Autonomy isn’t new. Manufacturers have been testing and experimenting with it for years—local pilots such as Masdar City’s Personal Rapid Transit started moving passengers over a decade ago. What’s new is how quickly the industry is accelerating, driven by rapid innovation in AI and machine learning.
Most commercial R&D started with a focus on civilian use cases of autonomy, including passenger vehicles, where significant advances have been made. The military industry has followed, with autonomous systems being used in military units worldwide. But common for all is a key barrier to adoption at scale: The high cost of replacing fleets of existing vehicles given that autonomous technologies are not yet deployed at scale in most industries.
This barrier to adoption is further augmented in the defence industry, which has significantly higher performance demands than civilian mobility: Every vehicle has been purpose-built for resilience in high-risk missions, replacement parts are specialized, and procurement and certification processes are long and complex. These barriers are magnified even further in the Gulf region, where vehicles need to be able to operate in extreme environmental conditions.
In spite of these challenges, local defence forces can’t afford to ignore the benefits of autonomy, which combat units in theatres such as Ukraine are experiencing: Driverless vehicles keep personnel out of harm’s way and increase ROI. Autonomy is also a force multiplier, extending operational reach, allowing fewer people to do more, and enhancing precision and efficiency.
These benefits are increasingly outweighing the barriers to autonomy, and the most cost-effective, accessible solution for most organizations is becoming clear: Adapt existing platforms for autonomy rather than replacing entire fleets.
Autonomy integration: The smart path to defence autonomy
Adapting an existing system for autonomy doesn’t need to be a compromise. Adding autonomous capabilities to existing fleets has several advantages:
Improving ROI of existing fleets: Adding autonomous driving systems to existing fleets increases the ROI of expensive defence programs by extending their service life and adding new capabilities.
Lower operational costs: Autonomy reduces labour needs and increases productivity by enabling 24/7 operations. Additionally, service lifetimes are extended and maintenance costs are lowered thanks to more consistent operations and reduced wear. According to Japan’s Komatsu, autonomy leads to 40 percent longer brake and tire life and 13 percent lower maintenance costs compared to manual operations. Overall, operational costs can be reduced by almost 50% at scale.
Built-in sustainability: Retrofitting avoids up to 38 tons of embedded CO₂ per vehicle, equivalent to emissions that would otherwise come from manufacturing a new machine from scratch. More efficient routing systems also reduce idle time and optimize vehicle flow, trimming fuel consumption by double digits. This is good for the environment and operator budgets.
Gradual rollout: Equipping fleets with autonomous driving systems can happen gradually, with systematic integration into existing workflows. This helps ensure that autonomous vehicles remain multi-use, with human-driven modes that can be toggled as needed.
A gradual approach also facilitates careful testing and approval processes, allowing officers to minimize risk. Some civilian mobility operators can afford to experiment with full autonomy, where the risk of malfunction might mean commuters are delayed. But military generals can’t afford that kind of gamble.
Transforming legacy fleets for autonomy: What it means
Adapting a military platform for autonomy involves four key processes:
- Designing and integrating an autonomous hardware kit
Installed hardware kits consist of perception, localization, and onboard compute components: Cameras, radars, and LiDAR identify and classify objects in the vehicle’s path. GNSS, INS and LIDAR identify the vehicle’s precise position and location. Onboard edge computing allows for all decisions and algorithms to run locally.
- Customizing and developing the vehicle dynamics module
The way a specific vehicle moves, from steering to braking, is adapted to integrate with the autonomous driving system.
- Integrating the autonomous software stack
Software installed on an onboard computer fuses the sensor inputs and uses advanced decision-making algorithms to plot a navigational path. The software also incorporates critical safety logic, with the ability to automatically slow, stop, and alert fleet managers to intervene.
- Connecting the platform to a fleet management system
To maximize operations, most autonomous fleets are integrated with a fleet management system that can orchestrate multiple missions from a single interface.
What does all this mean for military personnel? In addition to spending less time in hazardous, front-line environments, they’ll have the opportunity to upskill: drivers and logistics specialists will transition into supervisory and systems roles and oversee multiple vehicles remotely, expanding operational reach, capacity, and resilience.
A practical call to action
The lesson for Gulf defence and government logistics operators is clear: Delaying will only widen the gap. Adapting even a fraction of your existing fleet can deliver measurable gains in fuel efficiency, uptime, and safety within a single year.
Start with a low-risk pilot and validate the impact by tracking fuel use, mission throughput, downtime, maintenance costs, and safety incidents—or lack thereof. The data will speak for itself.
Smarter, safer, sooner. That’s the power of adapting systems you already trust for autonomy.
