Since 2025, India’s long-standing confidence in its IT industry has been shaken by two symbolic setbacks. The first was the emergence of DeepSeek, a globally influential open-source AI platform originating in China rather than India, prompting soul-searching in a country long celebrated for its software prowess. The second was Tata Consultancy Services’ announcement of its largest-ever layoffs—12,000 mid- to senior-level positions—raising concerns that structural weaknesses, rather than cyclical downturns, are weighing on the sector. Together, these events highlight the vulnerability of an industry built predominantly on a labor-intensive, contract-manufacturing model that has become deeply path-dependent and innovation-constrained.
This predicament contrasts sharply with China’s internet and technology sector, which evolved from a late-starting follower into a co-runner and, in some domains, a global leader. India’s IT services model, like contract manufacturing in hardware, faces an inherent contradiction: once firms succeed as trusted outsourcers, developing proprietary products risks alienating clients who fear the loss of intellectual property and competitive advantage. China’s success, by contrast, reflects a broader set of systemic capabilities—advanced infrastructure, scenario-driven innovation, ecosystem-level collaboration, and state-backed resilience—that together enabled sustained upgrading. This divergence offers a revealing lens through which to understand not only India’s current challenges, but also the deeper dynamics shaping technological competition in the emerging Sino-U.S. rivalry.
Beyond OEM: Building Product, Platform, and Ecosystem Sovereignty
Rejecting pure OEM dependence is not a tactical adjustment but a strategic choice that determines whether firms—and nations—can climb the technology value chain. OEM-centered growth offers early scale and cash flow, yet it embeds structural limitations: value is captured upstream, learning is constrained to execution, and long-term competitiveness is forfeited. By contrast, a development path anchored in productization from the outset enables control over user experience, data flows, and iteration cycles, laying the foundation for platform formation and, ultimately, ecosystem leadership.
Different starting points help explain divergent outcomes. India’s IT industry emerged from Y2K remediation and enterprise outsourcing, naturally locking into a labor-arbitrage, per-hour delivery model. China’s internet industry, by contrast, grew out of localized consumer needs—portals, instant messaging, search, and e-commerce—driving early product-level innovation. Even when initial models were imitative, Chinese firms rapidly adapted them to local scenarios, iterated aggressively, and internalized core capabilities. This product-first logic proved decisive: it created feedback loops that enabled scale, data accumulation, and continuous innovation.
The contrast is further illustrated by the Huawei-style approach. Although Huawei undertook OEM contracts, it never treated OEM as a strategic anchor. By insisting on owning core technologies—protocol stacks, chips, and operating systems—it avoided dependence on system integration margins and preserved strategic autonomy. Similar instincts characterize leading Chinese internet firms, which were willing to absorb early losses to master interfaces, data, and interaction loops. Conversely, OEM-centric IT firms such as Neusoft and Pactera struggled to evolve into global platforms, underscoring the inherent tension between OEM dependence and independent brand or platform development.
What China broadly did right was to compress a three-stage leap—from productization to platformization to ecosystem building—often in parallel rather than sequentially. Firms such as BAT, ByteDance, Pinduoduo, and Shein avoided deep entanglement in multinational outsourcing systems, thereby escaping path dependence. Even hardware-oriented companies pursued “technology backup” strategies alongside OEM work, eventually breaking through with independent products. National policies reinforced this trajectory by encouraging upgrades from “usable” to “easy to use,” and ultimately to “globally competitive,” accelerating the transition from execution to leadership.
In the context of Sino–U.S. competition, the lesson is stark. OEM security is an illusion; ecosystem sovereignty is real security. Control over products and platforms defines who can withstand supply disruptions, sanctions, or AI-driven substitution. A country that exports only labor remains exposed, while one that builds domestic platforms and ecosystems gains strategic buffer space and genuine choice. The core issue is not openness versus closure, but whether openness is voluntary and reversible. China’s experience demonstrates that cooperation and autonomy can coexist, whereas pure OEM dependence locks participants into one-way vulnerability with diminishing strategic options.
Engineering Innovation Through Real-World Scale and Complexity
China’s internet and AI development has followed a distinctive path: using massive, highly complex local scenarios as a proving ground for continuous engineering iteration. Rather than treating technology development as an abstract or laboratory-first exercise, Chinese firms have embedded innovation directly into dense, high-frequency real-world environments. A unified digital market serving more than a billion users, combined with essential daily-use scenarios such as payments, logistics, mobility, and social interaction, has generated an unparalleled volume of behavioral data. This data has functioned as a new means of production—fueling rapid feedback loops that translate directly into product refinement and system optimization.
The effectiveness of this model rests on three structural conditions. First, China’s relatively integrated digital ecosystem enables data to circulate seamlessly across platforms and services. Second, high-frequency, mission-critical use cases—mobile payments, food delivery, ride-hailing, and government services—ensure constant stress-testing of systems under real constraints. Third, a regulatory approach that has historically allowed experimentation before formal rulemaking created space for trial, error, and fast iteration. Together, these conditions enabled companies to convert scale and complexity into a sustained engineering advantage.
By contrast, India’s IT sector has largely exported labor and services rather than cultivating domestic data assets. Fragmented languages, lower levels of digitization, and delayed payment infrastructure have limited the formation of closed-loop, high-value data ecosystems. Even rapid mobile internet adoption did not translate into deeply integrated, data-driven platforms comparable to China’s super-apps or algorithmic content systems. Similarly, Indian IT firms have typically operated as intermediaries for Western clients, translating external demands rather than defining and owning end-user scenarios, which constrained their ability to develop scenario-driven intelligence.
China’s success lies in allowing real-world complexity to shape technology itself. Extreme peak loads in mobile payments forced breakthroughs in risk control and high-concurrency systems; social features such as digital gifting accelerated advances in distributed architectures; short-video platforms drove real-time recommendation engines and end-to-cloud coordination; and community group buying refined last-mile logistics and digital scheduling. These environments were often more demanding than those in mature Western markets, compelling firms to compensate for gaps in foundational theory with superior engineering execution.
As a result, competition—particularly between China and the United States—has shifted from a narrow focus on model size to a broader contest over implementation efficiency and cost control. China’s experience in compressing models, deploying edge inference, and integrating AI into hybrid cloud systems reflects capabilities forged under relentless real-world pressure. Ultimately, the decisive factor in future technological leadership may not be laboratory breakthroughs alone, but the ability to embed intelligence deeply into everyday economic and social activity. In this respect, mastery of large-scale, complex scenarios has become a strategic asset—and one of China’s most enduring strengths.
Infrastructure First: How State Leadership Built China’s Three-Layer Digital Foundation
China’s digital rise has been anchored not primarily in isolated entrepreneurial breakthroughs, but in an infrastructure-first strategy in which the state led the systematic construction of a three-layer digital foundation: connectivity, computing power, and data. Physical infrastructure—broadband penetration into rural areas, nationwide 4G/5G coverage, high-speed rail, and dense logistics networks—was treated as a form of operating-system support for the digital economy. These investments enabled platform-scale applications to diffuse rapidly and uniformly: e-commerce required high-density logistics to reach county-level markets; short video platforms depended on low-latency national networks; and public digital services such as health codes and travel credentials relied on unified identity authentication to achieve instant nationwide rollout.
This foundation was reinforced by a policy toolkit designed to balance competition with coordination. In consumer-facing sectors such as digital payments, navigation, and ride-hailing, regulators adopted a “horse-racing” approach—allowing multiple firms to compete while enforcing non-negotiable bottom lines around data security, interoperability, and anti-monopoly constraints. At the same time, a model of controlled openness insulated the domestic digital ecosystem from overwhelming external competition during its formative years, creating a critical window for local firms to scale and mature. In long-cycle, capital-intensive domains where market incentives were weak—such as core computing infrastructure, AI platforms, and large-scale models—the state activated a “new national system,” leading initiatives like the East-to-West Computing project and supporting open-source ecosystems to close structural investment gaps.
The result was a globally rare level of integration across the digital stack. China built the world’s densest mobile network, accounting for more than half of global 4G/5G base stations, alongside near-universal fiber-to-the-home coverage. Massive data center clusters in regions such as Gui’an and Ulanqab provided elastic computing capacity, while unified digital identity systems and government cloud platforms laid the groundwork for data interoperability and public data experimentation. For internet companies, this translated into a low-cost, high-certainty operating environment, allowing innovation to concentrate at the application and service layer rather than being diluted by recurring infrastructure failures.
A comparison with India is instructive. India’s IT success has largely been embedded within multinational corporate architectures, compensating for domestic infrastructure constraints rather than overcoming them. By contrast, China’s digital economy was built atop an independently constructed foundation under state leadership, reducing systemic friction and accelerating scale. The lesson extends to US–China competition: in the digital era, infrastructure functions as a form of strategic defense. Market fragmentation and local autonomy have complicated the United States’ ability to deploy nationwide, low-latency networks at speed, while China’s coordinated approach confers advantages in sectors that demand tight integration across hardware, networks, and data—such as connected vehicles, industrial internet systems, and the low-altitude economy.
Ultimately, national capacity need not impede innovation. When effectively deployed, it reduces system entropy, shortens diffusion cycles, and converts technological possibility into scalable reality. In the contest to define the next generation of digital rules, the decisive factor will be which system can most rapidly transform emerging technologies into widely shared, interoperable infrastructure.
Toward a Closed-Loop Innovation Ecosystem: Integrating Talent, Technology, and Capital to Prevent One-Way Brain Drain
A central challenge facing many emerging economies is the one-way outflow of top talent: once elite researchers and engineers leave, they rarely return, weakening domestic innovation capacity over time. By contrast, China has deliberately built a multi-layered innovation ecosystem that integrates industry, academia, research, application, and finance into a single, mutually reinforcing community. This system emphasizes circulation rather than extraction of talent, transforming potential brain drain into a sustainable, closed-loop process of talent reproduction and upgrading.
At the core of this model is deep institutional integration. Leading universities and enterprises jointly establish laboratories and long-term research platforms, enabling academic discovery to remain closely linked to industrial needs. Corporate-led research institutions—supported by major technology firms—complement university research by focusing on applied science and frontier technologies. At the same time, government-guided investment funds and local innovation finance mechanisms de-risk early-stage commercialization, ensuring that promising research outcomes can move efficiently from the laboratory to the market.
Equally important is the creation of a fluid talent circulation mechanism. Researchers can move between universities, corporate R&D centers, startups, and public research institutes without sacrificing career continuity or social recognition. Well-designed programs for overseas returnees—combining research opportunities, financial incentives, and quality-of-life support—further reinforce this circulation. The result is not a rigid system, but a revolving door in which talent repeatedly reinvests its knowledge and experience back into the domestic innovation ecosystem.
The contrast with the United States highlights a broader strategic lesson. In an environment where innovation has become heavily financialized, top talent is increasingly drawn toward short-term, high-return sectors rather than long-cycle, foundational technologies. China’s approach, by comparison, aligns state guidance, market incentives, and social prestige to keep talent concentrated in the real economy and core technologies. In a prolonged global competition, the decisive factor is not the absolute number of talents acquired, but the ability to retain, recycle, and continuously regenerate them. A tightly integrated, five-dimensional innovation community offers a durable path toward that goal.
Beyond Open Source Dependence: Building a Strategically Controllable Technology Stack
Over the past decade, a hard-earned lesson has crystallized within China’s technology community: reliance on external technological ecosystems creates structural vulnerability. From the Snowden revelations in 2013 to the ZTE sanctions in 2018 and the Huawei supply-chain disruptions in 2019, repeated shocks demonstrated that technological dependence can rapidly become a strategic liability. These experiences fostered a deep-rooted awareness that prosperity built on dependency is inherently fragile—and that resilience requires both openness and control.
In response, China has pursued a dual-track strategy. On one hand, it has embraced open source at scale, becoming one of the world’s largest contributors and participants. On the other, it has systematically reduced exposure at critical layers of the technology stack by developing independently controllable alternatives. This includes operating systems and platforms such as HarmonyOS, openEuler, OpenHarmony, and OpenAnolis; foundational databases like OceanBase; and AI and computing toolchains such as MindSpore, Pangu, Wenxin, and DeepSeek. Complementing this is a “bottom-line thinking” approach—maintaining strategic backups to ensure continuity under extreme conditions.
This approach contrasts sharply with technology ecosystems that have not faced comparable systemic disruptions. In such environments, heavy dependence on closed-source, foreign-controlled toolchains—operating systems, cloud platforms, and enterprise software—has often produced a false sense of security. When external breakthroughs or shocks occur, the instinctive reaction is imitation rather than introspection, revealing gaps in foundational capabilities and long-term strategic planning. The absence of sustained pressure delays the development of autonomous ecosystems and weakens resilience.
China’s model, by comparison, emphasizes rapid innovation at the application layer while steadily securing control at the system and infrastructure layers. It pairs openness with autonomy: encouraging vibrant experimentation in consumer applications and services, while investing heavily in independently governed operating systems, chips, frameworks, and standards. Active participation—and leadership—in global standard-setting initiatives such as RISC-V, next-generation communications, and AI governance further embeds this strategy within international collaboration rather than isolation.
The broader implication for global technological competition is clear. The experience of Huawei underscored that “open source” alone does not guarantee security or continuity; key services, governance mechanisms, and ecosystem chokepoints can remain closed or politically constrained. The emerging contest is therefore not about whether technologies are open or closed, but about who defines the rules, controls critical nodes, and shapes the evolution of open ecosystems. By moving from a passive user of open source to an active co-builder and rule-setter, China is advancing a model of “controllable openness”—one that seeks to capture the benefits of collaboration without surrendering strategic autonomy.
Building Organizational Resilience Through an Ownership-Oriented Culture
Organizational resilience in the digital economy is not merely a function of strategy or technology; it is deeply rooted in culture. A decisive cultural shift—from an employee mindset centered on task execution to an ownership spirit focused on value creation—has played a critical role in shaping the adaptability and long-term competitiveness of leading Chinese internet companies. This shift contrasts sharply with more transactional employment models found elsewhere and offers insight into how resilience is cultivated at scale.
One foundational driver of this transformation has been the widespread adoption of equity incentives. Early-stage Chinese internet firms aggressively implemented employee stock ownership plans, aligning individual effort with enterprise outcomes and turning technical staff into genuine stakeholders in innovation. This ownership-based structure fostered intrinsic motivation and long-term commitment. By comparison, the dominant model in large Indian IT services firms emphasizes project-based staffing, rigid hierarchies, and limited upward mobility for technical talent, reinforcing an employee mentality focused on delivery rather than discovery.
A second pillar of resilience lies in internal talent circulation. China has developed a self-reinforcing ecosystem in which large platforms, entrepreneurship, and capital formation are tightly interconnected. Alumni of companies such as Alibaba, Tencent, and ByteDance frequently go on to found startups or lead investment initiatives, creating a closed-loop system of experience, capital, and mentorship. This dynamic continually refreshes the innovation pipeline. In contrast, much of India’s top technical talent exits the domestic system for opportunities abroad, with relatively few returning to build companies or investment institutions at home, resulting in a thinner venture capital and entrepreneurial base.
Finally, tolerance for failure has become an embedded organizational norm within the Chinese internet sector. The prevailing ethos emphasizes rapid trial and error, incremental experimentation, and fast iteration. High-profile examples—including Baidu’s push notification initiatives, Tencent’s Pengyou.com, and Alibaba’s Laiwang—illustrate a system in which unsuccessful experiments are accepted as necessary costs of progress rather than career-ending mistakes. This stands in contrast to outsourcing-driven IT organizations, where strict adherence to client specifications leaves little room for deviation, experimentation, or learning from failure.
Taken together, equity-based incentives, dynamic talent circulation, and a normalized failure culture have enabled a transition from compliance-driven execution to ownership-driven innovation. This cultural leap has endowed organizations with greater resilience, allowing them not only to withstand shocks but to adapt, reinvent, and compound their capabilities over time.
Mutual Reinforcement of Manufacturing and the Internet as a Force for Industrial Integration
Since the 1980s, India has followed an unconventional development trajectory, bypassing the classic sequence from agriculture to manufacturing and then to services. Through this “industrial leap,” it has built a service-led economy and a globally competitive service export sector, particularly in information technology. This path was shaped in part by constraints in physical infrastructure—such as highways, ports, and logistics networks—which limited the large-scale consolidation of manufacturing capabilities.
However, productive services, especially IT, are not independent of manufacturing. In practice, they require deep integration with industrial processes to generate foundational technologies and platforms. India’s incomplete manufacturing ecosystem has constrained this integration, leaving gaps in critical areas such as domestic databases, industrial AI models, and enterprise systems like ERP. As a result, despite its strong presence in global outsourcing, India has struggled to develop core digital-industrial capabilities rooted in its own production systems.
By contrast, China illustrates how the internet can function not merely as a virtual economy but as the operating system of the real economy. Digital platforms and manufacturing firms reinforce one another through continuous feedback loops: flexible apparel supply chains enabled by Alibaba’s Rhino Manufacturing, industrial MRO procurement digitized by JD.com, direct-to-consumer automotive sales pioneered by BYD through live streaming, and content-driven drone ecosystems built by DJI. In these cases, internet technologies are shaped by manufacturing realities, while manufacturing efficiency and innovation are amplified by digital systems.
The long-standing disconnection between India’s IT sector and its manufacturing base highlights the cost of missing this two-way empowerment. Software firms may service global clients, but without access to real production, assembly, and operational scenarios, their products risk becoming abstract tools divorced from industrial substance. Sustainable industrial upgrading depends on breaking these silos—allowing manufacturing to inform digital development, and digital platforms to reconfigure manufacturing—so that each side continuously strengthens the other.
Strategic Clarity: Balancing Core Security with Frontier Innovation
China has pursued a deliberate strategy that combines robust security with ambitious technological advancement, demonstrating a model of strategic clarity. Rather than treating the internet and emerging technologies purely as commercial domains, China has structured its approach along complementary layers. At the core, government-led initiatives, financial institutions, and state telecommunications companies ensure the resilience of critical infrastructure and basic software. Programs such as the Information Technology Innovation Project, coupled with backup planning mechanisms, secure the “bottom line” against systemic risks.
Simultaneously, China encourages private enterprises to explore frontier breakthroughs in both consumer and industrial sectors. Platforms like Pinduoduo’s Temu and Shein exemplify how flexible supply chains and innovative business models can flourish under state oversight, pushing technological boundaries without compromising systemic stability. This dual-track approach is reinforced by a clear institutional framework: laws and regulations, including the Data Security Law and Generative AI Management Measures, strike a careful balance between fostering innovation and safeguarding security. The result is an evolutionary “red versus blue team” model, where state entities protect the core while private actors experiment and expand the technological frontier, coordinated strategically by the state at critical junctures.
The contrast with the United States underscores the significance of China’s model. Overly rigid security measures, such as the TikTok ban, have inadvertently accelerated global decoupling from U.S. technology, while China’s “precise security” approach defends only essential assets, allowing broader market experimentation. This enables strategic resilience not merely as protection from attacks, but as the combination of defense and rapid adaptation. By permitting continuous market-driven innovation alongside secure infrastructure, China effectively “changes engines as it runs” in high-tech sectors such as AI, electric vehicles, and photovoltaics—avoiding the U.S. dilemma of halting innovation due to political friction or financial risk aversion. In sum, China’s approach exemplifies how strategic clarity can harmonize bottom-line security with frontier breakthroughs, sustaining both stability and long-term technological leadership.
Final Thoughts
China’s true competitive advantage in the internet and technology sector is not demographic scale or the number of engineers, but a systemic innovation mechanism defined by state guidance, market dominance, scenario-driven development, engineering implementation, organizational evolution, and bottom-line defense. Unlike India’s reliance on cheap labor and perpetual arbitrage, China has transformed its comparative advantages into systemic capabilities—spanning user interfaces, protocol stacks, data centers, chips, algorithmic models, and industrial processes—gradually reclaiming the power of definition. This approach illustrates that China’s rise is not a replication of the West, but a redefinition of modernity in the digital era. Infrastructure forms the skeleton, scenario-driven needs the blood, engineering capabilities the muscles, and institutional flexibility the nervous system. While the US retains strengths in original innovation and capital, China’s scale of scenarios, system integration, and strategic patience allow it to convert technology into productivity for 1.4 billion people, replicable globally and embedded across industries. The lesson is clear: enduring competitiveness arises not from single-factor advantages or one-off inventions, but from the cultivation of systemic intelligence through the coordinated effort of state, market, and society.