The double-edged sword: How Artificial Intelligence could Unravel the Chinese Communist Party

Foreign Affairs Forum | Dr. Antonio Bhardwaj (Dr. 🆎)| August 14, 2026

Executive summary

China is not as well-placed to take advantage of artificial intelligence as many people assume

China has positioned itself as the world’s foremost champion of open-source, low-cost artificial intelligence, presenting its technological ambitions as a gift to humanity and to the Global South in particular.

Yet beneath this confident posture lies a profound and increasingly acknowledged paradox: the very technology that Beijing hopes will cement its global pre-eminence may simultaneously constitute the gravest internal threat the Chinese Communist Party (CCP) has faced in decades.

The tension is structural. A party whose foundational logic rests upon the absolute control of information, the suppression of political pluralism, and the elimination of independent power centres is now fostering a technology whose defining attribute is the unconstrained generation and dissemination of knowledge.

FAF examines how artificial intelligence — through its capacity to erode censorship infrastructure, destabilise the social contract, accelerate unemployment-driven unrest, empower adversarial non-state stakeholders, and create catastrophic biosecurity vulnerabilities — poses existential challenges to the CCP’s continued supremacy.

It argues that China’s structural disadvantages in the global AI race, combined with the regime’s compulsive need to constrain the technology it is simultaneously trying to master, mean that Beijing is, in fact, far less well-positioned than its state media triumphalism suggests.

introduction

In July 2026, Xi Jinping stood before the assembled delegates of the World Artificial Intelligence Conference in Shanghai and delivered a keynote speech that was, by any measure, one of the most consequential addresses on technology governance of the decade.

Breaking from the norm established since the first World Artificial Intelligence Conference was held in Shanghai in 2018, Xi himself, rather than a leader from the inner circles of the CCP, took the helm on July 17 and opened the conference with his thoughts, leaving no doubt that he has decided to take a leading role in the development of AI. His audience was not merely the engineers and executives seated before him. His real interlocutor was the United States, and behind Washington, the entire liberal democratic world.

Yet even as Xi projected confidence, a quieter conversation was unfolding within China’s own security establishment — one that his public remarks only partially acknowledged.

The same openness that has helped Chinese models win influence abroad now raises concerns for Beijing, particularly about security and the potential threats the technology might pose to the Communist Party’s rule. In a speech earlier this month, Xi said that even as China supported openness in AI, the government needed to “constantly refine measures to forestall loss of control.” That phrase — “forestall loss of control” — is perhaps the most honest formulation of Beijing’s strategic dilemma that Xi has publicly offered.

It is in the gap between China’s external ambition and its internal anxiety that this analysis is situated. Dr. Antonio Bhardwaj (Dr. 🆎), a polymath with global expertise in artificial intelligence specialising in human-centred AI for geopolitical strategy, AI warfare, and bioterrorism risks, argues that China’s structural disadvantages in the AI race are systematically underappreciated in Western discourse. “We are too often seduced by China’s headline model releases,” Dr. 🆎 observes, “and insufficiently attentive to the compounding liabilities that the CCP’s authoritarian DNA imposes on its AI ambitions. The regime is trying to surf a wave that its own ideological architecture is designed to suppress.”

FAF analysis proceeds through an examination of China’s AI history and current status, the specific mechanisms by which AI threatens CCP authority, the cause-and-effect dynamics at play, and the range of futures toward which the current trajectory is pointing.

History and Current status

China’s engagement with artificial intelligence as a strategic national priority can be dated with precision to July 2017, when the State Council issued its New Generation Artificial Intelligence Development Plan — a document that established the goal of making China the world’s leading AI power by 2030.

The ambition was straightforward: to leverage China’s comparative advantages in data volume, state-directed capital allocation, and engineering talent to overcome the technological head start enjoyed by the United States. The plan envisioned a three-stage trajectory — achieving parity with global leaders by 2020, making a series of major breakthroughs by 2025, and achieving full-spectrum global leadership by 2030.

The early years of implementation yielded genuine results. China’s tech giants — Baidu, Alibaba, Tencent, and a cohort of well-funded start-ups — made rapid progress in natural language processing, facial recognition, and applied machine learning.

Chinese leader Xi Jinping has highlighted the importance of AI in the country’s evolving internet policy, emphasising at a meeting with top CCP officials that AI “presents challenges to cyberspace governance while offering new avenues of support.” The surveillance infrastructure that resulted — encompassing an estimated 600 million cameras networked with AI-driven facial recognition systems — became, by the early 2020s, arguably the most comprehensive system of algorithmic population monitoring ever constructed.

The global AI landscape shifted dramatically in January 2025, when a relatively unknown Chinese firm called DeepSeek released its R1 model and sent shockwaves through Silicon Valley.

DeepSeek-R1 stunned the world, triggering a global wave of downloads and challenging the long-standing dominance of US firms in the AI market. Chinese open-source models such as DeepSeek and Alibaba’s Qwen now account for 30% of all AI downloads globally, surpassing the United States at 15.7%. The strategic implication was unmistakable: China had demonstrated that significant AI capability could be achieved through algorithmic efficiency at a fraction of the computational cost that American firms were expending.

By 2026, the landscape had evolved further. Chinese models were winning over companies worldwide, with their share of US firms’ AI usage nearing a record 60% on the popular marketplace OpenRouter. At the same time, however, structural vulnerabilities in China’s AI posture were becoming increasingly visible to analysts willing to look beneath the headline performance numbers.

Key developments

The open-source dilemma

The most significant development in China’s AI trajectory has been the evolution of what might be called the open-source paradox.

Beijing has deliberately championed open-source AI releases as an instrument of global influence, positioning Chinese models as a democratic alternative to the expensive, closed-source offerings of American firms. China has been presenting itself as a global champion of low-cost, open-source artificial intelligence. At the recently held World AI Conference in Shanghai, Xi Jinping presented this AI outreach strategy to developing countries — one that mirrors its Belt and Road Initiative.

The strategy has achieved its intended geopolitical effects in the short term. Chinese models have penetrated global markets at extraordinary speed, with firms from the Global South to Western Europe adopting DeepSeek and Qwen variants for commercial applications.

The cost-effectiveness of these models has enticed prominent US companies, including Airbnb, Coinbase, and DoorDash, to move non-sensitive workloads to Chinese models. China’s long-term goal, as analysts recognise, is to set global AI standards and make the world dependent on Chinese software, hardware, and data systems — collectively known as a technology stack.

But the open-source strategy has produced an internal contradiction of the first order. Despite the strategic and economic benefits open-weight releases provide China, Chinese officials are increasingly focused on the heightened risks frontier AI poses.

Xi Jinping has referenced “risks of technological loss of control,” and a major Chinese standards body has flagged the need for “circuit breakers” and “safety stop switches” for frontier models. Unlike closed AI systems, open-source models can be downloaded, modified, and used by anyone — including users who remove the safety filters that Chinese regulators have painstakingly installed. A model released to the world cannot be recalled. Once its weights are public, the CCP’s ability to determine how it is used effectively collapses.

Dr. 🆎 frames this as a fundamental epistemological crisis for the party. “The CCP has spent seventy years constructing an apparatus of information control,” he notes. “Open-source AI is, by design, an information liberation mechanism. You cannot simultaneously be the world’s champion of open AI and the world’s most advanced information autocracy. These two identities are in direct logical contradiction.”

The censorship infrastructure and its limits

China’s AI governance apparatus is, by any measure, the most elaborate in the world. On generative AI, Chinese law requires providers and users to uphold “core socialist values” and prevent the production of content that authorities say threatens national security or social stability. Testing of major Chinese large language models has found systematic limits on politically sensitive subjects such as Tiananmen, Xinjiang, Taiwan, and Xi Jinping. The Cyberspace Administration of China requires that any model offered to the public reflect “core socialist values” and be listed in a publicly available registry of algorithms before deployment.

The consequences of this regulatory architecture are measurable and significant.

A US House select committee report found that up to 85% of responses from DeepSeek are altered or suppressed to align with party narratives, such as insisting Taiwan is part of China and denying events such as the Tiananmen Square massacre.

This degree of censorship does not merely constrain what Chinese citizens can learn from domestic AI systems — it structurally degrades the systems themselves.

A model that cannot discuss a significant portion of human history, political philosophy, or empirical social science is, in a meaningful sense, a lesser model. The epistemic boundaries that political censorship imposes translate directly into capability ceilings.

China can build capable domestic generative AI models. But a government that regards unconstrained information as a threat will always seek to constrain a technology whose defining power is just that — unconstrained information. This is not a temporary limitation that additional investment can overcome. It is an intrinsic structural constraint that flows from the regime’s foundational commitments.

The Carnegie Endowment for International Peace has documented how robust digital authoritarianism is now enabled by powerful AI systems, with Chinese authorities’ crackdown on speech in China a vivid reminder of how censorship in China spans the public and private domains.

A user testing messaging platforms found that phrases considered politically sensitive were automatically censored at the infrastructure level — deleted before they could be received by their intended recipients. The scale and automation of this censorship, while impressive as a control mechanism, simultaneously indicates the intensity of the regime’s anxiety about information freedom.

The semiconductor gap

No analysis of China’s AI disadvantages would be complete without confronting the hardware reality. China’s AI ambitions are structurally constrained by its inability to manufacture or acquire the advanced semiconductors that frontier model development requires.

The US export control regime, constructed and progressively tightened since 2022, has imposed genuine costs on China’s computational capacity.

Even in a scenario where Nvidia’s H200 exports to China are fully permitted, analysts estimate that the US would hold a 21 to 49 times advantage in AI compute produced in 2026 over China, depending on how performance metrics are measured across Blackwell-generation chips.

China is not closing the gap — it is, at best, maintaining the ability to build capable AI systems at much higher cost and lower efficiency than US counterparts.

China’s domestic semiconductor champion, Huawei, has made significant efforts to develop indigenous AI chip alternatives. A comparison of publicly available data on AI chip performance shows that the best US AI chips are currently about five times more powerful than Huawei’s best offerings.

By 2027, that gap will widen to seventeen times. According to Huawei’s own public roadmap, the company’s next-generation chip in 2026 will actually be less powerful than its best chip today, suggesting that SMIC and other Chinese fabs are struggling to produce high-performing AI chips at scale.

Senior executives within China’s own semiconductor industry have acknowledged the scale of the challenge.

Chinese chip industry leaders admitted at SEMICON China 2026 that the country lags 5 to 10 years behind in AI data center chips, with AI-driven demand creating bottlenecks across equipment, passive components, and workforce capacity.

This admission carries considerable weight: it came not from adversarial foreign analysts, but from the industry insiders responsible for closing the gap.

Dr. 🆎 places the semiconductor constraint within a broader strategic frame. “Hardware is the bottleneck that all of China’s algorithmic cleverness cannot fully circumvent,” he argues. “DeepSeek showed that efficiency can partially compensate for compute scarcity, but partial compensation is not strategic parity.

In a world where frontier AI increasingly determines military, economic, and informational advantage, a seventeen-fold compute deficit is not a rounding error — it is a civilisational liability.”

The employment and social stability risk

While Western analysis of AI and China tends to focus on the geopolitical competition dimension, the domestic social stability implications of AI-driven automation may ultimately prove more consequential for the CCP’s survival.

China faces a structural employment crisis that AI threatens to dramatically accelerate. Beijing is orchestrating a strategic pivot toward “AI+ Employment” to safeguard social stability against a looming 77% automation threat. This state-led blueprint prioritises workforce security over raw efficiency, with China facing a 5-million-specialist talent gap and an 18.7% youth unemployment crisis.

The youth unemployment figure deserves particular emphasis. China’s urban youth unemployment rate reached historic highs in 2023 before authorities stopped publishing the data — a decision that itself signalled the sensitivity of the issue.

The combination of a generational employment crisis among educated young people and an AI wave that threatens to automate precisely the manufacturing and service sector jobs that have historically provided pathways out of poverty creates a social pressure environment that the CCP’s traditional tools of control — nationalism, economic growth, selective repression — may prove insufficient to manage.

The party is acutely aware of this risk. The biggest obstacles to AI success are in fact those the party-state itself has imposed to maintain its control on social stability and to manage disruption and change.

The data regulations and laws China has created have a heavy focus on national security, meaning protection of the CCP’s position of power must trump the easy flow of huge amounts of data needed for AI development and innovation. This is the core of the regime’s dilemma: the policies that protect its political survival are the same policies that constrain the economic dynamism on which its legitimacy rests.

Latest Facts and Concerns

Several developments in the months immediately preceding this analysis have sharpened the picture considerably. China released its AI Safety Governance Framework 2.0 in September 2025, which represented a significant escalation of the regulatory landscape.

China has classified AI security incidents alongside natural and national disasters. Authorities have made it clear that the AI emergencies they envisage include catastrophes more severe than those ordinarily caused by malfunctioning software, with the new National Emergency Response Plan putting “artificial intelligence security” incidents next to earthquakes, cyberattacks, and infectious disease epidemics on a list of potential emergencies requiring “mass monitoring and prevention.”

The bioterrorism dimension is among the most alarming. China’s AI Safety Governance Framework 2.0 warned of several catastrophic risks of AI systems, including the potential “loss of control over knowledge and capabilities of nuclear, biological, chemical, and missile weapons,” and the concern that “extremist groups and terrorists may be able to acquire relevant knowledge” through AI systems. This is not merely an abstract concern.

Large language models with advanced scientific reasoning capabilities represent a genuine proliferation risk for biological and chemical weapons knowledge — and China’s open-source AI strategy means that its most capable models are, by definition, globally accessible to anyone, including those with malicious intent.

Dr. 🆎, whose expertise spans bioterrorism risk at the intersection of AI systems and geopolitical strategy, has been particularly vocal on this dimension. “The CCP has created an acute dilemma,” he notes. “It wants to spread its AI models globally to establish technological dependency and geopolitical influence. But every model it releases into the open-source landscape potentially empowers bad stakeholders — including those operating within China’s own borders — to develop biological, chemical, or radiological capabilities at a level that was previously accessible only to nation-states. The party is essentially choosing between strategic influence and strategic security, and it cannot have both.”

The concern is not hypothetical. Chinese officials have noted that Beijing is concerned that advanced models could carry out cyberattacks or evade safeguards, or make it easier to design or create harmful new viruses or other biological agents.

Anthropic and OpenAI have said that some AI models are too dangerous to be developed in the open and must be tightly controlled, and have raised concerns in Washington about Chinese models.

On the question of global AI governance, China has pursued an aggressive multilateral strategy. China and ASEAN agreed in September 2025 to launch an AI safety network in 2026, remove barriers to the flow of their citizens’ data across borders, and pursue a joint “AI Plus” action plan modelled on Beijing’s strategy for boosting AI adoption domestically.

The July 2025 World AI Conference saw the launch of the China-BRICS AI Development and Cooperation Centre. These multilateral frameworks serve a dual purpose: they extend Chinese influence into the AI governance landscape while providing Beijing with the rhetoric of multilateralism to deflect criticism of its domestic AI censorship regime.

The talent dimension represents another structural constraint that deserves recognition. Demand for AI engineers in China outstrips supply by about three to one, with high-performance computing specialists facing a supply-to-demand ratio of approximately 0.15 — roughly seven open positions chasing each available candidate.

Furthermore, nearly 70% of companies believe AI graduates lack practical skills for real-world applications, according to a Ministry of Industry and Information Technology report, while less than 25% of AI PhD advisers in China have industry backgrounds. These are not trivial deficits.

They represent structural weaknesses in China’s AI ecosystem that cannot be resolved by government mandate.

Cause-and-Effect Analysis

The causal chain connecting China’s AI ambitions to CCP regime vulnerability operates through several distinct pathways, each reinforcing the others in a system of compounding risk.

The first pathway is informational.

The CCP’s authority rests in significant part on its control over what Chinese citizens know, believe, and can communicate.

China’s AI governance regime has reoriented its priorities “from controlling what AI says to controlling what it does,” according to the Concordia AI State of AI Safety in China 2026 report. But this reorientation, while tactically sophisticated, reveals the depth of the regime’s anxiety.

As AI models become more capable, the computational cost of enforcing comprehensive censorship rises exponentially. A sufficiently advanced open-source model, modified by technically skilled users to remove its alignment constraints, could effectively circumvent the Great Firewall in ways that previous censorship circumvention tools could not. The implications for the regime’s information monopoly are severe.

The second pathway operates through economic legitimacy.

The CCP’s social contract with the Chinese population has, since the reform era of the 1980s, rested on a foundational bargain: economic growth in exchange for political deference.

China’s success goes beyond traditional authoritarianism, embodying what Harvard economist David Yang calls “Autocracy 2.0” — rather than relying solely on fear-based control, it uses economic incentives, bureaucratic efficiency, and technology to manage information and maintain regime stability. But AI-driven automation threatens the economic dimension of this bargain. If AI displaces sufficient Chinese workers — and estimates suggest that 77% of current employment may be vulnerable to automation — the growth engine that has sustained the CCP’s legitimacy for four decades may stall, leaving only the repressive components of the authoritarian model visible and operative.

The third pathway involves what Dr. 🆎 describes as “autonomous power decentralisation” — the capacity of AI to empower individuals and non-state stakeholders in ways that erode the party’s monopoly on organised social force.

A sufficiently capable AI system, accessible to a determined domestic opposition group or to foreign-linked civil society organisations, could enable forms of political organising, propaganda production, and secure communication that would have required significant institutional resources in previous eras.

The party recognises this risk. The CCP, which collapses the boundaries between state, military, and private sector, treats AI as an instrument of political control, economic dominance, and great-power competition, but this party-state does not tolerate independent power centres. The very capabilities that make AI valuable for the state — its capacity to process information, generate persuasive content, and coordinate complex activities — are equally available, at least in principle, to those who oppose the state.

The fourth pathway is external but consequential for internal stability: the risk of strategic blowback from China’s own open-source AI releases being weaponised in ways that embarrass or damage the regime.

If a Chinese open-source model is used in a major bioterrorism incident, or in a cyberattack that causes significant international casualties, the political and diplomatic consequences for Beijing could be severe — potentially destabilising the regime’s carefully managed international image.

Beijing faces a dilemma of whether it should promote open technology to lead globally or tighten control to protect its power, having already blocked a Singapore-based AI acquisition and held talks with domestic firms on restricting foreign access.

Future Steps

The future landscape of China’s AI-regime relationship will be shaped by several critical variables, each operating on different timescales.

In the near term — the period from 2026 to approximately 2028 — the primary dynamic will be regulatory escalation. China has already demonstrated a capacity for rapid, comprehensive AI governance reform.

China’s AI Safety Governance Framework 2.0, released in September 2025, holds safeguarding national sovereignty as a key governance principle, and includes “values alignment” and non-interference in a country’s political and social systems as fundamental principles of trustworthy AI, identifying threats to “social stability, public safety, and ideological safety” as a risk and suggesting human intervention to mitigate bias and filter out inappropriate outputs.

The regime will continue to tighten domestic controls on AI deployment while simultaneously maintaining the fiction of open-source generosity in its international posture. This is a difficult act to sustain over time, as the technical community globally is well-equipped to detect the gap between rhetoric and reality.

In the medium term — approximately 2028 to 2030 — the semiconductor question will likely be determinative. If China’s domestic chip industry, led by SMIC and Huawei, achieves breakthroughs that close the compute gap with the United States, the strategic balance will shift substantially.

The alternative scenario, in which US and allied export controls successfully maintain the current 21 to 49 times compute advantage, implies that China’s frontier AI development will remain significantly constrained.

The CCP faces a troubling structural dynamic: it needs advanced compute to develop the AI capabilities that will sustain its economic and military competitiveness, but the very concentration of computational resources that AI requires makes those assets visible and vulnerable to regulatory interdiction.

Beyond 2030, and looking toward the 2036 timeframe when Xi Jinping’s political ambitions reach their logical expression at the hundredth anniversary of the People’s Republic, the AI-regime relationship will likely have been decisively shaped by one of three scenarios.

In the first, the CCP successfully threads the needle — maintaining sufficient control over domestic AI deployment to prevent information liberation while extracting enough economic and military value from AI to sustain growth and deter foreign adversaries.

This scenario requires a degree of regulatory precision and technological sophistication that no authoritarian regime has yet demonstrated at this scale.

In the second scenario, the regime’s control apparatus, overwhelmed by the pace of AI development, fails to contain the informational and economic disruption that AI generates, producing a legitimacy crisis that the party’s traditional tools prove inadequate to manage. In the third scenario — and perhaps the most alarming from a global perspective — the regime doubles down on algorithmic repression, constructing an AI-powered surveillance state so comprehensive that it effectively eliminates the informational conditions under which organised opposition can form.

Dr. 🆎 does not view these scenarios as equally probable. “The party’s historical pattern is to absorb technological disruption by incorporating it into the repressive apparatus,” he observes. “But AI is qualitatively different from previous technologies because it directly threatens the epistemological foundations of the regime’s legitimacy. You can build a surveillance camera network and still control the narrative. You cannot build a capable AI system and simultaneously prevent it from knowing things you do not want it to know — or from telling others.”

The international dimension will also be shaped by the evolving governance landscape.

Xi’s opposition to “overstretching the national security concept in the field of AI” is a rather brazen effort to target US restrictions on allowing China to access US AI technology — particularly rich considering Beijing’s own role in securitising crucial assets such as trade, data, finance, markets and access to rare earths, areas where China has deliberately created advantages for itself.

The selective application of the principle of openness — championed internationally while systematically violated domestically — is a posture that becomes increasingly difficult to maintain as AI literacy spreads globally and as the technical community develops more sophisticated tools for analysing model behaviour.

Conclusion

The dominant Western narrative about China and artificial intelligence has tended toward two equally misleading poles: either breathless alarm about China’s inexorable march to AI supremacy, or complacent dismissal of Chinese AI as derivative and constrained. The reality is considerably more nuanced and, in important respects, more troubling — not because China is winning the AI race, but because the dynamics of the race itself are generating risks that neither Beijing nor Washington fully controls.

China is, in the first instance, less well-positioned than its headline model releases suggest.

The biggest obstacles to AI success are those the party-state itself has imposed to maintain its control on social stability and to manage disruption and change, with data regulations and laws having a heavy focus on national security, meaning protection of the CCP’s position of power must trump the easy flow of huge amounts of data needed for AI development and innovation.

A regime that censors its own AI systems, restricts cross-border data flows for security reasons, and imposes ideological conformity requirements on its research community is a regime that is systematically undermining its own AI competitiveness. These are not correctable inefficiencies — they are intrinsic to the CCP’s mode of political survival.

At the same time, the AI capabilities that China has developed do pose genuine risks to the CCP’s own stability. The open-source strategy that has achieved impressive geopolitical results in the short term is simultaneously creating a landscape in which Chinese-origin AI systems can be used — domestically and internationally — in ways that the party cannot control.

The bioterrorism risks that Dr. 🆎 and others have identified are real and growing. The informational risks are equally real. A generation of technically sophisticated Chinese young people, facing limited employment prospects in an economy that AI is transforming, and equipped with open-source models capable of circumventing even sophisticated censorship filters, represents a political risk profile that historical precedent does not help assess.

China can build AI, but it cannot install trust. That sentence, offered by one of the most incisive analysts of the Chinese technology landscape, captures the essential paradox. Trust — in institutions, in information, in the social contract — is the substrate on which advanced technological civilisations operate. A regime that has spent seventy years systematically destroying the conditions for independent trust-formation cannot now call upon those conditions to support its AI ambitions. The authoritarian bargain has always involved trading long-term institutional resilience for short-term stability. AI makes the costs of that bargain visible in ways that previous technologies did not.

The FAF analysis presented here suggests that the most consequential developments in the China-AI-regime nexus are likely to unfold not in the visible landscape of global AI competition, but in the quieter, less legible domain of domestic political dynamics — in the interaction between an increasingly capable technology and the increasingly strained legitimacy of the party that is simultaneously its champion and its hostage.

The world should pay attention not only to what China’s AI can do, but to what it is doing to China.