PatentVest Pulse:

2.0 Market Landscape Overview

In the rapidly evolving landscape of generative AI, data centers have transitioned from infrastructure providers to critical enablers of transformative innovation. The increasing scale and complexity of data centers present significant management challenges across diverse components, including servers, networking, and energy systems.

By 2025, global enterprise data generation and utilization are projected to reach approximately 1.2 million exabytes, demanding robust storage and processing capabilities across public cloud platforms and private data centers. This exponential growth, driven by increased AI applications, IoT deployments, and edge computing requirements, presents substantial data management challenges. High-speed interconnects are critical for addressing data gravity—the increasing tendency of large datasets to attract more applications, services, and computing resources. Several companies hold key patents in this area, particularly in chip-to-chip, server-to-server, and datacenter-to-datacenter interconnects. For example, Nvidia’s NVLink enables high-speed GPU-to-GPU communication, which is essential for AI model training. Intel’s Compute Express Link (CXL) facilitates memory sharing between CPUs, GPUs, and accelerators, mitigating AI data bottlenecks. AMD leverages Xilinx technology to optimize low-latency AI networking.

A critical concern is the significant energy and resource consumption of data centers, further amplified by the industry’s ongoing expansion driven by pervasive digitalization. The growing power requirements of artificial intelligence (AI) workloads have spurred considerable advancements and patent filings in data center liquid cooling technologies. Conventional air cooling is proving insufficient for dissipating the heat generated by high-performance computing (HPC) and AI applications, thus motivating companies to develop innovative liquid cooling solutions. For example, In 2024, NVIDIA submitted a patent application for energy-efficient liquid cooling systems for data centers. This technology seeks to mitigate the significant energy consumption inherent in conventional cooling approaches. Additionally, The demand for energy-efficient AI processing has led to innovations in chip design. For example, Xeon “Sierra Forest” is designed for hyperscale cloud AI workloads with ultra-high energy efficiency.

The escalating demand for computational resources and optimized AI workloads has intensified the competition for intellectual property protection in this sector. Significant financial investments from industry leaders like Salesforce, Nvidia, and Cisco confirm the considerable promise of AI startups.

Past technological innovations, such as Amazon’s pioneering “1-Click” patent and NVIDIA’s CUDA software, demonstrate how foundational intellectual property can create substantial industry advantages, giving companies a lasting competitive edge. Organizations such as OpenAI and Cohere have successfully obtained significant funding to develop AI models that require considerable computing power, including the purchase of high-end processors from companies like Nvidia. For data centers, securing key patents is no longer a strategic choice; it is a necessary condition for success in the AI-driven economy.

To secure a competitive edge, data centers must first understand their place within the broader AI tech stack. This stack spans three primary layers: hardware, middleware, and applications. At the hardware level, innovations like GPUs, AI-specific chips, and scalable storage solutions are critical for managing the massive workloads’ generative AI demands. Middleware plays a key role in optimizing operating systems and hypervisors for AI-specific applications. At the top of the stack, AI-driven applications for resource allocation, load balancing, and model deployment are becoming central to data center operations.

Trends such as the utilization of renewable energy sources, the implementation of advanced cooling solutions, and adherence to green building practices are gaining prominence; therefore, the data center infrastructure management market is projected to reach a valuation of 1,962.3 million USD by 2024, exhibiting a rise from its 2023 value of 1,755.2 million USD.

The global data center as a service market reached a valuation of USD 71.92 billion in 2022 and is projected to experience a compound annual growth rate (CAGR) of 25.1% between 2023 and 2030.

Developing a robust patent strategy begins with mapping the AI tech stack and identifying areas where data center technology can make the biggest impact. Assessing patentability is a critical next step, as IP strategies must focus on enforceable and high-impact technologies that align with the economic realities of the industry. Chokepoints, such as NVIDIA’s CUDA patents that lock users into their ecosystem, offer a blueprint for how data centers can establish similar strategic advantages. By identifying and protecting such critical technologies, data centers can transform their investments into long-term revenue streams through licensing and partnerships.

3.0 Patent Landscape Analysis

The most valuable patents in this landscape focus on tangible improvements and efficiency gains. For example, combining AI and hardware innovations to enhance energy optimization or reduce latency offers more protective and impactful IP than abstract algorithmic ideas. Data centers that strategically target these areas—particularly in technologies like liquid cooling systems, AI-driven predictive maintenance, and traffic routing—can secure their place as leaders in the AI infrastructure ecosystem.

While many areas of AI infrastructure are heavily patented, emerging opportunities remain for data centers to claim whitespace. Underexplored domains like energy-efficient GPU integration, modular edge data centers, and privacy-preserving mechanisms for distributed AI systems present fertile ground for innovation. The shift to generative AI has also opened new doors for collaborative AI model training, multi-cloud orchestration, and infrastructure scalability, allowing forward-thinking data centers to stake their claims early in these spaces.

To uncover these opportunities, patent landscaping becomes an indispensable tool. Analysts can provide insights into competitors’ IP positions and map the landscape to highlight whitespace opportunities in AI infrastructure. For instance, benchmarking portfolios from players like NVIDIA, AMD, Google, and Microsoft reveals areas of saturation and gaps where new patents can thrive. By analyzing regional trends and patent filings in high-growth AI markets, data centers can strategically align their IP efforts with global market dynamics. This approach not only identifies valuable niches but also prepares data centers to secure patents in jurisdictions where enforcement and monetization are most effective.

Patent landscaping also allows data centers to anticipate and adapt to emerging trends. Recent activity around AI infrastructure, such as energy-efficient cooling and edge computing, highlights where innovation is heading. Analysts can track these trends, evaluate the maturity of technologies, and identify under-patented areas with high potential for growth. By presenting these findings through clear visuals like heatmaps and trend analyses, patent landscaping provides actionable insights that directly inform R&D priorities and strategic planning.

This section provides a comprehensive analysis of the patent landscape for AI-driven data centers, encompassing patent holdings, technological trends, and competitive positioning. Analysis of patent families and overall document counts will reveal key areas of innovation.

This analysis will also include a comprehensive patent portfolio assessment of the top players, comparing factors such as their filing trends over time, the overall size of their patent portfolios, the geographic coverage of their patents, the average age of the patents in their portfolios, and the specific technologies they focus on.

Additionally, we will examine litigation trends to understand how these companies are leveraging their patents to protect their market share and gain a competitive advantage. These insights will provide a valuable understanding of the competitive dynamics and future direction of the AI-driven data center market.

At PatentVest, we understand the unique challenges and opportunities facing data centers in the AI revolution. Our tailored IP solutions help data centers navigate this complex landscape by identifying whitespace opportunities, crafting strong patent portfolios, and leveraging IP for partnerships and licensing. With our support, data centers can move beyond being infrastructure providers to become innovation leaders, driving the next wave of AI breakthroughs.

The generative AI era is transforming industries at an unprecedented pace, and data centers are at the heart of this transformation. By adopting a proactive and strategic approach to IP, data centers can not only adapt to these changes but lead them, securing their position as indispensable players in the AI economy. Now is the time to act, before the whitespace disappears and competitors seize the opportunities that could define the future of AI infrastructure. Let us help you turn these challenges into a competitive advantage. Together, we can make your data center the backbone of the AI-driven future.

3.1. Major Players In AI-Driven Data Centers

The AI-driven data center sector is defined by a select group of companies and institutions that dominate patent filings and technological innovation. These organizations are securing intellectual property in key areas such as AI hardware acceleration, edge computing, and energy-efficient data center operations, positioning themselves as leaders in the evolving landscape.

Intel Corporation – AI Hardware Acceleration & Edge Computing

Intel’s extensive patent holdings reflect a proactive strategy of defensive filings and strategic licensing, allowing the company to secure its market position in the face of rising competition from NVIDIA and AMD. Its AI-centric data center IP portfolio is designed to strengthen Intel’s foothold in AI workload acceleration and model optimization. Building on a foundation of AI-specific hardware accelerators, memory architectures, and workload optimization techniques, Intel continues to position itself as a dominant player in AI-driven data centers. The company’s three-pronged AI strategy includes:

• AI Hardware: Development of processors optimized for AI inference and training
• AI Software: Enhancements to maximize efficiency in AI workloads
• AI Data Centers: Scaling AI computing while optimizing power consumption and performance

Notable patents from Intel include:

• US11157311B2 – Automatic localization of acceleration in edge computing environments
• US11507430B2 – AI-optimized data processing architecture
• US11630706B2 – AI model inference acceleration for edge computing

These patents underscore Intel’s focus on AI-driven infrastructure efficiency, resource optimization, and high-performance computing, solidifying its leadership in next-generation AI-powered data centers.

State Grid Corporation of China – AI-Driven Energy Optimization

As a major patent holder in AI-powered data center operations, the State Grid Corporation of China leverages artificial intelligence to optimize energy usage across large-scale infrastructures. Its portfolio highlights advanced power management and dynamic resource scheduling, reflecting a strong commitment to efficiency and sustainability in data center environments. Notable patents from SGCC include:

• CN113282368A – Edge computing resource scheduling method for substation inspection.
• CN114281544A – Electric power task execution method and device based on edge calculation.

In particular, CN114281544A demonstrates an AI-driven approach to dynamic energy optimization, adjusting power supply based on workload projections and environmental factors such as temperature and humidity. This capability aligns with global sustainability trends and green data center strategies, solidifying State Grid’s position as a leader in energy-efficient AI deployments.

Chongqing University of Posts and Telecommunications – Edge Computing Innovations

Chongqing University conducts edge computing research, developing AI-based solutions to improve distributed computing environments. Its patent portfolio highlights resource scheduling, network security, and infrastructure for performance-sensitive applications. Notable patents from Chongqing University include:

• CN111813502B – Computing resource management scheduling for industrial edge node.
• CN112202847B – Server resource allocation method for mobile edge computing.

By focusing on server resource allocation through mobile edge computing, the university aims to reduce latency and enhance overall performance in AI-driven data centers.

Nanjing University of Posts and Telecommunications – Deep Learning for Resource Allocation

Nanjing University conducts AI-powered resource allocation and network optimization research, emphasizing deep learning to improve efficiency and reliability in AI-driven data centers. Notable patents from Nanjing University include:

• CN115562760A – Deep learning model layering and resource unloading method for edge computing nodes
• CN112540845B – Collaboration system and method for mobile edge computation

By applying mobile edge node computation, the university addresses latency and resource utilization challenges, contributing to advancements in next-generation data center technologies.

Samsung – Mobile Edge Computing & AI Resource Management

Samsung has increased its patent filings in AI-driven data centers, focusing on mobile edge computing. The company’s patents address AI-powered resource allocation and dynamic workload distribution in edge and cloud environments. Notable patents from Samsung include:

• US11689968B2 – Method and apparatus for executing virtualized network function
• US11321132B2 – Edge computing method and apparatus for flexibly allocating computing resources

By collecting resource usage data at the edge, Samsung’s approach evaluates service traffic and usage to enhance efficiency in mobile edge computing.

3.2 Comparative Patent Portfolio Analysis of Top Players

As mentioned above, this section will cover a comprehensive patent portfolio assessment of the top players, comparing factors such as their patent filing trends over time, the overall size of their patent portfolios, the geographic coverage of their patents, the average age of the patents in their portfolios, and the specific technologies they focus on.

3.2.1 Patent Publishing Trends in AI-Driven Data Centers

Analyzing patent filing activity over the past decade provides valuable context for understanding competitive dynamics and innovation patterns within AI-driven data centers. As illustrated in the chart below, patent filings in this technology space increased substantially starting in 2020 and have remained elevated since then. This sustained level of patent activity indicates intensified innovation efforts and growing strategic interest among leading technology companies and research institutions.

The notable increase in patent filings since 2020 reflects companies’ strategic emphasis on securing intellectual property to protect technological innovations and market positions. This trend highlights not only the rising importance of AI-driven data center technologies but also underscores patenting as a crucial tool for competitive differentiation, monetization, and long-term strategic advantage.

Patent Publishing Trends - Top Companies

The chart below compares patent publishing trends among five key organizations leading innovation in AI-driven data centers: Intel Corporation, State Grid Corporation of China (SGCC), Chongqing University of Posts and Telecommunications, Nanjing University of Posts and Telecommunications, and Samsung. 

• Intel Corporation: Intel's significant increase in patent filings during 2022 suggests a strategic initiative to bolster its intellectual property portfolio and potentially explore new market opportunities. Intel maintains a robust portfolio of edge computing solutions for data centers. Recent patent filings highlight Intel's focus on AI-driven resource allocation and edge computing to optimize power consumption. Intel's AI strategy integrates AI hardware, specifically processors optimized for AI workloads; AI software, maximizing hardware utilization; and AI data centers, scaling AI workloads while prioritizing power, performance, and efficiency. Intel's patent holdings are closely aligned with this AI strategy.

• The State Grid Corporation of China: The State Grid Corporation of China is prioritizing patent applications for resource allocation methods that combine edge and cloud computing to decrease energy consumption. The State Grid Corporation of China’s AI aims to improve the management and operation of energy grids and AI-powered data centers by optimizing data center energy usage, cooling, and server load distribution. The State Grid Corporation of China patent holdings are closely aligned with this AI strategy.

• Chongqing University Of Posts And Telecommunications: Chongqing University of Posts and Telecommunications is strategically allocating resources for edge computing device development. Since 2022, the university has consistently filed patents, reflecting a commitment to innovation and intellectual property protection. This patent activity, particularly in network security, directly supports the university's AI hardware and software strategy and its focus on big intelligent computing, AI education, and AI application research.

• Nanjing University Of Posts And Telecommunications: Nanjing University of Posts and Telecommunications is pursuing patents for the application of deep learning to resource allocation. Nanjing University of Posts and Telecommunications exhibits a strategic alignment of its AI-driven data center patent portfolio with its overarching AI hardware and software strategy. The university's emphasis on machine learning, data mining, network security, and hardware reliability is strongly supported by its patent filings, positioning NJUPT for substantial contributions to the advancement of AI and data center technologies.

• Samsung: Samsung is strategically focusing on filing patents for resource allocation using edge computing, particularly mobile edge computing. Samsung's AI strategy is founded on three key pillars: AI hardware advancements (including processing units, memory, storage, and power-efficient computing), AI software development, and the deployment of AI applications within the data center. Samsung’s AI-driven data center patents align strongly with its overall AI strategy.

3.2.2 Crowded vs. Whitespace Patent Opportunities in AI-Driven Data Centers

The patent heatmap below identifies crowded patent areas—where leading companies have established strong intellectual property positions—and white spaces, which are emerging technology categories with fewer existing patents, offering strategic opportunities for meaningful IP development.

Crowded Areas - Heavily Patented

Crowded areas are sectors heavily saturated with patent filings by major industry players. Categories such as AI and Machine Learning Data Processing Services (321 patents), Industry-Specific Edge Computing Frameworks (120 patents), Standard Cloud Hosting and Data Management (93 patents), AI-driven regional Data Gravity Optimization Platforms (83 patents), and Data Storage Solutions for Large Enterprises (29 patents) illustrate intense competition. In these highly contested segments, differentiating innovations is challenging, prompting companies to pursue strategic monetization methods like licensing, mergers, acquisitions, and patent pooling. Intel’s 2022 licensing agreement with IPValue Management Group, transferring nearly 5,000 patents, demonstrates how effectively managing and monetizing extensive patent portfolios can generate significant revenue and strategic partnerships even in crowded markets.

White Space - Emerging Patent Opportunities

White spaces represent emerging technology categories in AI-driven data centers with limited patent activity. These less-patented areas—such as Adaptive Data Sovereignty and Compliance Engines (7 patents), Hybrid Public-Private Cloud Orchestration (7 patents), Green Energy-Powered Data Gravity Reduction Systems (6 patents), Backup and Disaster Recovery Services (3 patents), and Traditional Data Center Co-location Services (3 patents)—offer valuable opportunities for companies to secure foundational intellectual property early. By strategically filing patents aligned with their core capabilities and market positioning, companies can establish strong competitive barriers and become early market leaders.

Successfully monetizing patents in these white space areas depends on careful market analysis, understanding competitors, and accurately valuing IP assets. Companies that secure strong patent positions in these emerging segments can generate meaningful revenue through licensing deals, joint ventures, and specialized infrastructure offerings, positioning themselves for sustainable growth and lasting competitive advantage.

3.2.3 Jurisdictional Coverage

The chart below illustrates the global patent filings for AI-driven data center technologies by jurisdiction.

China leads global patent filings with 521, reflecting its dominant position in AI data center innovation. The United States ranks second with 80 patents, highlighting its ongoing importance as a critical market for technology development and IP protection. South Korea (11), Canada (7), and Germany (7) follow as strategic markets valued for strong patent enforcement and commercial opportunities. Additional targeted filings in Australia (5), Japan (4), the Netherlands (2), and Taiwan (1).

The chart below details where Intel, State Grid Corporation of China, Chongqing University of Posts and Telecommunications, Nanjing University of Posts and Telecommunications, and Samsung are seeking patent protection.

• Intel: Most activity in the U. S. (19) and additional activity in China (8), Germany (6), and European Patent Office (5).
• State Grid Corporation of China (SGCC): Main focus is in China (27) with one WIPO filing (1).
• Chongqing University of Posts and Telecommunications: Focused mostly in China (18) but has WIPO (2) and EPO (1) filings as well.
• Nanjing University of Posts and Telecommunications: Large volume in China. (14). Smaller volumes in the United States, WIPO, and EPO.
• Samsung: Some activity in the United States (4), EPO (3), and South Korea (2), as well as some activity in other regions.

By examining these patent distributions, one can see different strategic priorities at play—Chinese-based entities often prioritize domestic protection first, while Intel and Samsung maintain a broader international reach. These choices reflect regulatory environments, commercial opportunities, and competitive pressures in each region, shaping how companies protect and monetize their AI-driven data center innovations.

3.2.4 Patent Age

The chart below provides a quick snapshot of the average age of patents held by major players in the AI-driven data centers technology space.

The State Grid Corporation of China has the oldest patent portfolio, suggesting a long-standing commitment to innovation and a strong foundation of intellectual property. This could translate to a competitive advantage and potential dominance in the market. Samsung and Chongqing University of Posts and Telecommunications have a relatively new portfolio, suggesting a recent emphasis on AI-driven data center technology, as evidenced by their patent filings. They have been active in this field since 2022. Intel and Nanjing University of Posts and Telecommunications have slightly older patent portfolios, indicating established patent protection, but perhaps less extensive than that of the State Grid Corporation of China.

3.2.5 Patent Litigation Review

In the patent landscape of the AI-driven data centers market, understanding the complexities of patent litigation is crucial when comparing competing companies. This section provides a snapshot of the ongoing legal battles between industry giants, examining key cases, outcomes, and their implications. By looking at these fights, we can see how companies try to protect their inventions, win market share, and influence the future of AI-driven data centers technology. This analysis helps us understand the competition, risks, and opportunities for each company, giving us a better idea of how they might do in the future. Litigation cases involving top players Samsung and Intel are detailed below:

Netlist vs. Samsung 

In 2021, Netlist initiated a lawsuit against Samsung for alleged patent infringement related to the production of memory chips for data center servers, asserting that memory modules utilized in Samsung Electronics' cloud computing servers infringed upon their patents. In November 2024, a jury in Marshall, Texas, rendered a verdict awarding Netlist $118 million. Samsung employs patents to facilitate cross-licensing agreements and mitigate potential disputes. Samsung licenses its patented technologies, such as OLED displays and memory chips, to other companies, including competitors. Historically, Samsung has leveraged its patent portfolio to address legal challenges posed by Apple in the smartphone market. Apple and Samsung have engaged in a protracted legal battle spanning a decade, involving numerous lawsuits filed globally by both companies.

VLSI Technology LLC v. Intel 

Following a 2021 patent infringement trial in the U.S. District Court for the Western District of Texas (Waco), VLSI Technology LLC v. Intel Corp., case number 21-57, Intel has been ordered to pay VLSI Technology LLC $2.18 billion in damages. Intel possesses a substantial patent portfolio and often engages in cross-licensing agreements with other technology companies to prevent legal disputes. Intel generates revenue from certain patents, especially those in areas where it is not currently competing, such as older processor designs and connectivity technologies. Intel has been involved in patent infringement lawsuits, most recently against VLSI Technology.

Google vs. Singular Computing 

Singular Computing filed a suit against Google in the District Court for the District of Massachusetts (Case No. 1:19-cv-12551), alleging patent infringement related to its Tensor Processing Units (TPUs). The suit filed December 20, 2019, and concluded March 4, 2024, claimed Google incorporated Singular Computing's patented TPU technology into its AI processing units supporting services such as Google Search, Gmail, and Google Translate. Google's strategy emphasizes strategic partnerships over direct licensing, although key patents, such as those for Android, have been licensed to certain partners. The company employs a defensive patent acquisition strategy, aiming to minimize litigation while protecting its intellectual property.

AWS vs Kove

The patent infringement lawsuit between Kove IO, Inc. and Amazon Web Services, Inc., case number 1:18-cv-08175, was heard in the United States District Court for the Northern District of Illinois. Filed in 2018, this lawsuit addressed AWS's utilization of cloud data storage products based on Kove's patented technology for scalable cloud systems.

ParTec vs Microsoft

In June 2024, ParTec AG initiated a patent infringement lawsuit against Microsoft Corporation in the U.S. District Court for the Eastern District of Texas. The lawsuit, filed on June 10, asserts that Microsoft's actions infringe upon patents related to its dynamic modular system architecture (dMSA). ParTec and its licensing agent, BF exaQC AG, are the plaintiffs. The court case number is 2:24-cv-00433.

Nvidia and Microsoft vs. Xockets

In 2024, Xockets initiated legal proceedings against Nvidia and Microsoft in the U.S. District Court for the Western District of Texas (case number 6:24-cv-00453-ADA). The suit alleges that Nvidia's 2020 acquisition of Mellanox led to infringement of Xockets' patents. Xockets contends that its patented "data processing units" (DPUs) are crucial components in systems developed by Nvidia and Microsoft, enabling improved performance by offloading tasks from server processors. Microsoft's substantial investment in OpenAI, a prominent figure in generative AI, and Nvidia's provision of data center equipment for AI development are also relevant to the case. Microsoft generates significant revenue by licensing Android-related patents to various smartphone manufacturers, including Samsung, HTC, and LG. Similarly, NVIDIA earns income through the licensing of its CUDA AI computing patents to cloud service providers.

The following table presents a summary of litigation outcomes, analyzing their impact on competition within the AI-driven datacenter market.

4.0 Conclusion

The rapid evolution of AI-driven data centers is reshaping the technology landscape, with intellectual property emerging as a decisive factor in establishing competitive advantage. As enterprise data generation accelerates and global patent activity intensifies—led by China’s commanding share and key innovators such as Intel and Samsung—companies must proactively navigate the IP landscape to secure foundational patents, drive innovation, and safeguard their market position. Patent litigation cases further emphasize IP's strategic and financial significance in this high-stakes market.

Companies are encouraged to leverage PatentVest’s insights to deeply understand the IP landscape, identify whitespace opportunities, assess competitor portfolios, and strategically inform their R&D and product development initiatives. Those who take decisive action now, investing in strategic intellectual property management, will not only shape the future of AI infrastructure but solidify their leadership in the global AI-driven economy.