AI, Automation, and War

Anthony King is a sociologist of war at the University of Warwick, and AI, Automation, and War, published by Princeton University Press in 2025, is his attempt to drag a debate dominated by speculation back onto empirical ground. The book is built on roughly a decade of fieldwork and 126 interviews with serving officers, defence-ministry officials, think-tank analysts, and executives at the technology companies now selling into the Pentagon, Whitehall, and the Israel Defense Forces. King writes against a literature that has, in his reading, become unusually consensual: from the open letter signed by Stuart Russell, Stephen Hawking, Elon Musk, and Demis Hassabis at the 2015 International Joint Conference on Artificial Intelligence, through Russell’s 2020 BBC Reith lecture on slaughter-bots, to Henry Kissinger, Eric Schmidt, and Daniel Huttenlocher’s The Age of AI, the field has converged on the view that machines are about to displace human commanders and human soldiers. King thinks that view is wrong, or at least vastly premature, and that getting it wrong matters because it crowds out a more accurate and more disturbing story about how military AI is actually being absorbed.

His central argument is that the popular framing — autonomous killer robots on one side, reassuring talk of humans-in-the-loop on the other — misses what is happening. AI is real, it is here, and it is consequential, but it is not automating war. Its dominant function in Western militaries today is the fusion and processing of intelligence, sensor, and logistics data at scales and speeds beyond human reach. Commanders are not being replaced; they are being given a faster, deeper picture of the battlespace from which to decide. King takes his methodological cue explicitly from David Hume, refusing causal predictions about a future for which there is no evidence, and confining himself to what armed forces have actually done in the past two decades. The more interesting transformation, he argues, is not technological but organisational: armed forces are restructuring their headquarters, their procurement, and their relationship with the private sector to be able to use AI at all. The result is the emergence of what he calls a military-tech complex — a hybrid civil-military configuration distinct from the older military-industrial complex of Lockheed, BAE, and Raytheon, and one with serious political and constitutional implications.

The book is built in ten chapters that move outward from technology to organisation to operations. An opening pair, Robot Wars and What AI Can Do, sets out the literature and provides a sober tour of what second-generation, data-driven AI can and cannot do — its breakthroughs in protein folding via AlphaFold, in commerce at Amazon and Walmart, in image recognition, alongside the brittleness exposed by Winograd schemas and the hallucinations of large language models. AI Strategy surveys the doctrinal documents — the US Third Offset Strategy of 2014, the National Security Commission on Artificial Intelligence, US Air Force and US Army concepts, NATO’s policies, and the UK’s defence AI strategy. A Military-Tech Complex and The Special Relationship examine how Silicon Valley emerged from Cold War defence funding and has now been re-pulled into national security work, and how Special Operations Forces in particular have built unusually close partnerships with tech firms. AI and Planning, AI and Targeting, and AI and Cyber Operations work through specific operational domains. The Human-Machine Team challenges the centaur metaphor borrowed from chess, and the closing chapter, War at the Speed of Light, draws careful, deliberately limited conclusions about where this is all heading.

The empirical heart of the book is the case material King has gathered on three militaries — the US, the UK, and Israel — and on the firms now embedded with them. Palantir Technologies receives the most sustained treatment. Founded by Peter Thiel and a group of PayPal alumni, Palantir grew out of fraud-detection software and was repurposed for counter-IED work in Iraq and Afghanistan after Marines and Special Operators began using it without official sanction. King traces how Stanley McChrystal’s Joint Special Operations Command in Iraq, hunting Abu Musab al-Zarqawi and later ISIS, became the forcing function for a new kind of data-driven targeting, and how Palantir eventually sued the US Army to be allowed to compete against the bespoke Distributed Common Ground System. Anduril, founded by Oculus’s Palmer Luckey, gets credit for its Lattice sensor-fusion platform and the way its veterans of Special Operations seeded the company. Helsing in Europe, Rebellion Defence and Adarga in the United Kingdom, and the Israeli ecosystem around Elbit Systems and Rafael round out the picture.

Project Maven is the canonical example. Established in 2017 under Robert Work and run operationally by Jack Shanahan and Drew Cukor, Maven was designed to apply computer vision to the deluge of full-motion video coming off uncrewed aerial systems over Iraq and Syria. Google won the initial contract, then dropped it after employee protests; the program continued, eventually migrating to Palantir’s Metaconstellation platform. King uses Maven to make several points at once: that the dominant problem AI solves for Western militaries is data triage rather than autonomous killing; that the procurement bureaucracy could not have produced Maven on its own and required a parallel structure, the Defense Innovation Unit, to bypass the Cold-War waterfall model; and that even a relatively narrow image-classification task required deep, ongoing human work — the labellers at CrowdFlower, the data scientists at Google and then Palantir, the targeting officers in headquarters who actually used the output.

The Israeli material is among the book’s most striking. King describes Operation Guardian of the Walls in May 2021, which the IDF described as the “first AI war,” and the much more brutal campaign in Gaza after the Hamas attacks of 7 October 2023. Two named systems anchor the discussion: Gospel (Habsora), which generates building-level targets, and Lavender, which generates lists of suspected Hamas militants. Both have been used at industrial scale, and King is careful with what they actually do — they propose, they classify, they fuse intelligence streams; they do not autonomously fire. The decision to strike, and the decision about how much collateral damage is acceptable, remains with human officers, often under conditions of extreme time pressure that may make the AI’s recommendation effectively decisive. The Torch battle-management system, supplied by Elbit, illustrates how deeply Israeli defence firms have integrated with the IDF, in a way King contrasts with the more arm’s-length British and the more contested American relationships.

The Russo-Ukraine War runs through the book as the most important contemporary case. King describes the Ukrainian IT Army, Mykhailo Fedorov’s Ministry of Digital Transformation, and the role of Microsoft, Amazon Web Services, Google, ESET, and SpaceX’s Starlink in keeping Ukrainian command and control alive under Russian cyber and kinetic pressure. The Kropyva and Delta battle-management systems pull together commercial satellite imagery, social-media reporting, and tactical sensor data into a common operating picture. Palantir software is reportedly behind the targeting that wounded Russian Chief of the General Staff Valery Gerasimov, working in partnership with the US XVIII Airborne Corps under Christopher Donahue and a Task Force Dragon staffed by civilian technicians from Palantir alongside American soldiers. King treats this episode carefully — it sits at the constitutional edge of what civilian contractors can lawfully do in an active war — and uses it to make his argument about the military-tech complex concrete. The civilian programmers in that headquarters are not vendors delivering a product; they are functionally part of the kill chain.

A long set-piece chapter on Liverpool’s Covid testing programme during the pandemic serves as King’s analogue for AI-enabled targeting. The same techniques used to identify Hamas operatives or Russian command nodes — fusing wastewater data, mobility data, and self-reporting through algorithmic pattern recognition — were used to direct testing capacity across a city. The point is not the politics of public health but the sociology of the operation: it required a heterogeneous team of epidemiologists, data scientists, military planners, and civilian volunteers to make the algorithm useful, and it broke down where the data was thin or the human collaboration faltered. Targeting in Gaza or Ukraine, King argues, looks more like Liverpool than like a Hollywood depiction of a robot executing a kill list.

On cyber, King takes a deflationary line. He works through Stuxnet, the Russian NotPetya attack of 2017, North Korean operations against Microsoft, and Ukrainian and Russian operations in 2022 and after. AI is being applied to cyber defence and offence, but autonomous cyber war remains an exaggeration. Cyber operations require enormous human expertise to mount and maintain, the effects fade quickly, and they have so far never produced strategic results commensurate with the early predictions of John Arquilla or Mike McConnell. Information operations — bots, deepfakes, the Cambridge Analytica playbook, the Armenian-diaspora campaigns during the Nagorno-Karabakh wars, the Ukrainian use of Volodymyr Zelensky’s image — receive similar treatment. They matter, but they have not replaced kinetic war.

The chapter on the human-machine team is where King is most pointed against the rest of the field. The centaur metaphor, borrowed from advanced chess, has done a lot of damage, he argues, by suggesting an even partnership between human and machine. The reality is closer to what he calls a fetishism: the AI gets the credit for work that an elaborate, mostly invisible human apparatus is doing. The brittleness of AI in real conditions — the AlphaDogfight trials are dissected here, with all the ways the simulated environment was rigged in the algorithm’s favour — means that human operators must constantly maintain, correct, and interpret it. Far from reducing the demand for skilled personnel, AI is increasing it, and the people the system most depends on are often civilians on the payroll of private firms.

Reception within the field has tended to read King’s book as the empirical counterweight to a literature that had grown speculative. Paul Scharre’s Army of None covers the policy and doctrine end and is more sanguine about autonomy; Mariarosaria Taddeo’s work on the ethics of AI in defence handles the normative ground; Ben Buchanan and Andrew Imbrie’s The New Fire is closer in subject matter but more bullish about transformation. King is more sceptical than any of them, and his sociological training shows: he is interested in careers, training, unit culture, contracting cycles, and the slow social work of building trust between operators and the systems they are handed. Critics have pushed back on the geographic narrowness — China and Russia are largely treated through their effects on Western planning rather than on their own terms — and on a certain conservatism about what near-future systems may yet do. The book was finished before the full implications of large-scale agentic AI in 2024 and 2025 had become clear, and some of its caution about generative models in planning may already look dated. The Gospel and Lavender material, conversely, has only become more relevant as reporting on the Gaza campaign has expanded.

For a reader trying to make sense of AI in war today, King is a corrective to two opposite errors. He pulls back from the science-fiction reading in which strategy and combat are about to be handed over to algorithms; he also pulls back from the reassuring industry line that everything important still has a human in the loop. Both, in his account, miss the actual transformation, which is the quiet integration of private-sector software firms into the operational core of Western militaries, and the political and legal questions that integration raises about who is fighting and on whose authority. The book pairs well with Scharre on policy and with the journalism around Palantir’s Ukraine and Gaza work; it does not try to be a manual on the underlying technology, and readers wanting depth on transformer architectures or autonomous swarm coordination will need to look elsewhere.

What is likely to age well in AI, Automation, and War is the framing — the insistence that the interesting story is organisational and sociological, the warning that a new kind of complex is forming around defence software, and the discipline of working from interviews and operational evidence rather than from manifestos. What may date faster is some of the technical caution: King wrote at a moment when the limits of large language models were more obvious than their trajectory, and the next few years of agentic systems and battlefield autonomy will test his Humean reluctance to predict. The deeper bet of the book — that the friction in adopting AI is human and institutional, and that the consequences for civil-military relations are at least as significant as the consequences for the battlefield — looks likely to hold.