Neuromorphic Computing Market Size, Share and Trends 2025 to 2034

Neuromorphic Computing Market Size and Forecast 2025 to 2034

The global neuromorphic computing market size was calculated at USD 6.90 billion in 2024 and is predicted to reach around USD 47.31 billion by 2034, expanding at a CAGR of 21.23% from 2025 to 2034. The increased demand for AI and ML in industries is driving the growth of the global market. Advancements in neurotechnology are increasing the adoption of neuromorphic computing.

Neuromorphic Computing Market Key Takeaways

• North America dominated the global neuromorphic computing market with the largest market share of 37% in 2024.
• Asia Pacific is anticipated to grow at a double digit CAGR of 22.71% over the forecast period.
• By component, the hardware segment contributed the biggest market share of 80% in 2024.
• By component, the software segment is predicted to expand rapidly during the forecast period.
• By application, the image processing segment has held a major market share of 46% in 2024.
• By application, the data processing segment is estimated to grow at the fastest rate during the forecast period.
• By end-use, the consumer electronics segment accounted for the largest share of the market in 2024.
• By end-use, the automotive segment is expected to witness significant growth in the forecast period.
• By deployment, the edge segment held the largest market share in 2024.
• By deployment, the cloud segment is anticipated to grow at a remarkable CAGR during the forecast period.

How Artificial Intelligence (AI) Works Along with Neuromorphic Computing

Artificial intelligence integration is a significant player in cutting-edge technologies; the neuromorphic computing market is not an exception. The need for neuromorphic computing has increased due to the rising complexity of artificial intelligence and machine learning technology. However, the combination of these two technologies is creating a promising future for technology across various sectors. AI is able to improve speed and image recognition in neuromorphic computing. With growing innovation for the development of advanced neuromorphic computing, AI integration remains and will bring steady importance. The ongoing promotion of AI programs to understand computing more accurately and effectively among academic institutes is a significant factor in transforming neuromorphic computing innovations and development.

• In May 2024, Cornell Tech collaborated with BrainChip, the world’s first commercial producer of neuromorphic artificial intelligence, to develop a novel course in neuromorphic computing for university graduate students by joining the company’s University AI Accelerator Program.

U.S. Neuromorphic Computing Market Size and Growth 2025 to 2034

The U.S. neuromorphic computing market size was exhibited at USD 1.76 billion in 2024 and is projected to be worth around USD 12.33 billion by 2034, growing at a CAGR of 21.49% from 2025 to 2034.

North America dominated the global neuromorphic computing market with the largest market share in 2024 due to its regional base for early adoption of neuromorphic technology. The presence of a competitive landscape contributes to the growth of the North American market. Factors like rising consumer electronics utilization, industrialization, and an advancing healthcare sector are shaping the North American market. The growing adoption and advancements in cutting-edge technologies, including AI, ML, deep learning, and IoT technology, are creating a high demand for neuromorphic computing in the region.

The United States is leading the regional market due to the presence of well-established research institutes and key companies in the country. Additionally, ongoing studies and neuroscience advancements, including functional magnetic resonance imaging and electroencephalography (EEG), are contributing significantly to countries' markets. On the other hand, Canada is projected to grow rapidly in North America due to the rising adoption of consumer electronics and a large base of the Canadian marketing and advertising industry.

Asia Pacific is anticipated to witness significant growth in the neuromorphic computing market over the forecast period due to the rising adoption of advanced technologies, including AI, ML, IoT devices, and neural networks, across industries in the region. The expanding industrialization, government support, and investments in industries are allowing access to such technologies. Asian governments are playing a crucial role in advancing research institutes and digital infrastructure, making it possible to share in the growth. Additionally, the rising collaboration and partnerships among key companies with government and research institutes are leveraging the market.

India is the second-largest country dominating the neuromorphic computing market due to growing government focus and investments in AI developments in the country. Additionally, the government term for ‘Digital India” contributes to the share in market growth. With growing research and development activities, India is expected to witness further market growth in the forecast period. 

China is leading the regional market due to government initiatives such as ‘Made in China’ and investments in AI research and the semiconductor sector. Furthermore, countries like Japan and South Korea are significantly fueling regional markets due to their well-established cutting-edge AI infrastructure, advanced R&D sectors, and government initiatives.

• In September 2024, researchers at the Indian Institute of Science (IISc) introduced a brain-inspired analog computing platform. This platform is able to store and process data in 16,500 conductance states within a molecular film.

Market Overview

Neuromorphic computing, or chips, mimics the human brain's functions and understandings and converts them into required commands or processing. The rising importance of neuromorphic computing in artificial intelligence (AI), ML, deep learning, IoT devices, and cognitive computing is a key transformer of the global neuromorphic computing market. The rising complexity in cutting-edge technologies regarding data analytics or processing is a major reason behind the increased adoption of neuromorphic computing.

The ongoing collaborations between academic institutes and market key players and government investments in research institutes are shaping market growth. The growing adoption of cutting-edge technologies like AI and ML in various industries is driving the need for neuromorphic chips to handle the complexity of such technology. Additionally, the rising demands for automotive and robotics are raising the need for neuromorphic computing.

Neuromorphic Computing Market Growth factors

• Advancements in neuroscience: The advancements in neuroscience include the enhancement of understanding of brain function and the improvement of the effectiveness of neuromorphic computing, making them more popular in various industries.
• Government initiatives: The rising government support and investments in digitalization encourage the adoption of cutting-edge computing, including neuromorphic computing.
• Rising demand for edge technology: The demand for edge technologies, including edge computing, AI, and Internet of Things (IoT) technologies, has increased, which requires neuromorphic computing to reduce power consumption and improve process efficiency.

Market Scope

Market Dynamics

Driver

Increased adoption of newer technologies

The rising adoption of robotics in industrialization-driven growth of the neuromorphic computing market. Furthermore, there is a surge in the adoption of AI and ML applications in expanding industries, including healthcare, academics, automotive, and pharmaceuticals, which is leveraging the growth of the market. AI and ML applications have become more complex and data-intensive; the need for more computing power and memory for such applications has increased the adoption of neuromorphic computing.

The need for real-time monitoring for the processing of ML applications has surged the demand for neuromorphic computing, as this computing provides real-time processing by mimicking the brain's ability. Advancements in chip architecture, including memristor-based chips, are able to provide more efficiency and computing power. Additionally, with the growing demand for edge AI applications, the market is expected to expand further in the forecast period.

Restraint

Regulatory challenges

The regulatory uncertainty and lack of standards for neuromorphic computing are the major restraints of the market. Neuromorphic computers have very limited standards for data formats and communication protocols, which has made it difficult for them to gain regulatory support. The challenges of data protection and security are limiting the adoption of such computing in the healthcare sector. 

The neuromorphic computing market handles sensitive information, which causes the risk of cyber threats, the fear of production damage, and liability, making it hard to adopt such computing in major industries. The regulatory compliance for limiting application access to neuromorphic computing and regulatory protective information in healthcare is hampering the adoption of these chips in the sector.

Opportunity

Biometric advancements

The increased adoption of advanced biometric systems in security, electronic identification, and authentication is creating significant growth opportunities for the global neuromorphic computing market. Neuromorphic computing is able to analyze EEG data and detect patterns, which makes it essential in the electronic identification process. Similarly, the ability of these chips to process brain signals and convert them into commands is making it easier for industrialization.

Biometric functions, including fingerprints, facial traits, speech patterns, and handwriting speed, need to be optimized, and neuromorphic chips not only help optimize but also improve such cognitive functions. The rising adoption of AI biometrics in the field leverages the requirement of neuromorphic computing to improve the dependability, efficiency, and safety of biometric identification systems.

Component Insights

The hardware segment led the global neuromorphic computing market in 2024. The demand for neuromorphic computing has increased to handle complex data processing among various industries. The development of customized hardware chips has had a significant impact on market growth. Also, the advancements in memristor technology are drawing ways for the growth of scalable neuromorphic computing hardware. Moreover, ongoing innovations in the development of cognitive computing are emerging in the segment expansion.

• In September 2024, Purdue University's Center for Brain-inspired Computing (C-BRIC) announced the advancement of cognitive computing with a USD 32 million project aimed at developing neuro-inspired algorithms and neuromorphic hardware, which will enable autonomous intelligent systems.

On the other hand, the software segment is predicted to expand rapidly during the forecast period due to the rising adoption of edge computing. Advancements in edge technologies such as AI, ML, deep learning, edge computing, and IoT devices are shaping the segment's success. The growing companies’ investments in building and developing neural networks are enhancing the efficiency of neuromorphic computing. 

Application Insights

The image processing segment contributed the highest neuromorphic computing market share in 2024. The segment growth is attributed to the rising utilization of neuromorphic computing in computer vision applications. The rising adoption of neuromorphic computing for medical imaging is the major factor driving the segment growth. Neuromorphic computing is widely used in automotive vehicles for object detection and image processing. Similarly, it is a major player in the real-time processing of images in surveillance. The ability of neuromorphic computing to provide high-speed image processing is raising its utilization.

On the other hand, the data processing segment is estimated to grow at the fastest rate during the forecast period due to the increased utilization of neuromorphic chips in data processing applications. The rising complexity of data requires predictive data analytics, real-time data processing, and unauthorized detections. The ability of neuromorphic computing to simulate human brain functions is advantageous in data processing. Additionally, the need for high-speed data processing with more accuracy and minimal power consumption highlights the need for neuromorphic computing in data processing applications.

End-Use Insights

The consumer electronics segment accounted for the largest share of the neuromorphic computing market in 2024. The segment growth is driven by increased demands for consumer electronics, including smartwatches, smartphones, laptops, remote controls, tablets, and PCs. The growing digitalization requires neuromorphic computing in the consumer electronics industry. Moreover, the integration of AI and ML in such devices has surged demand for neuromorphic computing. Moreover, the adoption of smart home devices, wearable devices, and gaming consoles is projected to transform the market condition in the upcoming period.

However, the automotive segment is expected to witness significant growth in the forecast period due to the increased adoption of autonomous vehicles. The surge for electrification and network connections in vehicles is driving the need for neuromorphic computing in automotive vehicles. The rising adoption of advanced driver-assistance systems (ADAS) is attributed to the segment's growth. The ability of neuromorphic computing to analyze human brain functions and provide advanced sensors, real-time processing, safety commands, and autonomous decision-making is raising their preference for automotive vehicles. The growing adoption of electric vehicles (EVs) is significantly impacting the adoption rate of neuromorphic computing.

Deployment Insights

The edge segment held the largest neuromorphic computing market share in 2024 due to the rising adoption of edge computing and edge AI in industries like healthcare, automotive, and academics. The rising use of edge AI for real-time monitoring and decision-making applications is driving the need for neuromorphic computing. The rising adoption of wireless devices is fueling the neuromorphic computing demands. Additionally, the ability of this computing to work in low-power applications is making them popular.

• In September 2023, the Xylo IMU neuromorphic development kit and improvement pack was launched by SynSense, which allows ultra-low-power applications for smart wearables and industrial monitoring devices.

The cloud segment is anticipated to grow at a remarkable CAGR during the forecast period. The segment growth is accounted for by the rising adoption of cloud-based neuromorphic computing due to its high scalability and flexibility ability. Cloud-based neuromorphic computing helps to reduce hardware, software, and infrastructure costs. The ability of neuromorphic computing to provide advanced accessibility for organizations is increasing the popularity of cloud-based neuromorphic computing.

Neuromorphic Computing Market Companies

• Intel Corporation
• IBM Corporation
• Brain Corporation
• CEA-Leti
• General Vision Inc.
• HRL Laboratories, LLC
• Samsung Electronics Co. Ltd
• BrainChip, Inc.
• Vicarious
• Qualcomm Technologies, Inc.
• Knowm Inc.

Latest Announcements by Industry Leaders

• In September 2024, Navakanta Bhat, Professor at CeNSE and an expert in silicon electronics, announced that: “The India Semiconductor Mission will be a game changer, revolutionizing industrial, consumer, and strategic applications. And the country's importance in this context cannot be overstated.”
• In April 2024, Mike Davies, director of the Neuromorphic Computing Lab at Intel Labs, announced that “the Hala Point and its relevant research will advance the adaptability and efficiency of large-scale AI technology.”

Recent Developments

• In April 2024, Intel launched the world's largest 1.15 billion-neuron neuromorphic system, Hala Point, a large-scale system designed to support future brain-inspired artificial intelligence (AI) and improve the efficiency, sustainability, and scalability of AI.
• In November 2024, in order to reduce complex algorithms on IBM quantum computers with record levels of scale, speed, and accuracy, IBM advanced its quantum hardware and software.

Segments Covered in Report

By Component 

• Hardware
• Software
• Services

By Application

• Signal Processing
• Image Processing
• Data Processing
• Object Detection
• Others

By End-Use

• Consumer Electronics
• Automotive      
• Healthcare       
• Military and Defense        
• Others

By Deployment 

• Edge
• Cloud

By Geography

• North America
• Asia Pacific
• Europe
• Latin America
• Middle East and Africa