On November 20, 2025, Lenovo Group announced its Q2 FY2025/26 results for the period ending September 30, 2025. The company reported a 15% year-over-year revenue increase to RMB 146.4 billion, significantly surpassing market expectations and setting a new quarterly record. Adjusted net profit rose 25% YoY to RMB 3.66 billion.

A key highlight was the AI-related business, which now accounts for 30% of total revenue—a 13-percentage-point increase YoY. These figures demonstrate Lenovo's position as a pioneer in the global AI race, successfully monetizing its technology and signaling a new phase in the deep integration of manufacturing and artificial intelligence.

Historically, China's manufacturing sector has competed on supply chain efficiency, with production capacity, cost control, and distribution channels determining a company's market position. AI is reshaping this landscape by expanding value creation and altering competition dynamics. The AI industrial chain—spanning infrastructure, models, terminals, and applications—has opened new opportunities for traditional manufacturers. Meanwhile, the complex ecosystem required for AI implementation has shifted the competitive focus toward technological integration and deployment capabilities rather than pure efficiency.

This article examines Lenovo's hybrid AI strategy to illustrate the ongoing transformation in the AI industry and how major players are evolving their business structures and competitive models, offering investors fresh perspectives on corporate value.

1. Hybrid AI Emerges as the Industry Solution Public awareness of AI often begins with ChatGPT, which impressed users with its human-like responsiveness, attracting over 100 million users within two months. However, despite rapid advancements in large language models (LLMs), real-world AI applications face significant challenges.

Public LLMs offer vast knowledge and convenience but lack robust privacy and data security protections. Without access to private data stored on personal devices or within corporate systems, these models struggle to deliver personalized, accurate services. Additionally, AI deployment is constrained by factors like computing power, storage, bandwidth, and security, requiring systemic multi-layer coordination rather than isolated solutions.

To address these limitations, Lenovo proposed a "hybrid AI" approach in 2023, which has since gained industry-wide acceptance. Hybrid AI combines localized private AI deployments (on personal devices or enterprise data centers/private clouds) with public cloud-based models, creating a complementary ecosystem.

For personal AI, this means moving beyond single-device solutions. Lenovo's "one body, multiple terminals" framework distributes AI workloads across cloud and edge devices, enabling multimodal sensing and cross-device coordination for personalized services. The company's "Tianxi Super Intelligent Agent" serves as the core, deployed across PCs, smartphones, tablets, glasses, and watches to create a natural interaction hub.

This system relies on a robust technical matrix, including the X-Engine (a terminal inference accelerator capable of running billion-parameter LLMs on a single PC) and the Hybrid Personal Knowledge Base (HPKB) for personalized solutions. The recently launched Tianxi AI 3.5 emphasizes security, leveraging Lenovo's self-developed Trusted Hardware Computing Platform (THCP) technology.

Other tech giants have introduced similar ecosystem-based solutions, such as Microsoft's Copilot (deeply integrated into Windows 11), Honor's YOYO, and ByteDance's Lumine, reflecting a shared technical framework.

2. Industry Giants Transition to Full-Chain Suppliers Product and ecosystem upgrades typically drive replacement demand, boosting both user benefits and corporate performance—a trend evident in Q2 earnings reports.

Lenovo's PC revenue grew 17% YoY, with premium models surging 25%. The company now holds 31.1% of the global Windows AI PC market and 25.6% of the overall PC market, both record highs.

Other AI leaders also delivered strong results: Meta's revenue jumped 26% YoY, with CEO Mark Zuckerberg crediting AI-driven ad system improvements. Microsoft's revenue and net profit rose 18% and 12%, respectively, led by a 28% increase in intelligent cloud services.

These results confirm that hybrid AI adopters are entering a value-realization phase. However, the ecosystem's complexity exceeds that of the internet and mobile internet eras, meaning traditional metrics alone cannot capture an AI company's full value. Industrial value now encompasses not only LLMs but also the infrastructure (servers, storage, networks, software, data, edge devices) and hybrid computing terminals (PCs, tablets, phones, etc.) that enable model deployment.

For Lenovo, this shift has rendered its "traditional PC maker" label obsolete. Its "one body, multiple terminals" strategy has expanded AI capabilities to smartphones and tablets. AI tablet sales doubled YoY, while Motorola smartphone sales hit record highs. AI devices now contribute 36% of the Intelligent Devices Group (IDG) revenue, up 17 percentage points YoY.

The company's value chain is also extending into infrastructure. Revenue from the Infrastructure Solutions Group (ISG) grew 24%, with AI infrastructure services achieving double-digit growth. Income from Lenovo's self-developed Neptune liquid cooling technology soared 154%.

As LLM capabilities approach saturation, the AI competition has entered its "second half," where systemic integration for real-world applications becomes the key to value creation. This shift allows software-focused players like Meta and Google to expand into hardware, while Lenovo leverages its PC heritage to pivot toward the broader AI industrial chain.

Notably, this convergence is creating overlaps among previously distinct industry leaders. IDG predicts the global AI market will exceed RMB 2.3 trillion by 2025. Early hybrid AI adopters are poised to capture significant shares, though the long-term competitive landscape remains uncertain.

3. AI as Capability Spillover, Not Just Product Output Enterprise AI faces unique challenges compared to personal AI. Companies require quantifiable links between AI and core KPIs like productivity, but industry-specific data and model needs demand tailored solutions.

To address this, Lenovo SVP and China Solutions Services Group GM Dai Wei proposed a comprehensive enterprise AI service architecture. It starts with hybrid infrastructure as the foundation, collecting enterprise data to build model factories and intelligent agent platforms, ultimately delivering AI services.

Lenovo's "Hybrid AI Advantage Set" encompasses five capability layers—from infrastructure to services—enabling two delivery models: "Super Factory" (reducing project cycles by 80% via modular assembly) and Agent-as-a-Service (AaaS) (lightweight deployment through subscriptions).

Similar frameworks include Microsoft's Azure AI Foundry (letting developers "assemble AI capabilities like building blocks") and ByteDance's Coze (combining agents, knowledge bases, and plugins for rapid deployment).

These systems have proven effective internally. Lenovo's smart transformation cut supply chain order delivery times by 28%, improved accuracy by 25%, and reduced manufacturing/logistics costs by 20%. Its Hefei and Monterrey plants were named "Lighthouse Factories" by the World Economic Forum, and the company ranked eighth in Gartner's Top 25 Supply Chains.

The spillover effects are equally notable. For instance, Lenovo helped dairy giant Yili integrate a supply chain control tower system, lowering transportation costs per ton of raw milk and achieving a 98% on-time delivery rate. Yili also established a transparent data system traceable from farm to consumer—showcasing everything from pasture quality to nutritional details.

As Yili Digital Technology Center GM Shang Zhihu stated, "Every drop of milk embodies digital intelligence." Enterprise AI is redefining trust between businesses and consumers, transforming not just production efficiency but entire industry-consumer relationships.

4. Systemic Integration as the Core Barrier and Profit Driver IDC estimates AI will contribute $19.9 trillion to the global economy by 2030, boosting that year's GDP by 3.5%. Every $1 spent on AI could generate $4.6 in indirect effects (e.g., supply chain income, productivity gains).

This optimism is reflected in corporate earnings. Lenovo's Solutions and Services Group (SSG) revenue grew 18% to RMB 18.3 billion, with AI services posting triple-digit growth. Similarly, Microsoft's intelligent cloud and Google Cloud grew 28% and 34%, respectively, becoming their fastest-growing segments.

Yet adoption remains limited. According to Accenture's 2025 China Digital Transformation Index, while 46% of enterprises are scaling generative AI, only 21% do so rapidly, and just 9% achieve significant value conversion.

This suggests two insights: (1) service providers like Lenovo and Microsoft have untapped enterprise markets, and (2) successful AI deployment requires systematic methodologies and mature technical architectures—barriers for less-experienced firms.

This reaffirms the current AI competitive paradigm: value creation now stems from systemic integration capabilities rather than generic model improvements. Proven service architectures are becoming insurmountable moats for early movers.

Lenovo's SSG exemplifies this, maintaining an operating margin above 20% (22.3% in the latest quarter) as the group's profit engine.

Conclusion As hybrid AI becomes mainstream, its ecosystem complexity offers valuation upside and capability dividends for leaders like Lenovo, whose growth potential now spans a RMB 2 trillion AI market beyond PCs. Its first-mover technical服务体系 also delivers higher barriers and service premiums.

However, AI's challenges remain formidable. How industry giants navigate this terrain will unfold in the markets ahead.