Lenovo’s Artificial Intelligence (AI) capabilities were on full display at the 2025 Global Industry Analyst Conference (GIAC) in Raleigh, North Carolina. ABI Research analysts Leo Gergs and Paul Schell made the trip across the pond from Europe to assess Lenovo’s innovative AI strategy.
Enterprises are the big prize, but seizing this opportunity has been no picnic. According to an MIT study, 95% of Generative Artificial Intelligence (Gen AI) pilots fail to generate a Return on Investment (ROI), making organizations skeptical of deploying advanced AI tools. Moreover, many Small and Medium Enterprises (SMEs) lack the internal expertise to scale AI.
This all comes amid the backdrop of a cloud revolution and a growing data center cooling conundrum. Lenovo addresses these enterprise challenges directly through a comprehensive AI technology ecosystem that integrates infrastructure, software, and services.
In this blog, Gergs and Schell identify the four pillars of Lenovo’s enterprise AI strategy.
Key Takeaways:
- Hybrid AI: Lenovo’s hybrid AI architecture gives control back to the enterprise. Customers can deploy AI workloads where it makes the most sense: in the cloud, on-premises, or on-device.
- Vertically Integrated Supply Chain: The China-based company manufactures many of its own AI components and has a regionally diverse logistics apparatus. Therefore, Lenovo is more resilient to sudden supply chain disruptions than most of its Western competitors.
- Heterogeneous Cloud Computing: Lenovo develops cloud computing solutions that are flexible, cost-effective, compliant, and tailored to specific AI workloads and regions. For example, its TruScale Graphics Processing Unit-as-a-Service (GPUaaS) offering enables enterprises to accelerate AI breakthroughs at a managed, pay-as-you-go consumption model.
- Data Center Cooling: Lenovo’s liquid cooling solutions demonstrate substantial energy savings capabilities for AI servers. This is a value driver for data center operators and enterprises aiming to reduce energy costs.
1. Embracing Hybrid AI
What is Lenovo’s strategy?
Lenovo’s hybrid AI strategy instills flexibility into enterprise AI deployments by combining cloud, on-premises, and device-level infrastructure. That way, AI can be deployed where it is needed based on use case, security requirements, latency, etc.
Lenovo’s Hybrid AI Advantage platform is well-marketed as enterprises increasingly adopt advanced AI tools such as Agentic AI. Many enterprises struggle to realize ROI from AI deployments, and employees are often left in the dark. Lenovo complements its technological solutions with change management services, including AI readiness assessments, tailored workforce training, copilot integration, AI governance, and corporate culture adaptation.
Lenovo has worked closely with vendors like NVIDIA and Intel to support enterprise AI across hospitality, workplace safety, retail, and quality control.
How does this strategy benefit the AI value chain?
Lenovo’s hybrid AI solutions equip enterprises with more control, transparency, and freedom to run AI workloads wherever needed. The company’s after-sales services, under the Hybrid AI Advantage platform, help enterprises quickly transition from AI testing to real-world deployment.
2. Leveraging AI Supply Chain Advantages
What is Lenovo’s AI strategy?
Lenovo has one of the top-ranked supply chains in the world. The Chinese vendor uses a hybrid business strategy called the ODM+ model. It combines the company’s extensive and geographically dispersed supply chain with its AI design, manufacturing, and services capabilities. This accelerates AI delivery and helps shield Lenovo from sudden trade restrictions and geopolitical risks.
Lenovo has a vertically integrated supply chain because it has roots in China and a strong foothold in North America. Compared to many of its Western peers in the AI industry, Lenovo possesses greater end-to-end control by designing and integrating AI components in-house.
According to Gergs, Lenovo’s supply chain model is particularly conducive to hyperscaler customer acquisition. He says, “In the demanding AI hardware supply chain, the vertical integration seen in the ODM+ model is a key differentiator, particularly for hyperscale clients who require dozens of custom server designs for a single deployment.”
How does this strategy benefit the AI value chain?
Lenovo reduces supply delays and supports a variety of regions thanks to its versatile supply chain. As a result, hyperscalers and enterprises can deploy and scale AI systems faster and with fewer risks.
3. Supporting a Heterogeneous Cloud Landscape
What is Lenovo’s AI strategy?
At GIAC 2025, it was evident that Lenovo has ambitious plans to support a more heterogeneous cloud ecosystem. Its leadership team recognizes that enterprises are increasingly embracing mixed cloud strategies. combining hyperscalers with neoclouds and other specialized providers to achieve stronger regional compliance, address niche workloads, and gain greater price flexibility.
“Its [Lenovo’s] focus on heterogeneous compute architectures and open hybrid environments positions it as a credible alternative for enterprises that value autonomy and regulatory alignment as much as performance,” says Gergs. He emphasizes how Lenovo’s company initiatives aim to consolidate Central Processing Units (CPUs), Graphics Processing Units (GPUs), and accelerators under a single platform. Lenovo’s goal is to make it easier for enterprises to move between cloud environments and ensure cloud sovereignty.
How does this strategy benefit the AI value chain?
Lenovo’s heterogenous approach helps companies gain cloud agility and regulatory compliance as they scale AI workloads. Enterprises are growing tired of hyperscaler lock-in due to unclear pricing structures, over-reliance on proprietary systems, and a lack of specificity. Lenovo’s AI portfolio is evolving with these customer pain points in mind.
For Lenovo to build trust and compliance at the local level, ABI Research recommends that the company work closely with regional data center operators, AI infrastructure players, and cloud platform providers.
4. Cooling AI Data Centers
What is Lenovo’s AI strategy?
Data center cooling is another core pillar of Lenovo’s AI strategy. AI data centers require a significant amount of power, and energy consumption will only increase as enterprises scale Gen AI tooling. Tapping into more than a decade of experience in cooling, Lenovo supports high-performance computing with its Neptune-branded liquid-cooling solution. It can handle AI server racks with up to 105 Kilowatts (kW) capacity, sufficient for the vast majority of modern AI workloads.
According to Lenovo, its cooling portfolio yields a 40% reduction in power consumption and 3X better cooling efficiency. The company plans to support a more diverse AI server ecosystem as data center cooling becomes a bigger priority.
How does this strategy benefit the AI value chain?
Lenovo’s server cooling solution increases data centers’ Power Usage Effectiveness (PUE). These PUE gains are essential for meeting climate regulations and reducing energy costs. It’s also worth noting that liquid cooling helps reduce dependence on expensive air-conditioning infrastructure.
Schell states that “Lenovo’s approach [to cooling] allows data centers to sustain higher workload intensities without compromising reliability, while also supporting compliance with emerging sustainability regulations in Europe and Asia.”
Lenovo’s AI Strategy Is Enterprise-Ready
Lenovo has ventured far beyond its hardware roots and into the lucrative AI software and services landscape. The company excels at identifying enterprise pain points and staying attuned to the AI industry shifts. This has allowed Lenovo to adapt its AI strategy accordingly.
Translating AI hype into real-world revenue creation requires Lenovo and the wider AI industry to focus on integration, sovereignty, and sustainability. Through hybrid AI architecture, a vertically integrated supply chain, heterogenous cloud support, and data center cooling, Lenovo captures each corner of the enterprise AI value chain.
Grab Gergs and Schell’s more in-depth analysis of Lenovo’s AI blueprint and future expectations by downloading the whitepaper, Connecting Intelligence: Lenovo’s Vision for Scalable, Sustainable Enterprise AI.
Meet The Analysts
Leo Gergs, Principal Analyst
Principal Analyst Leo Gergs leads the enterprise connectivity and cloud research at ABI Research. Together with his team, Leo's research focuses on enterprise drivers, use cases, and providers for connectivity solutions, including private cellular, network slicing, Software-Defined Wide Area Networks (SD-WANs), and Fixed Wireless Access (FWA).
Leo's research also explores enterprise cloud deployments with a key focus on hybrid cloud deployment strategies, sovereign cloud offerings, and emerging trends like Graphics Processing Unit (GPU) clouds and quantum compute.
Paul Schell, Senior Analyst
Paul Schell, Senior Analyst at ABI Research, is responsible for research focusing on Artificial Intelligence (AI) hardware and chipsets with the AI & Machine Learning Research Service, which sits within the Strategic Technologies team. The burgeoning activity around AI means his research covers both established players and startups developing products optimized for AI workloads.