consistency Across The Board
A useful way to understand where robotics stands is to look at where it is already embedded in operations and adding tangible value. Across industries, a clear pattern emerges in how and where robotics is applied. One of my favorite robots is Boston Dynamics’ Spot. I am always excited to see it at exhibits and trade shows, even more so to see it in action in a plant or site. It is equipped to perform structured inspection rounds in industrial environments, capturing visual imagery, thermal readings, and acoustic data as it moves through predefined routes. It can detect temperature deviations in equipment, identify leaks or hotspots, read analog gauges, and listen for anomalies in rotating assets using acoustic sensors. In environments where conditions are hazardous or access is limited, it provides a consistent way to collect condition data without exposing people to risk, while creating a digital record of inspections that can be trended over time. One reported case involved early detection of a failing bearing, allowing intervention before failure occurred.
In logistics, robotics takes a different form and fills a different need. A good example is Victoria International Container Terminal in Melbourne, Australia. Here, automation is applied to the movement of containers through automated straddle carriers and coordinated systems. While speed is one of the primary benefits, the more meaningful advantage lies in consistency and predictability of movement. When assets operate within defined parameters, the variability in how assets are used is reduced, which helps reduce the variability in how they degrade over time. The implications extend beyond throughput and into asset health and lifecycle performance. When operations become more predictable, the maintenance of your assets becomes more manageable.
When we look at oil and gas, robotics’ application is largely shaped by risk and access. A strong example of this is ANYmal, one of ANYbotics’ inspection robots used in offshore environments where hazardous-area certification, logistical constraints, and safety considerations limit how inspections can be performed. ANYmal is designed to operate in these constrained environments, performing inspections and detecting anomalies without exposing people to the same level of risk. Here, the value ties back not just to frequency and consistency, but also to safety. When the effort and risk of inspections are reduced, you regain time as a decision variable.
I sometimes think that with robotics the sky is the limit. This takes on a different meaning when we look at the energy and utilities sectors: here, robotics are often airborne. Drones are deployed into operations at scale, as they are capable of performing hundreds of inspections daily. This is particularly valuable given the scale and geographic spread of assets in these sectors, and the conditions they are often exposed to. After a major weather event, the ability to establish situational awareness quickly and take required actions decisively becomes critical, especially when entire communities are relying on the performance of these assets. Drones shift inspection from a logistical challenge to a system capability.
Building a Business Case for Robotics
Across these industries, robotics is applied where the cost of delayed insight is high, where access is difficult, where safety is at stake, and where consistency matters as much – if not more – than speed. The investment case for robotics becomes clear when viewed through that operational lens. It is tempting to frame robotics primarily through the lens of labor savings, but this does not accurately capture its operational value. In most asset-intensive environments, labor is already constrained rather than excessive. The more relevant question then becomes: how do we use available expertise more effectively?
Robotics starts to answer that question by increasing consistency. It enables inspection routines to be executed consistently, at the same intervals, without the variability that naturally occurs in manual processes. Over time, this leads to a more stable baseline of information, making it easier to detect change within the right context. It also shifts the risk equation. In hazardous or hard-to-reach environments, robotics reduces the need for human exposure to risk. The improvement to safety is obvious, but it’s important to also consider the operational improvements: when access becomes easier, inspection frequency can increase, your information flow becomes more consistent and reliable and with it, your ability to act decisively when it matters most. There is also a long-term effect that is sometimes overlooked: robotics creates a more resilient monitoring layer. Most industries are dealing with labor gaps and knowledge scarcity; having robotics fill some of those gaps creates a more stable and consistent source of intelligence and insight.
The investment in robotics is not one that is limited to technology; the real effort lies in integration. Inspections and routes need to be defined, processes need to be updated and clearly documented, data flows need to be connected to asset management platforms, and teams need to be trained to interpret and act on what is observed. Organizations that treat robotics as a standalone solution often struggle, while those that embed it into existing operational discipline tend to see more durable results.
The Balance Between Augmentation and Displacement
In discussing robotics in asset management, it is only fair I also discuss the question of augmentation versus displacement. In practice, robotics does replace certain types of work and does so very effectively. Repetitive inspection tasks, structured movements, routine data collection tasks: they are well suited to automation, and we already see this transition in environments such as ports, warehouses, and highly standardized manufacturing facilities.
At the same time, the more meaningful impact lies in augmentation. By removing the need for people to perform repetitive or hazardous tasks, robotics decreases exposure to risk, and allow skilled labor to focus their expertise on higher priority, higher value, business-critical tasks.
This is where the balance becomes important. Many technical roles are built on experience gained through repetition. If that repetition is reduced, organizations need to approach skills development more deliberately. Robotics changes how the work is done, but does not remove the need for expertise; it redistributes it.
This redistribution becomes even more relevant in the context of labor shortages. Across manufacturing, energy, and logistics, the availability of skilled labor is a structural constraint rather than a temporary hurdle. At the same time, the complexity of the asset environments being managed continues to evolve and increase.
Robotics offers a way to alleviate some of this mounting pressure, not by replacing the human worker, but by allowing organizations to deploy their expertise more effectively. Time spent on low-value repetitive tasks or high-risk activities can be reduced, creating space for the type of work that requires judgment and experience.
There is also a cognitive dimension to all of this. Consistency in execution reduces noise, and when the basics are handled reliably, teams and individual asset professionals have more capacity to focus on what requires attention. It can help shift organizations from reactive firefighting toward proactive asset management. If you are only reacting to issues as they emerge, you leave little room to optimize your approach. In that sense, robotics supports not only operational efficiency, but also creates operational maturity and growth.
The Future of Assets and the Role of Robotics
It’s difficult to predict what the future holds, but I think that the trajectory of robotics in asset management is unlikely to be defined by sudden breakthroughs. More likely, it will be shaped by the gradual integration of technological advancements in artificial intelligence. Robotics will become less visible as a standalone topic and more embedded within broader asset management strategies. Inspection, data analytics, and maintenance will increasingly form connected loops, where data collected autonomously feeds directly into decision-making processes. The role robotics plays in that system is straightforward: it extends the organization’s ability to observe their operations with increased levels of frequency and consistency.
Ultimately, the future of robotics in asset management depends on what we do with the observations we generate. Which inspections are we not doing because they are too difficult, too costly, or too dangerous? Which risks are we willing to accept or defer because access is limited? Which decisions are we not confident in taking because the data is not strong enough to support decisive action?
These are not new questions, nor are they limited to the application of robotics within asset management. What is changing is that the constraints that apply to robotics are starting to shift. Robotics does not remove complexity; it is simply more effective in making certain limitations more visible. And perhaps that is where its real value lies: not in replacing people or transforming operations overnight, but by making it increasingly difficult to ignore the gaps it reveals. In building the Future of Assets, that kind of visibility may ultimately move the needle more than any individual technology.