Mass Autonomy and the Next Grammar of Power
Part II — China’s “intelligentized” trajectory vs. U.S. carrier-era doctrine, and the strategic implications of AI and drone swarms
Part II — China’s “intelligentized” trajectory vs. U.S. carrier-era doctrine, and the strategic implications of AI and drone swarms
Keywords: AI; autonomy; drone swarms; aircraft carriers; distributed operations; PLA strategy; U.S. Indo-Pacific doctrine; semiconductors; compute; logistics; command-and-control
Executive Summary
AI-enabled autonomy is rewriting great-power competition: China is organizing industry, doctrine, and C2 for cheap, scalable drone swarms, while the U.S.—still committed to scarce, expensive platforms—risks a transition shock analogous to Britain’s shift from coal to oil. This essay extends the Britain “coal→oil” framework into the AI era, arguing that the winning power will be the one whose whole system (industry, logistics, doctrine, and training) can operationalize autonomy at scale. Beijing’s official policies and military writings emphasize an “intelligentized” force and whole-of-nation AI development, whereas U.S. strategy is only belatedly adapting (Replicator, autonomy directives) around legacy naval platforms (China’s State Council, 2017; Department of Defense, 2025). Nine dimensions are examined: doctrine and force structure; industrial/manufacturing scale; compute and data access; software ecosystems; logistics/supply chains; command-and-control; cost-per-unit; countermeasures; and institutional adaptation. Primary and official sources (DoD strategy, China defense white papers, Congressional testimony) and major analyses (RAND, CSIS, CNAS, NDU) are used. Two tables compare U.S. vs China key metrics and map 19th-century naval variables to AI-era counterparts. Images are suggested to illustrate concepts and geography. Policy implications include treating compute and chip supply as strategic logistics, building U.S.–allied production networks for drones, and modernizing doctrine and defenses for swarm conflict.
The Britain coal→oil analogy and its relevance
Britain’s 19th-century dominance rested on a maritime system tuned to sail, coal, and steam (ports, coaling stations, shipbuilding, doctrine). Churchill’s 1913 remarks encapsulate the lesson: oil freed ships from coal but made them dependent on foreign fields and tankers—“safety and certainty in oil lie in variety” of sources and routes (Churchill, 1913). The U.S./China AI competition has a similar logic. In place of “fuel logistics” are compute and data logistics: how to field massive compute clusters, data pipelines, and software for autonomy. China’s leaders recognize this. PLA Strategic Support Force doctrine and national AI plans emphasize building an “intelligent” military using big data, cloud, and AI, and treating data and chips as strategic resources (China’s State Council, 2017; Department of Defense, 2025; National Institute for Defense Studies, 2022).
The core claim is that China is aligning structure around mass autonomy—industrial capacity, military-civil fusion, AI infrastructure—while the U.S. retains much of its Cold-War, platform-centric force structure: 11 nuclear carriers, air wings, and global deployments, and is only partially retooling. This mismatch could create strategic vulnerabilities unless the U.S. accelerates adaptation. The coal→oil case showed that even an early mover like Britain still had to re-architect its empire and navy for oil, with major strategic consequences (Churchill, 1913; Crafts, 2020).
Figure 1: The carrier symbolizes traditional concentrated power, the drones symbolize cheap, scalable autonomy.
Structural alignments: doctrine, force structure, and industrial base
U.S. posture and doctrine. The U.S. Navy’s force structure is officially anchored in carriers. A Congressional Research Service report notes the Navy has 11 operational nuclear carriers and by law must maintain at least 11. The 2020 tri-service Advantage at Sea maritime strategy affirms that carriers remain central but calls for “new platforms…new thinking…and new technologies” to enable distributed naval operations against adversary surveillance (Congressional Research Service, 2025; Royal Navy et al., 2020). The 2022 National Defense Strategy explicitly labels China as the “pacing challenge,” mandating urgent modernization but not prescribing precise force trade-offs (Department of Defense, 2022). In practice, U.S. naval doctrine is evolving—Distributed Maritime Operations, JADC2 connectivity, unmanned experimentation—but large platforms are still heavily funded and not scheduled for replacement anytime soon.
China’s posture and doctrine. China’s defense white papers and official speeches describe an “intelligentized” military. The 2019 White Paper urges speeding up the development of intelligent military capabilities (China’s State Council Information Office, 2019). PLA writings envision future wars as integrated cyber-physical conflicts, a mix of informationized and “intelligentized” warfare (National Institute for Defense Studies, 2022). Concretely, China is rapidly expanding its fleet and A2/AD forces. The Department of Defense assesses China now has two carriers, with a third in sea trials, and intends substantial additional expansion. At the same time, China is investing heavily in drones and missiles. It projects power via land-based ballistic and cruise missiles and is experimenting with swarms of smaller UAVs for surveillance and attack (Department of Defense, 2025).
Table 1: Comparison of U.S. and China on key strategic dimensions (sources cited in text). ([primary]: official sources; others are analyses)
Compute, data, and the “new fuel”
In the coal→oil analogy, coal was the homegrown resource and oil was mostly foreign. Here, the “fuel” is compute cycles and data.
China’s vulnerability is stark. The Department of Defense’s 2025 China report states that China’s AI development is constrained by limited access to high-performance AI accelerators, forcing strategies like stockpiling, sourcing through loopholes, and investing in domestic chip fabrication (Department of Defense, 2025). In other words, China treats advanced semiconductors as a strategic chokepoint, akin to how Britain treated oil fields. Stanford’s AI Index and publicly visible compute benchmarks indicate that Chinese firms possess fewer of the world’s most capable publicly visible AI and HPC systems than the United States and some of its allies. While raw figures for AI training capacity are proprietary, a useful proxy is high-performance computing: the November 2025 TOP500 list shows multiple U.S. exascale systems at the frontier (TOP500, 2025).
Figure 2: Public benchmark of leading supercomputers, showing U.S. dominance in exascale-class HPC, a proxy for national compute power.
Semiconductors form another layer. According to the Semiconductor Industry Association, U.S. firms held approximately 50.2% of global semiconductor market share in 2023, though much advanced fabrication remains offshore (Semiconductor Industry Association, 2024). China’s industrial plans target domestic chipmaking, yet China remains heavily dependent on imports and foreign tooling for leading-edge capability (Department of Defense, 2025). The U.S. CHIPS Act and export-control regime show Washington recognizes the strategic nature of semiconductors. In all, compute and chips are a battleground where the U.S. has a current edge and China is aggressively trying to catch up.
Software ecosystems are similarly critical. The U.S. boasts world-leading AI platforms, open-source communities, and private-sector labs. The DoD AI Strategy emphasized scaling successes across the enterprise (Department of Defense, 2018). China, meanwhile, has state-led initiatives: its 2017 AI plan sets targets for AI talent, laboratories, and deployment, while collaboration between the PLA and civilian industry is explicit (China’s State Council, 2017; National Institute for Defense Studies, 2022). The result is that both sides have sophisticated AI ecosystems, but with very different governance structures.
Logistics and production: mass vs scarcity
Production scale. A central lesson from Ukraine is that drone wars turn on production capacity. The Department of Defense’s 2025 memo bluntly states that adversaries collectively produce millions of cheap drones each year, implying an attritional logic of warfare (Department of Defense, 2025). China’s industrial base likely dwarfs the U.S. in sheer drone manufacturing. CNAS reports that China is already positioned to leverage a large fleet of drones, while Taiwan’s plans and Ukraine’s wartime targets show how quickly modern conflict shifts toward industrial drone scale (Center for a New American Security, 2024). The exact numbers are opaque, but the orders of magnitude matter. The U.S. Replicator initiative explicitly targets multiple thousands of attritable systems, a far cry from millions (Department of Defense, 2025).
Figure 3: Illustrative production scale on a logarithmic basis. Orders of magnitude in small UAV production show U.S. goals in the thousands, while Chinese-advantaged plans or adversary-scale production discussions operate in the millions. The chart is illustrative rather than audited.
Supply chains. Coal-era navies built global coaling stations. For drones and autonomy, the analogous supply chains include factories for airframes, motors, sensors, batteries, and chips, plus the broader national AI stack: data centers, fiber networks, cloud infrastructure, and secure software deployment. The DoD notes China is building modular factories and stockpiles while the U.S. is only beginning to rethink its own supply chains for scale (Department of Defense, 2025). Geography matters too. The western Pacific is far from many U.S. industrial nodes, while China’s industrial base sits near the probable theater of conflict.
Warfare economics and counter-swarm defenses
Cheap drones change the cost-exchange calculus. A modern missile or fighter can cost tens of millions; a drone can cost thousands. High numbers can overwhelm missile defenses. RAND highlights that defending against swarms may be prohibitively expensive, because interceptors, radars, and layered systems are themselves costly (Gerstein & Leidy, 2023). The strategic problem is not merely technological; it is financial.
A stylized saturation scenario illustrates the point. Suppose each attacking salvo grows over time while the defender’s interceptor supply shrinks. Eventually, the defender runs dry. At that point, expensive ships or airbases become exposed to cheap attritional attack.
Figure 4: Stylized saturation dynamic. Attacker drone salvos accumulate faster than defender interceptors deplete. Once the defender runs out of interceptors, large platforms become vulnerable. This is conceptual, not a battle simulation.
Countermeasures. The counter to swarms is layered defense: missiles, point defenses, jamming, directed energy, cyber disruption, and autonomous interceptors. But each comes with cost and scaling problems. The U.S. Navy and broader DoD are exploring lasers, EW suites, and improved short-range defenses, while China also fields counter-UAV and electronic warfare systems (Department of Defense, 2025). The future of defense may hinge not on who has the most exquisite platform, but on who can solve the cost problem of intercepting mass.
Institutional adaptation and geopolitical consequences
Strategic competition ultimately plays out at the intersection of technology, economics, and politics. Several cross-cutting insights follow.-
Institutional tempo. China’s whole-of-state innovation model can push rapid adoption once the government commits. The U.S. ecosystem is more decentralized and often more innovative in the long run, but slower to redirect in peacetime. The Pentagon’s own memoranda acknowledge bureaucratic friction and the need to empower units and cut delay (Department of Defense, 2025).
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Alliances and distributed basing. The U.S. relies on allies and partners to offset distance. Effective deterrence will require integrating allied drone production, data sharing, and AI-enabled operations. China, by contrast, may be able to leverage geographic concentration and regional pressure.
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Escalation dynamics. Cheap drones lower the threshold of action. A drone strike can be ambiguous, deniable, and rapid, increasing the danger of miscalculation.
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Economics of war. Just as late 19th-century industrial competition let the U.S. and Germany outpace Britain in productivity and new sectors, future competition may turn on who can outproduce in autonomy.
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Lessons from Ukraine. Recent war shows drones matter on land and sea, and that mass UAVs force even large militaries to adapt. China is surely studying this. The U.S. is studying it too, but study is not the same as systemic adaptation.
In sum, the parallels to Britain’s coal→oil era suggest policymakers should ask a simple question: What are the new nodes of vulnerability, and who controls them? For Britain it was oil. For the United States now it is compute infrastructure, semiconductor resilience, software integration, and mass manufacturing capacity.
Counterarguments and strategic recommendations
Counterarguments. It is important to acknowledge counterpoints. First, the U.S. Navy is not oblivious to autonomy. Distributed Maritime Operations, unmanned experimentation, and JADC2 all show movement. A simple collapse metaphor would overstate the degree of American blindness.
Second, China’s path is not guaranteed. American advantages in innovation, industrial agility, finance, software, undersea warfare, and alliances still matter. China’s centralized model can also produce inefficiency, concealment, and brittle command culture.
Third, multilateral norms, export controls, and coalition capacity may slow or reshape the most extreme forms of autonomous warfare.
Nonetheless, even if neither side “wins” a pure drone war, the strategic environment is shifting. The question is not whether swarms matter, but how fully states incorporate that fact into force design, procurement, and command doctrine.
Policy recommendations. For the U.S. and its allies, the implication is to treat the mass-autonomy shift as a systemic challenge.-
Invest in production capacity. Expand U.S. and allied factories for drones, sensors, chips, batteries, and munitions.
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Secure compute and data. Build military-relevant AI compute, harden power and cloud infrastructure, and protect semiconductor supply chains.
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Normalize attritable systems. Train forces to expect and manage high attrition of cheap autonomous systems.
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Layer defenses wisely. Field cost-effective countermeasures that match swarm threats economically, not merely technically.
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Integrate allies. Build joint standards, procurement pathways, exercises, and production ecosystems across alliances.
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Clarify governance. Develop clear legal and operational rules for autonomous systems to reduce escalation risk.
Timeline of key milestones
2017 Aug. 8 — China publishes its New Generation Artificial Intelligence Development Plan (China’s State Council, 2017).
2019 Jul. 24 — China’s defense white paper calls for “intelligentized” military modernization (China’s State Council Information Office, 2019).
2020 Dec. — U.S. releases Advantage at Sea tri-service maritime strategy (Royal Navy et al., 2020).
2022 Oct. 27 — U.S. releases new National Defense Strategy, naming China as the top pacing challenge (Department of Defense, 2022).
2023 — U.S. leadership launches the Replicator initiative for attritable autonomy (Department of Defense, 2025).
2025 Jul. 10 — DoD memorandum on military drone dominance emphasizes that this is a process race as much as a technological race (Department of Defense, 2025).
2025 Dec. 23 — U.S. DoD publishes the 2025 China Military Power Report, stressing intelligentized warfare and Chinese adaptation (Department of Defense, 2025).
2026 Mar. 26 — Chinese media report an Atlas drone-swarm demonstration involving one operator controlling 96 drones (CGTN, 2026).
Figure 5. Timeline of illustrative milestones in U.S.–China AI and autonomy strategies, 2017–2026.
References
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Center for Strategic and International Studies. (2023). The first battle of the next war: Wargaming a Chinese invasion of Taiwan. https://csis-website-prod.s3.amazonaws.com/s3fs-public/publication/230109_Cancian_FirstBattle_NextWar.pdf
CGTN. (2026, March 26). China’s Atlas drone swarm completes full-process demo. https://news.cgtn.com/news/2026-03-26/China-s-Atlas-drone-swarm-completes-full-process-demo-1LPiA7M9Gz6/p.html
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Note: Figures and tables are illustrative based on open-source reports and expert analysis. Some data, especially drone production and AI-chip access, remain estimates or inferred from official statements and industry reporting.