Neuromorphic Chip Market Report Scope & Overview:

Neuromorphic Chip Market Size was valued at USD 44.77 Million in 2023 and is expected to reach USD 2734.8 Million by 2031 and grow at a CAGR of 67.2% over the forecast period 2024-2031.

A neuromorphic chip, an application-specific integrated circuit (ASIC) microchip, is crafted to replicate the functionalities of the human nervous system and brain. This involves leveraging software solutions and very-large-scale-integrated (VLSI) systems to emulate human cognition and perception. Enhanced with artificial synapses and neurons, fabricated using silicon, these chips facilitate processing akin to the human brain's capabilities. Increasingly, neuromorphic chips are being integrated with AI and machine learning systems to enhance data processing and decision-making. The burgeoning neuromorphic chip market is fueled by its capacity to mimic the processing prowess of the human brain, offering efficient, low-power, and real-time data processing capabilities prized in diverse industries. The fundamental objective of neuromorphic chips is to augment the efficiency of AI systems, particularly in resource-constrained settings, by harnessing the energy-efficient principles of the human brain.

Neuromorphic Chip Market Revenue Analysis

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  • It is usually focused on either fast computation or low power.

  • Better-performing integrated circuits, increased demand for artificial intelligence and machine learning, and an increase in the number of cross-industry alliances and collaborations.

The progression of integrated circuits and semiconductor technology has resulted in enhanced ICs that can manage increasingly intricate computational tasks. This enhancement in performance has sparked a surge in the demand for AI and ML technologies across diverse sectors, including healthcare, finance, automotive, and manufacturing. AI and ML applications often necessitate substantial computational capabilities to efficiently process extensive datasets and train intricate models. Furthermore, the widespread adoption of AI and ML has spurred a rise in collaborative efforts and partnerships spanning multiple industries. Companies are joining forces to capitalize on each other's expertise and resources, facilitating innovation acceleration and the resolution of shared challenges. These partnerships may entail technology firms collaborating with sector-specific enterprises to develop AI-driven solutions tailored to specific use cases or industries, thus propelling further progress in AI and ML technologies. In essence, the combination of improved integrated circuits, escalating demand for AI and ML, and increased collaboration among industry stakeholders is reshaping the Chip landscape and fostering innovation across various sectors.


  • Technological immaturity regarding neuromorphic chip technology.

While neuromorphic chips show great potential across various applications, they are still in the developmental stage, encountering several significant hurdles before achieving widespread adoption. These challenges revolve around intricate issues in design, fabrication, and software tools. Designing neuromorphic chips involves complex processes aimed at emulating the functions of the human brain, while achieving precision in fabrication poses technical challenges. Moreover, the development of specialized software tools is crucial to enhance performance and compatibility with existing systems. Addressing these challenges is paramount to ensure the reliability and scalability of neuromorphic chip technology for broader acceptance. Additionally, the considerable cost associated with neuromorphic chip development and manufacturing presents a notable barrier to accessibility, mainly due to the intricacies of design, specialized equipment requirements, and limited production scale. Efforts to mitigate these cost barriers, such as increased research investment and economies of scale in manufacturing, are indispensable for improving affordability and accessibility. Furthermore, the dynamic ecosystem surrounding neuromorphic chips presents integration challenges, including a scarcity of specialized software tools and expertise among application specialists. To bolster and expand the neuromorphic chip ecosystem, fostering collaboration, investing in education and training initiatives, and promoting interdisciplinary research endeavors are crucial steps. Successfully overcoming these challenges has the potential to unlock breakthroughs in fields such as artificial intelligence, robotics, and neuroscience.Top of Form


The integration of speech recognition or biometric recognition technologies entails incorporating systems capable of precisely identifying and understanding spoken language or distinctive physical characteristics across a wide array of applications. Speech recognition technology empowers devices to comprehend human speech, transforming it into text or commands, thus facilitating its utilization in virtual assistants, dictation software, customer service systems, and smart home devices, ultimately enhancing user interaction and operational efficiency. Conversely, biometric recognition verifies and authenticates individuals based on biological traits like fingerprints, irises, faces, or voices, ensuring heightened security and precision in access control, identity verification, and law enforcement applications. Fueled by advancements in machine learning and computational capabilities, these technologies are progressively integrated into various sectors such as healthcare, finance, government, and retail, aiming to augment user experiences, fortify security measures, and streamline operational processes. Nevertheless, the prevalence of ethical and privacy concerns regarding the handling of sensitive biometric data underscores the imperative for cautious deliberation in their widespread adoption.


  • Ethical Considerations surrounding the advancement of neuromorphic chip technology.

As artificial intelligence (AI) capabilities advance, ethical issues concerning bias, fairness, and responsible development practices become increasingly relevant. Neuromorphic chips, with their capacity to replicate human-like cognitive processes, introduce ethical concerns regarding data privacy, algorithmic transparency, and societal impact. Developers must ensure that applications powered by neuromorphic chips adhere to ethical principles, fostering fairness, accountability, and transparency. Addressing these ethical considerations necessitates interdisciplinary collaboration among technologists, ethicists, policymakers, and stakeholders to establish guidelines, regulations, and best practices that prioritize the ethical and responsible utilization of neuromorphic chip technology. By integrating ethical considerations into the design, development, and implementation of neuromorphic chip-based systems, we can harness the transformative potential of this technology while mitigating potential risks and societal harms.


The COVID-19 epidemic has had an impact on the global neuromorphic computing market in a variety of verticals. Neuromorphic chips were first used in medical equipment in the year 2020. Watson, an analytical tool created by IBM Corp. (US), is designed to be linked with neuromorphic circuits and used for medical imaging analytics. Watson is a human-like analytical system. As a result, the medical industry's market is expected to grow. As a result of the pandemic, work from home (WFH) has become the new trend, increasing supply and demand for IT peripherals and propelling the neuromorphic computing market in the IT & telecommunications sector forward.


The Russia-Ukraine crisis has reverberated across various sectors, including electronics and semiconductors, indirectly impacting the neuromorphic chip market. Neuromorphic chips, which emulate the neural structures of the human brain, are driving advancements in AI and machine learning, addressing issues such as high-power consumption and inefficiency in traditional computing architectures. Particularly, these chips find increasing application in the automotive industry, notably in autonomous driving technologies, for their efficiency in classification tasks and performance in noisy environments. Companies like Intel and Brain Chip are actively developing neuromorphic chips for diverse applications, driven by their capacity to efficiently handle data-intensive tasks with lower power consumption.

However, the Russia-Ukraine conflict has introduced uncertainties and potential disruptions to the global semiconductor supply chain, indirectly impacting the development and deployment of neuromorphic chips. Geopolitical actions, such as the EU's restrictions on chip exports to Russia in response to the crisis, could have ripple effects on the semiconductor industry as a whole. While specific reports on the direct impact of the crisis on the neuromorphic chip market are scarce, it's evident that broader challenges faced by the semiconductor industry, exacerbated by geopolitical tensions, could influence the trajectory of neuromorphic chip development, production, and adoption. Nonetheless, ongoing innovations and partnerships in the field underscore its resilience and growth potential amidst these challenges.


Amidst the ongoing global economic slowdown, industries, including the neuromorphic chip market, experience diverse impacts, though specific details regarding its direct correlation remain elusive. Nonetheless, insights into general trends within the neuromorphic chip sector shed light on its response to prevailing economic conditions. Notably, the market demonstrates significant growth driven by rising demand for artificial intelligence-based microchips and the integration of neuroplasticity with electronics. Collaborations and advancements, such as Edge Impulse's enterprise-grade machine learning algorithms and SynSense's partnership with BMW for smart cockpit integration, underscore the market's dynamism and potential for innovation. Furthermore, robust competition among major players like IBM Corporation, Intel Corporation, and Qualcomm Incorporated intensifies, with a focus on new product developments and strategic alliances. Regionally, North America leads, buoyed by its strong presence across aerospace, defense, IT, and telecommunication sectors, while Europe and the Asia-Pacific region witness notable growth, particularly in France and China. Despite challenges posed by reduced investment and cautious R&D spending, persistent demand for AI and ML applications, alongside advancements in energy-efficient computing solutions, may mitigate these impacts. The market's emphasis on innovation and efficiency, combined with its diverse applications across industries, positions it well to navigate the complexities of the global economic landscape.



  • Software

  • Hardware

​​​​​​​​​​​​​​The Neuromorphic Chip market comprises two sub-segments: Hardware and Software. In 2023, the Software segment dominated with the largest market share. The push for miniaturization in integrated circuits is propelled by consumer demand for smaller, more cost-effective products. Industries such as smartphones, healthcare, and automotive extensively employ smart sensors and emergency smart technology. Consequently, recent years have witnessed a rise in the complexity of hardware design due to advancements in miniaturization technologies.

Neuromorphic Chip Market by Components


  • Signal Recognition

  • Image Recognition

  • Data Mining


  • Aerospace & Defense

  • Automotive

  • Industrial

  • It & Telecom

  • Medical

  • Others

​​​​​​​​​​​​​​In 2023, the Automotive segment secured the leading market share. Top-tier automotive manufacturers are making substantial investments to attain Level 5 autonomy in self-driving vehicles, leading to a surge in demand for artificial intelligence neuromorphic chips. To meet the stringent requirements of high throughput and low power consumption in the autonomous driving market, continuous enhancements in AI algorithms are essential. Neuromorphic circuits excel in classification tasks and offer versatility across various autonomous driving scenarios. Moreover, they demonstrate superior efficiency in noisy environments, such as self-driving cars, compared to conventional static deep learning methods.

Neuromorphic Chip Market By Vertical

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North America emerged as the frontrunner in the global market, and this dominance is anticipated to persist in the forthcoming forecast period. Meanwhile, the Asia-Pacific region is poised to exhibit the swiftest growth in the Neuromorphic Chip Market. The surge in adoption of neuromorphic Chip for security purposes is anticipated to propel market growth within this region. North America is projected to retain the lion's share of the global neuromorphic Chip market. This dominance is underpinned by widespread recognition of the benefits of neuromorphic Chip across key industries such as aerospace, military & defense, and medical. In North America, the United States leads the charge, leveraging artificial intelligence across sectors like medical and automotive for applications such as machine learning, natural language processing (NLP), image processing, and speech recognition. Conversely, the Asia-Pacific region is anticipated to capture the second-largest market share and exhibit the most rapid compound annual growth rate (CAGR). Within the APAC market, China, Japan, and South Korea are poised to be the primary contributors. Notably, China stands out as the predominant AI market in APAC, closely followed by Japan, thus positioning China as a promising market for neuromorphic Chip applications in machine learning and natural language processing.

Neuromorphic Chip Market By Region​​​​​​​


North America

  • US

  • Canada

  • Mexico


  • Eastern Europe

    • Poland

    • Romania

    • Hungary

    • Turkey

    • Rest of Eastern Europe

  • Western Europe

    • Germany

    • France

    • UK

    • Italy

    • Spain

    • Netherlands

    • Switzerland

    • Austria

    • Rest of Western Europe

Asia Pacific

  • China

  • India

  • Japan

  • South Korea

  • Vietnam

  • Singapore

  • Australia

  • Rest of Asia Pacific

Middle East & Africa

  • Middle East

    • UAE

    • Egypt

    • Saudi Arabia

    • Qatar

    • Rest of the Middle East

  • Africa

    • Nigeria

    • South Africa

    • Rest of Africa

Latin America

  • Brazil

  • Argentina

  • Colombia

  • Rest of Latin America



The key players in the neuromorphic chip market are Hewlett Packard Enterprise, Intel Corp., Brain chip Holdings Ltd., IBM, Innatera, Koniku, Samsung Electronics Limited, General Vision Inc., Qualcomm, Nepes Corp, Ceryx Medical & Other Players.

Samsung Electronics Limited-Company Financial Analysis

Company Landscape Analysis


In April 2022: Accenture and the Indian Institute of Science (IISc) Bengaluru initiated a partnership to conduct research and development (R&D) in cloud continuum and neuromorphic Chip at the Accenture Centre for Advanced Chip in India. This collaboration entails joint research projects and the co-development of intellectual properties and cutting-edge Chip technologies. These advancements encompass AI at the edge, spanning cloud, edge, quantum, and neuromorphic Chip, along with sustainable software engineering initiatives.

Neuromorphic Chip Market Report Scope:

Report Attributes Details
Market Size in 2023 US$ 44.77 Million
Market Size by 2031 US$ 2734.8 Million
CAGR CAGR of 67.2% From 2024 to 2031
Base Year 2023
Forecast Period 2024-2031
Historical Data 2020-2022
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Components (Software, Hardware)
• By Application (Signal Recognition, Image Recognition, Data Mining)
• By Vertical (Aerospace & Defense, Automotive, Industrial, IT & Telecom, Medical, Others)
Regional Analysis/Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America)
Company Profiles Hewlett Packard Enterprise, Intel Corp., Brain chip Holdings Ltd., IBM, Innatera, Koniku, Samsung Electronics Limited, General Vision Inc., Qualcomm, Nepes Corp. and Ceryx Medical.
Key Drivers • It is usually focused on either fast computation or low power.
• Better-performing integrated circuits, increased demand for artificial intelligence and machine learning, and an increase in the number of cross-industry alliances and collaborations.
Restraints • Technological immaturity regarding neuromorphic chip technology.

Frequently Asked Questions

The Neuromorphic Chip Market was valued at USD 44.77 Million in 2023.

 The expected CAGR of the global Neuromorphic Chip Market during the forecast period is 67.2%.

 The Asia Pacific region is anticipated to record the Fastest Growing in the Neuromorphic Chip Market.

The Automotive segment is leading in the market revenue share in 2023.

 The North America region with the Highest Revenue share in 2023.



1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions


2. Industry Flowchart


3. Research Methodology


4. Market Dynamics

4.1 Drivers

4.2 Restraints

4.3 Opportunities

4.4 Challenges


5. Impact Analysis

5.1 Impact of Russia-Ukraine Crisis

5.2 Impact of Economic Slowdown on Major Countries

5.2.1 Introduction

5.2.2 United States

5.2.3 Canada

5.2.4 Germany

5.2.5 France

5.2.6 UK

5.2.7 China

5.2.8 Japan

5.2.9 South Korea

5.2.10 India


6. Value Chain Analysis


7. Porter’s 5 Forces Model


8.  Pest Analysis


9. Neuromorphic Chip Market, By Component

9.1 Introduction

9.2 Trend Analysis

9.3 Software

9.4 Hardware

10. Neuromorphic Chip Market, By Application

10.1 Introduction

10.2 Trend Analysis

10.3 Signal Recognition

10.4 Image Recognition

10. 5 Data Mining

11. Neuromorphic Chip Market, By Vertical

11.1 Introduction

11.2 Trend Analysis

11.3 Aerospace & Defense

11.4 Automotive

11.5 Industrial

11.6 It & Telecom

11.7 Medical

11.8 Others


12. Regional Analysis

12.1 Introduction

12.2 North America

12.2.1 USA

12.2.2 Canada

12.2.3 Mexico

12.3 Europe

12.3.1 Eastern Europe Poland Romania Hungary Turkey Rest of Eastern Europe

12.3.2 Western Europe Germany France UK Italy Spain Netherlands Switzerland Austria Rest of Western Europe

12.4 Asia-Pacific

12.4.1 China

12.4.2 India

12.4.3 Japan

12.4.4 South Korea

12.4.5 Vietnam

12.4.6 Singapore

12.4.7 Australia

12.4.8 Rest of Asia Pacific

12.5 The Middle East & Africa

12.5.1 Middle East UAE Egypt Saudi Arabia Qatar Rest of the Middle East

11.5.2 Africa Nigeria South Africa Rest of Africa

12.6 Latin America

12.6.1 Brazil

12.6.2 Argentina

12.6.3 Colombia

12.6.4 Rest of Latin America


13. Company Profiles

13.1 Hewlett Packard Enterprise

13.1.1 Company Overview

13.1.2 Financial

13.1.3 Products/ Services Offered

13.1.4 SWOT Analysis

13.1.5 The SNS View

13.2 Intel Corp

13.2.1 Company Overview

13.2.2 Financial

13.2.3 Products/ Services Offered

13.2.4 SWOT Analysis

13.2.5 The SNS View

13.3 Brain chip Holdings Ltd

13.3.1 Company Overview

13.3.2 Financial

13.3.3 Products/ Services Offered

13.3.4 SWOT Analysis

13.3.5 The SNS View

13.4 IBM

13.4.1 Company Overview

13.4.2 Financial

13.4.3 Products/ Services Offered

13.4.4 SWOT Analysis

13.4.5 The SNS View

13.5 Innatera

13.5.1 Company Overview

13.5.2 Financial

13.5.3 Products/ Services Offered

13.5.4 SWOT Analysis

13.5.5 The SNS View

13.6 Koniku

13.6.1 Company Overview

13.6.2 Financial

13.6.3 Products/ Services Offered

13.6.4 SWOT Analysis

13.6.5 The SNS View

13.7 Samsung Electronics Limited

13.7.1 Company Overview

13.7.2 Financial

13.7.3 Products/ Services Offered

13.7.4 SWOT Analysis

13.7.5 The SNS View

13.8 General Vision Inc.

13.8.1 Company Overview

13.8.2 Financial

13.8.3 Products/ Services Offered

13.8.4 SWOT Analysis

13.8.5 The SNS View

13.9 Qualcomm

13.9.1 Company Overview

13.9.2 Financial

13.9.3 Products/ Services Offered

13.9.4 SWOT Analysis

13.9.5 The SNS View

13.10 Nepes Corp

13.10.1 Company Overview

13.10.2 Financial

13.10.3 Products/ Services Offered

13.10.4 SWOT Analysis

13.10.5 The SNS View

13.11 Ceryx Medical.

13.11.1 Company Overview

13.11.2 Financial

13.11.3 Products/ Services Offered

13.11.4 SWOT Analysis

13.11.5 The SNS View

14. Competitive Landscape

14.1 Competitive Benchmarking

14.2 Market Share Analysis

14.3 Recent Developments

            14.3.1 Industry News

            14.3.2 Company News

            14.3.3 Mergers & Acquisitions


15. Use Case and Best Practices


16. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

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This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

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Data Bank Validation

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