How AI is rewriting rules of warfare and who leads new military era? Article by Al Jazeera

An article published by international broadcaster Al Jazeera explores the rapidly developing AI-driven military technology sector, examining how artificial intelligence is transforming modern warfare and reshaping the defence industry. Caliber.Az brings its readers the most compelling insights from the article.

“For centuries, fighting wars meant deploying hardware such as tanks, aircraft, artillery and weapons, built by a handful of prime contractors under long-term government programmes. That paradigm is not disappearing, but software is becoming increasingly central to it. And now, more soldiers are fighting wars through a screen.

The military AI industry now encompasses everything from cloud computing to autonomous drones and decision-making software. This shift traces back to the US drone programme of the 2000s and 2010s, which turned remote, screen-based killing into a feature of how wars would be fought.

Billions of dollars are flowing into a handful of companies now leading the AI transformation of militaries, as the old military-industrial complex reshapes itself into a military-tech one.

As part of a series on AI and warfare, Al Jazeera looks at who some of these companies are.

Who are these companies?

On July 10, the UK Ministry of Defence signed a 2bn pounds ($2.7bn), 15-year contract with Omnia Training, a consortium led by Raytheon UK, to train 60,000 soldiers a year on using AI to make a “combat-ready” British military.

Days earlier, NATO awarded contracts to run the alliance’s Enhanced Air Command and Control Data Platform to US military-tech company Anduril for its Lattice AI software alongside US firm Palantir and the French military-tech joint venture Athea SAS. Lattice uses AI and computer vision to bring data from multiple sources into one live picture.

AI defence procurements are not new. The Pentagon’s 2014 “Third Offset Strategy” bet explicitly on AI defining the next generation of warfare, but the pace appears to be picking up as global military expenditure climbed to $2.88 trillion in 2025, with governments pouring record sums into defence budgets.

With wars raging from Ukraine to the Middle East, deals like these are multiplying fast, and the industry itself is evolving just as quickly – traditional arms firms and new entrants alike are jostling for a slice of the market. Researchers at the Stockholm International Peace Research Institute (SIPRI) mapped the AI military industry, grouping firms into four categories based on their role in the industry:

• Defence primes: traditional arms companies

• Neoprimes or defence startups: newer firms specialising in software for the military industry

• Big tech: tech giants that have massive cloud/computing capacity

• Foundational model providers: frontier AI labs building advanced AI models

Defence primes/contractors

These are the long-established arms manufacturers that have supplied militaries with systems and hardware for decades, and are now layering AI onto those existing systems. The largest of these firms include Lockheed Martin Corp, RTX, Northrop Grumman Corp, BAE Systems and General Dynamics Corp, all of which hit all-time highs after the onset of the US-Israel war on Iran.

In February, Lockheed Martin announced that it was flight-testing an AI tool for its F-35 fighter jets to help pilots identify hostile aircraft faster.

L3Harris, another American defence firm, built AI directly into its camera systems for real-time targeting.  It is also fitted with platforms like Shield AI‘s Tracker, which helps detect hostile drones. Shield AI is a US defence-tech company building autonomous AI pilots for military aircraft and drones.

Neoprimes or defence startups

This newer category, sometimes referred to as “neoprimes”, is software-first firms, selling specialised data products to the arms market as well as policing and border forces.

Palantir is perhaps the best-known name among such firms, largely through its role in Project Maven, the Pentagon’s flagship military AI programme. It is designed to speed up decision-making in battle, relying on AI and machine learning to automatically sift through satellite imagery, drone videos, and signals intelligence to identify and prioritise targets.

The system is being used in various conflicts, including the Ukraine war and US-Israel war on Iran — Maven identified 1,000 targets in the first 24 hours of the latter conflict. A direct competitor to Maven is Anduril’s Lattice platform, which ties its own hardware – drones, sensor towers, autonomous vehicles – into a single command network, with it being heavily utilised by the US Army.

Big tech 

Companies like Google, Meta and Amazon Web Services (AWS), which control roughly 67 percent of the global cloud infrastructure market, are increasingly linked to military applications that traditional defence contractors are providing.

In May, the US Department of Defense announced a new agreement with eight tech and AI companies to use their technologies for its classified networks. The agreements with SpaceX, OpenAI, Google, NVIDIA, Reflection, Microsoft, Oracle and AWS were brokered to “accelerate the transformation towards establishing the United States military as an AI-first fighting force”.

The deal has meant these companies have been cleared for IL6 and IL7 networks, the most sensitive and classified computing environments the Department of Defense operates.

Foundational model providers

The final category is firms that build the underlying AI models that other companies integrate into military tools, such as OpenAI and Anthropic in the US and Mistral AI in Europe.

Chinese researchers have been developing AI models for military use since the early 2020s, including using Meta’s Llama model as the base for the People’s Liberation Army (PLA) tool called ChatBIT, which was designed to gather intelligence and support decision-making in the field, according to Reuters.

The Pentagon estimated Chinese military AI spending comparable to American figures, about $1.5 to $2bn annually,” the article states.