How much automation should military vehicles have?

History is basically a repeating argument between complexity and resilience. The chariot, the longbow, the machine gun, radar—every leap adds capability but also adds dependence on training and sustainment.

Look at WWII: German optics, fire control, and vehicle engineering often outclassed opponents on paper, but Allied success leaned on reliability, mass production, and maintainability. The Sherman’s “good enough” philosophy plus logistics mattered as much as tactical performance. Then the Cold War adds another lesson: as systems became sensor-heavy (rangefinders, stabilizers, thermal sights), doctrine also shifted—combined arms, faster engagements, and more emphasis on first-shot probability.

So “how much automation” depends on doctrine and industrial capacity. If your concept of operations assumes high tempo and night fighting, automation in fire control and situational awareness is not a luxury. But if you can’t sustain it—spares, techs, training pipelines—it becomes a weakness. The best historical analog is not ‘simple vs advanced’ but ‘advanced with a degraded mode.’ Every serious army eventually insists on graceful fallback procedures and manual overrides, because battle damage and friction are constants (Clausewitz never goes out of date).

From a “stuff that actually gets used” perspective, I like automation that reduces workload without trapping the crew in a touchscreen circus.

Good automation: driver aids that prevent rollovers, transmission management that reduces driver fatigue, turret stabilization and hunter-killer cues that speed up finding targets, and built-in diagnostics that tell you which module is unhappy. Bad automation: anything that forces you into deep menus under stress or needs pristine sensors to function.

I’d apply the same rule we use for field gear: it should work with gloves, in the dark, when wet, and when you’re tired. Give crews physical backups (manual levers, hard switches for core functions, simple reticles as a last resort). Also: standardize connectors, batteries, and displays across platforms. If each vehicle is a bespoke ecosystem, maintenance becomes the real enemy.

In training you learn fast that “automation” is great until it isn’t, and then you’re judged on basics.

I’m not anti-tech, but the vehicle has to be fightable in a degraded state. If comms are jammed, GPS is flaky, or a sensor gets shot, the crew should still be able to drive, navigate, and defend themselves with a simpler workflow. And the unit needs SOPs for that—like muscle memory drills: manual reversion, alternate comm plans, paper maps, simple battle drills.

Where automation helps most is reducing fatigue on long movements and cutting down routine errors. Where it hurts is when people stop learning fundamentals because “the system will do it.” The right amount is whatever still lets a competent crew operate when half the fancy stuff is down.

People romanticize “simple” like it automatically equals reliable. That’s not how modern combat works.

If you think you can roll around with minimal automation while the other side has better sensors, faster targeting, and networked fires, you’re basically volunteering to be detected first and hit first. That’s not toughness, it’s denial.

The real debate is: do you design automation with redundancy and discipline, or do you bolt on gimmicks to win demos? Manual overrides, training for degraded ops, and hardened comms/EW posture solve most of the “what if it breaks” whining. The bigger risk is leaders buying underpowered, under-sensored vehicles because they’re afraid of complexity—then acting shocked when crews lose the detection/engagement race.

Automation is becoming mandatory because the battlefield is saturating with sensors and cheap strike systems. Vehicles can’t rely on a human crew noticing everything in time.

Near-term “right amount” to me: automated perception and alerts (acoustic shot detection, UAS warning, thermal cueing), assisted driving (lane/edge detection off-road, obstacle warning), and semi-autonomous behaviors like follow-the-leader convoy. But keep a human in the loop for lethal decisions and tactical maneuver choices.

Also, automation should be designed assuming contested GPS and comms. Local autonomy that works offline is more valuable than cloud-like networking that collapses under jamming. The best systems will degrade: full sensor fusion when available, then partial, then basic with clear status indicators so crews trust what they’re seeing.

For tanks/IFVs the biggest automation wins are in fire control, stabilization, and target handoff—not in trying to make the whole vehicle “self-driving” in a fight.

Modern engagements reward first-round hit probability and faster hunter-killer cycles. Thermal sights, laser rangefinders, ballistic computers, and auto-lead calculations are proven value. Autoloaders are more nuanced: they can reduce crew size and sustain rate of fire, but they add mechanical complexity and change survivability tradeoffs (ammo placement, crew layout). Different armies accept different risks.

Where I’m cautious is over-automating mobility and command functions. If a track tension sensor fails, that shouldn’t cripple movement. If the digital architecture crashes, you still need basic gunnery and comm options. The “right” approach is layered: core mechanical functionality + robust fire control + modular electronics that can be swapped fast at the unit level.

Navies wrestled with this decades ago: ships are floating systems-of-systems, and automation is essential—yet crews still plan for casualties, battle damage, and loss of sensors.

The parallel lesson is redundancy and damage control culture. On warships you’ll see multiple navigation methods, backup comm paths, and training that assumes parts of the ship are dark. Military vehicles need the land equivalent: degraded navigation, manual turret operation, alternate power routes, and clear procedures.

Also, automation affects manpower. More automation can reduce crew size, but it can also increase the need for highly trained maintainers. On ships, fewer sailors sometimes means less capacity to fight fires and fix systems under stress. On land vehicles, fewer crew might mean fewer hands for security, repairs, and casualty evacuation. So the “right amount” isn’t just tech—it’s force design.

Aviation is a good cautionary tale and a success story at the same time. Autopilots, fly-by-wire, and sensor fusion make aircraft survivable and reduce pilot workload, but pilots still train for “partial panel” and emergency modes because failures happen.

Translating that to vehicles: automate to reduce task saturation (especially when scanning, communicating, and maneuvering), but train crews to operate when the fancy layer drops out. And make the interface sane—aviation learned that confusing alerting and mode logic can kill.

One thing I’d borrow directly is clear, prioritized warnings and a concept of “modes” that are obvious. If a vehicle is in GPS-denied nav mode or degraded fire control mode, the crew should know instantly.

From the people/training side, more automation doesn’t always mean less training—it often means different training.

If vehicles become more software-driven, units need operators who understand basic troubleshooting, and they need a maintainers pipeline that can handle electronics, networks, and calibration. That can affect recruitment standards, schooling length, and retention incentives.

So the “right amount” is whatever your force can realistically train and sustain. If you’re building a professional force with long enlistments and strong technical schools, you can lean into automation. If you rely on short service terms or rapid mobilization, you might want simpler core functions and automation that’s intuitive rather than specialized.

SOF tends to like tech that increases awareness and speed but hates tech that makes you predictable or dependent.

For vehicles used in raids, recon, or partner-force ops, I’d prioritize automation that helps with stealth and navigation (quiet mobility management, low-light driving aids, quick sensor checks) and comms integration that’s fast. But anything that creates a big electronic signature or requires constant connectivity is a liability.

Also: SOF mindset is “mission first, improvise when it breaks.” So modularity matters more than maximum integration. If you can swap a sensor pod, a radio, or a display quickly and keep moving, that’s better than a perfect integrated suite that takes a specialist team to revive.

Automation should never replace fieldcraft; it should support it.

Navigation is the classic example: GPS and digital maps are amazing until they’re wrong, blocked, or unavailable. Vehicles should make it easy to fall back to simple methods—dead reckoning, landmarks, paper map references, and basic compasses/odometry. Same for power: if the main electrical system is stressed, you want a straightforward way to keep essentials running.

In the field, the most “survivable” platforms are the ones that crews can understand quickly and fix with limited tools. So I’m pro-automation for alerting and workload reduction, but I’m also pro-simple redundancy and training that assumes the screen goes black.

Automation is also a budget and supply-chain question, not just a tactical one.

More automation tends to mean more dependence on microelectronics, specialized components, and software sustainment. In a prolonged conflict, that raises questions about sanctions resilience, domestic production, and the ability to surge repairs. It also expands the attack surface for cyber and electronic warfare.

That doesn’t mean “avoid it.” It means treat automation like a strategic capability with governance: secure supply chains, long-term software support, red-teaming, and export controls. The right level is one that matches national industrial capacity and alliance support, not just what engineers can prototype.

For engineering and logistics vehicles, automation can pay off massively—if it reduces accidents and speeds throughput.

Convoy driver-assist, collision avoidance, better diagnostics, and predictive maintenance are real force multipliers because they keep vehicles moving and reduce non-combat losses. But the design priority should be maintainability: line-replaceable units, clear fault codes, and the ability to run “limp home.”

Also, automation should help with mobility support: tire pressure management, traction control tuned for mud/sand, and load monitoring. Those aren’t glamorous, but they prevent bog-downs and breakdowns that stall an entire operation.

I’m still learning this stuff, but I’m wondering: is there a standard like “manual backup for everything important”?

Like, do modern tanks/IFVs still have a way to aim and fire if the main computer dies, or is it basically game over? And for trucks, if the autonomous convoy mode fails, can the driver just take over instantly?

If anyone has examples of vehicles that did automation well (or badly), I’d love to read about them.

In wargame terms, automation shifts the distribution of outcomes: fewer routine mistakes, higher average performance, but potentially sharper failures when the system collapses.

So the “optimal” design is layered autonomy with explicit fallback levels. Level 0: manual operation. Level 1: assist (stabilization, warnings). Level 2: task automation (auto-track, convoy follow). Level 3: limited autonomy in constrained environments. Each level should be testable and trainable.

Force structure matters too. If automation reduces crew size, you might need more dismounts or support elements to compensate for security and maintenance. Strategically, you want automation that increases operational tempo without making units brittle under EW and attrition.

The trajectory is more unmanned teaming than fully autonomous “robot tanks” replacing crews overnight.

A practical near-future answer: keep crewed vehicles, add automation that enables optional remote operation for the most dangerous tasks (route proofing, breaching observation, resupply under fire), and integrate small unmanned ground vehicles that scout ahead. That lets you push risk onto cheaper platforms.

But autonomy needs trust. That means rigorous testing, clear rules of engagement, and robust human-machine interfaces. And it needs to fail safely: if the autonomy stack is confused or jammed, it should revert to a conservative state rather than doing something unpredictable.