Neuromorphic Computing Market Size, Share & Growth
Neuromorphic Computing Market by Offering (Processor, Sensor, Memory, Software), Deployment (Edge, Cloud), Application (Image & Video Processing, Natural Language Processing (NLP), Sensor Fusion, Reinforcement Learning) - Global Forecast to 2030
OVERVIEW
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
The neuromorphic computing market is projected to reach USD 1325.2 million by 2030 from USD 28.5 million in 2024, at a CAGR of 89.7% from 2024 to 2030. The growth of the neuromorphic computing market is driven by rising demand for ultra-low-power AI processing, increasing adoption of edge intelligence in robotics and IoT devices, and advancements in brain-inspired architectures enabling real-time learning and perception.
KEY TAKEAWAYS
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By RegionThe North America neuromorphic computing market accounted for a 35.6% revenue share in 2023.
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By OfferingBy offering, the software segment is expected to register the highest CAGR of 94.0%.
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By DeploymentBy deployment, the cloud segment is projected to grow at the fastest rate from 2024 to 2030.
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By applicationBy application, the Image & video processing segment is expected to dominate the market.
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By VertcialBy vertcial, the automotive segment will grow the fastest during the forecast period.
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Competitive LandscapeCompany Intel Corporation (US), IBM (US), and Qualcomm Technologies, Inc. (US) were identified as some of the star players in the neuromorphic computing market (global), given their strong market share and product footprint.
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Competitive LandscapeCompanies Natural Intelligence (US), Prophesee.ai (France), and Innatera Nanosystems BV (Netherlands), among others, have distinguished themselves among startups and SMEs by securing strong footholds in specialized niche areas, underscoring their potential as emerging market leaders
The neuromorphic computing market is witnessing strong growth, driven by rising demand for ultra-low-power, real-time AI processing in edge devices, autonomous systems, and advanced sensors. New deals and developments, including collaborations between chipmakers and research institutes, investments in brain-inspired architectures, and innovations in spiking neural networks and event-based vision technologies, are accelerating commercialization and reshaping the competitive landscape.
TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS
Neuromorphic computing is being increasingly adopted in applications such as autonomous vehicles, robotics, medical devices, and advanced driver assistance systems (ADAS). As these areas mature, traditional market growth potential may slow down. However, emerging application areas like edge AI, spiking neural networks, healthcare robotics, IoT, and wearables present new opportunities for revenue generation in the future.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
MARKET DYNAMICS
Level
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Rising adoption of neuromorphic hardware
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Need for alternative approaches to enhance computational power
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Lack of R&D investments
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Complexity of algorithms
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Fault-tolerant nature
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Increasing adoption in healthcare sector
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Complications associated with software development
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Complexities linked with developing computational models
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Driver: Rising adoption of neuromorphic hardware
Neuromorphic ICs will become a standard in high-performance computing, driving innovations and efficiency improvements across various industries due to their superior performance and energy efficiency compared to traditional ICs.
Restraint: Lack of R&D investments
Limited funding and slow progress in neuromorphic research will hinder immediate advancements and the development of practical applications, delaying market growth. As awareness and interest grow, increased investment and R&D efforts will mitigate this restraint, gradually accelerating development and real-world applications.
Opportunity: Fault-tolerant nature
Initial implementations will focus on enhancing autonomous vehicle navigation and optimizing space mission operations. Widespread adoption is expected, with significant advancements in autonomous driving and space exploration capabilities due to improved real-time data processing and decision-making.
Challenge: Complications associated with software development
Initial challenges will persist in developing software that can effectively utilize diverse neural hardware platforms, limiting widespread adoption in specialized applications. Standardization efforts and advancements in software tools will mitigate compatibility issues, fostering broader adoption across industries
NEUROMORPHIC COMPUTING MARKET SIZE, SHARE & GROWTH: COMMERCIAL USE CASES ACROSS INDUSTRIES
| COMPANY | USE CASE DESCRIPTION | BENEFITS |
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Neuromorphic chips used for real-time gesture recognition, autonomous robotics navigation, and sparse sensor data processing. | Ultra-low power processing, millisecond-level inference, improved edge AI performance. |
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Deploys neuromorphic systems for pattern recognition and large-scale neural simulations in research labs. | Massive parallelism, reduced computational load, highly energy-efficient training/inference. |
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Event-based neuromorphic vision sensors integrated into industrial inspection cameras. | High-speed motion tracking, reduced latency, lower data rates than traditional camera sensors. |
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Neuromorphic processors embedded in wearables and AR devices. | Always-on sensing with microwatt-level power consumption and instant response. |
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET ECOSYSTEM
The neuromorphic computing market ecosystem involves various categories of companies, organizations, and entities that play essential roles in developing, manufacturing, distributing, and utilizing neuromorphic computing.
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET SEGMENTS
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Neuromorphic Computing Market, By Offering
Processor segment will hold high market share during the forecast period. The market growth is credited to their ability to handle tasks like pattern recognition and adaptive learning more efficiently by replicating neural network structures in hardware. Neuromorphic processors are designed to address several limitations of conventional processors, particularly in AI and machine learning.
Neuromorphic Computing Market, By Deployment
Edge segment to hold largest market share in neuromorphic computing market during the forecast period. As businesses continue to prioritize low-latency, energy efficiency and real-time processing, the adoption of edge AI solutions is expected to accelerate, further driving growth in this segment.
Neuromorphic Computing Market, By Application
Natural language processing is one of the promising applications of neuromorphic computing that leverage the brain-inspired design of spiking neural networks (SNNs) to enhance the efficiency and accuracy of language data processing. The rise in demand for real-time and efficient language processing in devices like smartphones to IoT devices, necessitates low-power, high-performance solutions driving NLP demand in neuromorphic computing market
Neuromorphic Computing Market, By Vertical
Consumer electronics segment is projected to hold major share in neuromorphic computing market during the forecast period. Smartphones benefit from the neuromorphic technology's ability to handle power-hungry operations like biometrics more efficiently.There is also growing demand for wearables in personal health and fitness, underscoring the importance of neuromorphic computing.
REGION
Asia Pacific to be fastest-growing region in global neuromorphic computing market during forecast period
Asia Pacific will grow at a high rate during the forecasted period. APAC governments are actively investing in AI technology, by dedicating considerable resources in development of AI infrastructure. Since several new market players have shown their interest in neuromorphic computing and have escalated their investments in the developing technologies, the market is expected to see higher growth rate in the near future.
NEUROMORPHIC COMPUTING MARKET SIZE, SHARE & GROWTH: COMPANY EVALUATION MATRIX
In the neuromorphic computing market matrix, Intel Corporation (Star) leads with a strong market share and a broad technology footprint, driven by its Loihi neuromorphic processors and deep ecosystem collaborations across robotics, edge AI, and research institutions. BrainChip (Emerging Leader) is gaining momentum with its Akida platform, offering ultra-low-power, event-based processing that is increasingly recognized in automotive, IoT, and embedded AI applications.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
KEY MARKET PLAYERS
- Intel Corporation (US)
- BrainChip, Inc. (Australia)
- IBM (US)
- SynSense (China)
- MediaTek Inc. (Taiwan)
- NXP Semiconductors (Netherlands)
- Qualcomm Technologies, Inc. (US)
- Advanced Micro Devices, Inc. (US)
- Hewlett Packard Enterprise Development LP (US)
- SAMSUNG (South Korea)
MARKET SCOPE
| REPORT METRIC | DETAILS |
|---|---|
| Market Size in 2023 (Value) | USD 20.9 Million |
| Market Forecast in 2030 (Value) | USD 1,325.2 Million |
| Growth Rate | CAGR of 89.7% from 2024-2030 |
| Years Considered | 2020-2030 |
| Base Year | 2023 |
| Forecast Period | 2024-2030 |
| Units Considered | Value (USD Million), Volume (Thousand Units) |
| Report Coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Segments Covered |
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| Regions Covered | North America, Asia Pacific, Europe, RoW |
WHAT IS IN IT FOR YOU: NEUROMORPHIC COMPUTING MARKET SIZE, SHARE & GROWTH REPORT CONTENT GUIDE
DELIVERED CUSTOMIZATIONS
We have successfully delivered the following deep-dive customizations:
| CLIENT REQUEST | CUSTOMIZATION DELIVERED | VALUE ADDS |
|---|---|---|
| Chip Manufacturer | Comprehensive benchmarking of neuromorphic processors vs GPUs/ASICs | Analysis of spiking neural network (SNN) architectures |
| AI Hardware OEM | Workload mapping for neuromorphic suitability in vision, speech, robotics, and anomaly detection | Performance and accuracy comparison with traditional accelerators |
| Cloud & Edge Service Providers | Deployment feasibility for neuromorphic accelerators in edge nodes, micro-data centers, and hybrid architectures | Real-time inference benchmarking under varied workloads |
| Automotive & Robotics Firms | Detailed mapping of neuromorphic computing use cases in perception, sensor fusion, SLAM, real-time decision-making, and motion control | Benchmarking of response time and robustness under dynamic environments |
| Research Labs & Government Agencies | Technology scouting across global neuromorphic R&D hubs | IP and patent landscape mapping |
RECENT DEVELOPMENTS
- May 2024 : BrainChip, Inc. partnered with Frontgrade Gaisler, a leader in RISC-V processor development for space applications, to create a groundbreaking integration. This partnership brings together BrainChip’s Akida neuromorphic processor with Frontgrade Gaisler’s fault-tolerant, radiation-hardened microprocessors.
- April 2024 : Intel Corporation launched Hala Point, the world's largest neuromorphic system, at Sandia National Laboratories. Utilizing Loihi 2 processors supports brain-inspired AI research and improves efficiency and sustainability. The system offers over ten times more neuron capacity and up to 12 times higher performance than previous systems.
- September 2023 : SynSense launched the XyloIMU neuromorphic development kit for IMU-based motion processing applications, including human movement analysis and industrial monitoring. The kit integrates with Rockpool, SynSense’s open-source Python toolchain, allowing developers to train and deploy SNN models and fostering exploration of new use cases and research applications.
- COLUMN 'A' SHOULD BE IN TEXT FORMAT AND NOT DATE FORMAT :
Table of Contents
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Methodology
The research process for this technical, market-oriented, and commercial study of the neuromorphic computing market included the systematic gathering, recording, and analysis of data about companies operating in the market. It involved the extensive use of secondary sources, directories, and databases (Factiva, Oanda, and OneSource) to identify and collect relevant information. In-depth interviews were conducted with various primary respondents, including experts from core and related industries and preferred manufacturers, to obtain and verify critical qualitative and quantitative information as well as to assess the growth prospects of the market. Key players in the neuromorphic computing market were identified through secondary research, and their market rankings were determined through primary and secondary research. This included studying annual reports of top players and interviewing key industry experts, such as CEOs, directors, and marketing executives.
Secondary Research
In the secondary research process, various secondary sources were used to identify and collect information for this study. These include annual reports, press releases, and investor presentations of companies, whitepapers, certified publications, and articles from recognized associations and government publishing sources. Research reports from a few consortiums and councils were also consulted to structure qualitative content. Secondary sources included corporate filings (such as annual reports, investor presentations, and financial statements); trade, business, and professional associations; white papers; Journals and certified publications; articles by recognized authors; gold-standard and silver-standard websites; directories; and databases. Data was also collected from secondary sources, such as the International Trade Centre (ITC) (Switzerland), and the International Monetary Fund (IMF).
List of key secondary sources
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Web Link |
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IEEE |
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U.S. Department of Energy |
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Open Neuromorphic |
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IOPscience |
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NIST |
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Data Science Association |
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Sandia National Laboratories |
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National Library of Medicine |
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Los Alamos National Laboratory |
Primary Research
Extensive primary research was accomplished after understanding and analyzing the neuromorphic computing market scenario through secondary research. Several primary interviews were conducted with key opinion leaders from both demand- and supply-side vendors across four major regions—North America, Europe, Asia Pacific, and RoW. Approximately 30% of the primary interviews were conducted with the demand side, and 70% with the supply side. Primary data was collected through questionnaires, emails, and telephonic interviews. Various departments within organizations, such as sales, operations, and administration, were contacted to provide a holistic viewpoint in the report.
Note: Other designations include technology heads, media analysts, sales managers, marketing managers, and product managers.
The three tiers of the companies are based on their total revenues as of 2023 ? Tier 1: >USD 1 billion, Tier 2: USD 500 million–1 billion, and Tier 3: USD 500 million.
About the assumptions considered for the study, To know download the pdf brochure
Market Size Estimation
In the complete market engineering process, both top-down and bottom-up approaches were used, along with several data triangulation methods, to estimate and forecast the size of the market and its segments and subsegments listed in the report. Extensive qualitative and quantitative analyses were carried out on the complete market engineering process to list the key information/insights pertaining to neuromorphic computing market.
The key players in the market were identified through secondary research, and their rankings in the respective regions determined through primary and secondary research. This entire procedure involved the study of the annual and financial reports of top players, and interviews with industry experts such as chief executive officers, vice presidents, directors, and marketing executives for quantitative and qualitative key insights. All percentage shares, splits, and breakdowns were determined using secondary sources and verified through primary sources. All parameters that affect the markets covered in this research study were accounted for, viewed in extensive detail, verified through primary research, and analyzed to obtain the final quantitative and qualitative data. This data was consolidated, supplemented with detailed inputs and analysis from MarketsandMarkets, and presented in this report.
Bottom-Up Approach
- Identifying various verticals of neuromorphic computing
- Analyzing the penetration of each type of neuromorphic computing technology through secondary and primary research
- Analyzing the penetration of neuromorphic computing for different applications and verticals through secondary and primary research
- Conducting multiple discussion sessions with key opinion leaders to understand the detailed working of neuromorphic computing and their implementation in multiple applications; this helped analyze the break-up of the scope of work carried out by each major company
- Verifying and cross-checking the estimates at every level with key opinion leaders, including CEOs, directors, operation managers, and finally with MarketsandMarkets domain experts
- Studying various paid and unpaid sources of information, such as annual reports, press releases, white papers, and databases
Top-Down Approach
- Focusing initially on the top-line investments and expenditures being made in the ecosystem of the neuromorphic computing market; further, splitting the key market areas based on offering, deployment, application, vertical, and region, and listing the key developments
- Identifying all leading players and applications in the neuromorphic computing market based on region through secondary research and thoroughly verifying them through a brief discussion with industry experts
- Analyzing revenues, product mix, geographic presence, and key applications served by all identified players to estimate and arrive at percentage splits for all key segments
- Discussing splits with the industry experts to validate the information and identify key growth pockets across all key segments
- Breaking down the total market based on verified splits and key growth pockets across all segments
Neuromorphic Computing Market : Top-Down and Bottom-Up Approach
Data Triangulation
After arriving at the overall market size from the market size estimation process explained above, the total market was split into several segments and subsegments. Data triangulation and market breakdown procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The data was triangulated by studying various factors and trends from both demand and supply sides. Along with this, the market size was validated using both top-down and bottom-up approaches.
Market Definition
Neuromorphic computing is a cutting-edge approach to designing computing systems that mimic the structure and functioning of the human brain's neural networks. It involves the development of hardware and software that replicate the way neurons communicate and process information, using specialized architectures like spiking neural networks (SNNs). Neuromorphic systems are highly energy-efficient, capable of real-time learning, and can process complex sensory data, such as images and sounds, with minimal power consumption. This technology is used in applications ranging from AI and robotics to healthcare, autonomous vehicles, and edge computing. These are used across various industries like consumer electronics, aerospace & defense, automotive, industrial, medical, IT & telecommunication, others.
Key Stakeholders
- Neuromorphic computing device manufacturers
- Research organizations and universities
- Original equipment manufacturers (OEMs)
- Technology standard organizations, forums, alliances, and associations
- Analysts and strategic business planners
- Government bodies, venture capitalists, and private equity firms
- Existing and prospective end users
- Venture capitalists, private equity firms, and startup companies
- Distributors and traders
Report Objectives
- To define, describe, segment, and forecast the neuromorphic computing market size, in terms of value, based on offering, deployment, application, vertical, and region
- To forecast the market size, in terms of value, across North America, Europe, Asia Pacific, and the Rest of the World (RoW)
- To present detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and challenges)
- To provide an ecosystem analysis, case study analysis, patent analysis, technology analysis, ASP analysis, Porter’s Five Forces analysis, investment and funding scenario, and regulations pertaining to the market.
- To offer a comprehensive overview of the value chain of the neuromorphic computing market ecosystem
- To critically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
- To strategically profile the key players and comprehensively analyze their market shares and core competencies
- To assess the opportunities in the market for stakeholders and describe the competitive landscape of the market
- To analyze competitive developments in the market, such as collaborations, agreements, partnerships, product developments, and research and development (R&D)
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Growth opportunities and latent adjacency in Neuromorphic Computing Market