War has always been shaped by technology.

Gunpowder changed battlefields.
Aircraft changed distance.
Nuclear weapons changed deterrence.

Artificial intelligence may change speed.

Recent reports suggest AI systems were used during a wave of nearly 900 coordinated strikes on Iranian targets within 12 hours, compressing what once took days of planning into minutes.

For the first time, the “kill chain” — the military process from identifying a target to launching a strike — is being accelerated by machines.

Modern AI systems can analyse enormous volumes of information simultaneously.

Drone footage.
Satellite images.
Signal intelligence.
Historical strike data.

Platforms built by companies like Palantir Technologies combine machine learning and data analysis to prioritise targets, recommend weapons, and simulate likely outcomes.

Large language models such as Claude have reportedly been used to help analyse intelligence and support planning processes.

The goal is simple: shorten the time between seeing a target and acting on it.

Military strategists call this decision compression.

In practice, it means that operations which historically required days of analysis can now unfold in minutes.

In the recent conflict involving Iran, analysts say the speed of strikes was part of the strategy itself.

By launching hundreds of attacks simultaneously, the aim is to overwhelm a country’s ability to respond — disabling command systems, missile sites, and leadership structures before retaliation becomes possible.

AI makes this kind of synchronized operation far easier.

Instead of teams of analysts working through intelligence manually, algorithms can process thousands of signals at once and generate possible strike plans almost instantly.

The battlefield begins to resemble a real-time data problem.

But this acceleration creates a new concern.

Humans are slower than machines.

If an AI system can generate targeting recommendations in seconds, decision-makers may only have moments to review them.

That dynamic risks turning human oversight into a rubber stamp.

Some experts warn that this phenomenon — sometimes called “cognitive offloading” — could lead commanders to rely heavily on machine-generated reasoning.

Not because they want to surrender control.

But because the pace of modern conflict leaves little time for anything else.

The military use of AI is no longer theoretical.

The United States, China, and Israel are already integrating machine learning across intelligence, logistics, targeting, and cyber operations.

Companies like Anthropic and OpenAI have both explored partnerships with defence organisations, highlighting how closely advanced AI development is becoming tied to national security.

For countries facing sanctions or technological limitations, such as Iran, keeping pace with these capabilities is far more difficult.

The result could be a widening technological gap in warfare.

Artificial intelligence is not creating new wars, but it is fundamentally changing how quickly they unfold.

Historically, military strategy operated on longer timelines. Intelligence had to be gathered, analysed by teams of specialists, and debated before decisions were made. Planning major operations could take days, weeks, or even months.

AI is compressing that process.

Advanced systems can analyse vast streams of intelligence data — from satellite imagery to intercepted communications — in seconds. This allows militaries to identify targets, simulate outcomes, and coordinate strikes far faster than traditional planning cycles allowed.

As a result, the pace of modern warfare is accelerating.

The strategic advantage increasingly belongs to the side that can process information faster and act on it first. While human decision-makers remain formally responsible for approving military actions, the window for evaluating complex recommendations is becoming much narrower.

This shift suggests that future conflicts may be defined less by the size of armies or weapons stockpiles, and more by the speed at which information can be turned into decisions.