Neuromorphic Computing Market Set for Explosive Growth to USD 6,801.9 Million by 2030, Led by North America's 35% Market Share | Key Players - Intel Corporation, IBM Corporation, Qualcomm Technologies, Inc

The Global Neuromorphic Computing Market reached USD 48.3 million in 2022 and is projected to witness lucrative growth by reaching up to USD 6,801.9 million by 2030. The global neuromorphic computing market is expected to exhibit a CAGR of 91.5% during the forecast period (2024-2031).

Market growth is driven by surging demand for energy-efficient AI processing, rapid advancements in brain-inspired chip architectures like Intel's Loihi and IBM's TrueNorth, and expanding applications in edge computing, robotics, and autonomous systems. Increasing investments from tech giants such as Qualcomm and SynSense, alongside breakthroughs in spiking neural networks and hardware-software co-design, are further propelling adoption across IoT, healthcare diagnostics, and defense sectors.

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Key Industry Developments
United States:
✅ January 2026: Intel Corporation launched the Loihi 3 neuromorphic chip, featuring 10x improved energy efficiency for edge AI applications in AgTech, enabling real-time crop monitoring with spiking neural networks that mimic brain-like processing for low-power precision agriculture.

✅ December 2025: IBM Research unveiled a neuromorphic accelerator for smart sensors, certified under new EPA guidelines for low-emission IoT devices in sustainable farming.
This development targets vertical farming innovations, with initial deployments optimizing water and nutrient delivery via neuromorphic edge computing.

✅ October 2025: SynSense released a neuromorphic vision sensor for US AgTech robotics, gaining USDA nod for integration in automated harvesting systems.

Asia Pacific / Japan:
✅ January 2026: Sony Corporation introduced the next-gen Intelligent Vision Sensor (IMS) with neuromorphic processing, tailored for Japan's precision agriculture robots under MAFF subsidies.

✅ November 2025: Prophesee and Samsung co-launched a neuromorphic event-based camera chip for APAC smart farming, approved for Japan's green tech incentives.

✅ October 2025: Fujitsu Laboratories debuted a neuromorphic prototype for earthquake-resilient AgTech sensors, backed by Japanese regulatory fast-tracking for disaster-proof IoT.

Strategic Mergers and Acquisitions:
✅ SoftBank Group acquired Ampere Computing for approximately $6.5 billion in March 2025, enhancing its energy-efficient AI and processor design capabilities with neuromorphic-adjacent technologies.act centers.

Key Players:
Brain Corporation | CEA-Leti | General Vision, Inc. | Hewlett Packard Company | HRL Laboratories, LLC | International Business Machines Corporation | Intel Corporation | Knowm Inc. | Qualcomm Technologies, Inc. | Samsung Electronics Co., Ltd.

Strategic Leadership Report: Top 5 Players in Neuromorphic Computing Market 2026
-Intel Corporation: Advanced the Loihi 2 neuromorphic chip with enhanced on-chip learning capabilities, enabling ultra-low-power edge AI for real-time pattern recognition in robotics and autonomous systems.

-IBM Corporation: Progressed TrueNorth successor architectures integrating neuromorphic processing with hybrid AI workflows, optimizing energy-efficient deep learning for large-scale data analytics in healthcare and defense applications.

-BrainChip Holdings Ltd.: Deployed the Akida neuromorphic processor platform with event-based spiking neural networks, delivering scalable, temporal inference for IoT vision and sensor fusion at sub-milliwatt power levels.

-Qualcomm Technologies, Inc.: Introduced Zeroth-inspired neuromorphic IP within Snapdragon platforms, featuring adaptive learning engines for always-on context awareness in mobile devices and automotive edge computing.

-Samsung Electronics Co., Ltd.: Developed neuromorphic memory-in-memory architectures using advanced 3D-stacked DRAM, accelerating AI training with analog spiking neurons for high-throughput applications in consumer electronics and data centers.

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Regional Insights:
-North America: 35% (Largest share, driven by advanced AI research and key players like Intel and IBM).

-Asia Pacific: 27% (Fastest growing, fueled by rapid AI and IoT adoption in China, India, and Japan).

-Europe: 21% (Supported by neuromorphic chip investments and digital reforms in Germany and the UK).

Key Growth Drivers:
-Surging demand for AI and machine learning applications that require brain-like, efficient processing.

-Rising need for energy-efficient computing solutions in edge devices and data-intensive tasks.

-Advancements in neuromorphic hardware, including chips mimicking neural architectures for faster performance.

-Expanding use in autonomous systems, robotics, and self-driving vehicles for real-time decision-making.

-Increased investments in R&D and collaborations driving innovation in cognitive and event-driven computing.

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Market Segmentation Analysis:
-By Offering: Hardware Leads with Core Processing Power
Hardware dominates at 62% market share in 2024, providing specialized neuromorphic chips like IBM TrueNorth and Intel Loihi for efficient, brain-inspired parallel processing in AI tasks.
Software holds 38%, enabling algorithm optimization, simulation, and integration for neuromorphic systems, with growth from open-source frameworks.

-By Deployment: Edge Computing Prevails for Real-Time Efficiency
Edge computing captures 58% share, ideal for low-latency, power-efficient inference in IoT devices and autonomous systems mimicking neural adaptability.
Cloud computing accounts for 42%, supporting scalable training and large-scale data analytics via neuromorphic cloud platforms.

-By Application: Image Recognition Tops with AI Demand
Image recognition leads at 35%, leveraging spiking neural networks for superior object detection and vision processing in surveillance and robotics.
Signal recognition follows at 25%, excelling in audio/pattern analysis; data mining at 20% for efficient big data pattern extraction; others (e.g., NLP, control systems) at 20%.

-By End-user: Consumer Electronics Commands Largest Share
Consumer electronics holds 28% share, powering smart devices with energy-efficient AI like voice assistants and cameras.
Automotive takes 22% for ADAS and autonomous driving; IT & Telecom 18%; Aerospace & Defense 15%; Healthcare 12%; Others 5%.

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