Neural Processors

Global Neural Processors Market to Reach US$894.3 Million by 2030

The global market for Neural Processors estimated at US$306.1 Million in the year 2024, is expected to reach US$894.3 Million by 2030, growing at a CAGR of 19.6% over the analysis period 2024-2030. Inference Operation, one of the segments analyzed in the report, is expected to record a 17.1% CAGR and reach US$487.1 Million by the end of the analysis period. Growth in the Training Operation segment is estimated at 23.0% CAGR over the analysis period.

The U.S. Market is Estimated at US$80.5 Million While China is Forecast to Grow at 18.6% CAGR

The Neural Processors market in the U.S. is estimated at US$80.5 Million in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$138.1 Million by the year 2030 trailing a CAGR of 18.6% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 17.7% and 17.2% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 14.6% CAGR.

Global Neural Processor Market – Key Trends & Drivers Summarized

How Are Neural Processors Revolutionizing Artificial Intelligence?

Neural processors, also known as neural processing units (NPUs), are specialized chips designed to accelerate machine learning and artificial intelligence (AI) computations. Unlike traditional central processing units (CPUs) and graphics processing units (GPUs), NPUs are optimized for parallel processing, allowing them to efficiently handle AI workloads such as image recognition, natural language processing, and real-time decision-making. These processors are becoming critical in various applications, from edge computing and autonomous vehicles to smart devices and high-performance computing. The rise of AI-driven applications in industries such as healthcare, finance, and robotics has significantly increased the demand for neural processors, enabling faster, more efficient AI model training and inference. As deep learning algorithms grow in complexity, traditional computing architectures struggle to keep up with the required computational power. NPUs, with their ability to process vast amounts of data in real time while consuming less power, are now at the forefront of AI hardware evolution. With the expansion of cloud-based AI services and on-device AI processing, neural processors are shaping the next generation of intelligent computing.

What Challenges Are Hindering the Growth of the Neural Processor Market?

Despite their rapid adoption, neural processors face several challenges that could limit their widespread deployment. One of the primary concerns is the high cost of designing and manufacturing NPUs, as the development of AI-specific hardware requires significant research and investment. Unlike general-purpose processors, NPUs must be tailored to specific AI workloads, leading to compatibility issues across different AI models and frameworks. Another major challenge is power consumption, particularly for high-performance NPUs used in data centers and AI-driven applications. While NPUs are more efficient than traditional processors, the increasing demand for real-time AI processing is driving up power requirements, leading to cooling and sustainability concerns. Additionally, the fragmented nature of the AI hardware market means that developers must optimize their machine learning models for specific NPUs, reducing flexibility and increasing integration complexity. Security risks are also a growing concern, as AI-powered systems are vulnerable to adversarial attacks, data breaches, and unauthorized manipulations. Furthermore, supply chain disruptions and global semiconductor shortages have impacted the availability of NPUs, delaying deployment in key industries. Addressing these challenges requires continued advancements in chip design, standardization efforts, and enhanced security protocols to ensure seamless AI integration across various applications.

How Are Innovations in Neural Processing Units Enhancing AI Capabilities?

The neural processor industry is undergoing rapid innovation, with new technologies emerging to enhance AI performance, efficiency, and scalability. One of the most significant advancements is the development of neuromorphic computing, which mimics the architecture of the human brain to process information more efficiently. These bio-inspired processors use spiking neural networks (SNNs) to enable low-power, real-time AI computations, making them ideal for edge computing and autonomous systems. Another breakthrough is the integration of NPUs into consumer devices, such as smartphones, smart home systems, and wearable technology, enabling on-device AI capabilities that reduce latency and enhance user experiences. Quantum AI is also gaining traction, with researchers exploring the potential of quantum computing combined with neural processors to solve complex problems at unprecedented speeds. Additionally, AI accelerators such as tensor processing units (TPUs) and field-programmable gate arrays (FPGAs) are being optimized for deep learning applications, providing greater flexibility in AI model deployment. Edge AI is another key trend, with NPUs being embedded in IoT devices to enable real-time AI processing without relying on cloud connectivity. These innovations are not only expanding the capabilities of AI systems but also paving the way for next-generation computing architectures that prioritize speed, energy efficiency, and scalability.

What Is Driving the Growth of the Neural Processor Market?

The growth in the neural processor market is driven by several factors, including the increasing adoption of AI applications, advancements in deep learning models, and the expansion of edge computing. The widespread use of AI in industries such as healthcare, finance, and automotive is fueling demand for high-performance NPUs capable of handling complex machine learning tasks. The rise of autonomous vehicles and AI-powered robotics is another major driver, as these technologies require real-time data processing and decision-making capabilities that traditional processors cannot provide. The proliferation of smart devices and IoT applications is also contributing to market growth, with NPUs enabling on-device AI features such as voice recognition, predictive analytics, and biometric authentication. Additionally, the expansion of AI-driven cloud services is pushing data centers to adopt NPUs to enhance computational efficiency and reduce latency. The growing emphasis on energy-efficient AI processing is further accelerating NPU adoption, as businesses seek sustainable solutions for large-scale AI deployments. With continuous advancements in chip design, AI model optimization, and semiconductor manufacturing, the neural processor market is poised for exponential growth, shaping the future of intelligent computing and next-generation AI technologies.

SCOPE OF STUDY:

The report analyzes the Neural Processors market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Operation Type (Inference Operation, Training Operation); Application (Smartphones & Tablets Application, Autonomous Vehicles Application, Robotics & Drones Application, Healthcare & Medical Devices Application, Smart Home Devices & IoT Application, Cloud & Data Center AI Application, Industrial Automation Application, Other Applications)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 47 Featured) -

• Advanced Micro Devices, Inc. (AMD)
• Apple Inc.
• ARM Holdings plc
• BrainChip Holdings Ltd.
• Cerebras Systems
• Google LLC
• Graphcore Limited
• Groq Inc.
• Hailo Technologies Ltd.
• Huawei Technologies Co., Ltd.
• IBM Corporation
• Intel Corporation
• Kneron
• Mythic AI
• NVIDIA Corporation
• Qualcomm Incorporated
• SambaNova Systems
• Samsung Electronics Co., Ltd.
• Syntiant Corp.
• Tenstorrent Inc.

TARIFF IMPACT FACTOR

Our new release incorporates impact of tariffs on geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by artificially increasing the COGS, reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

We are diligently following expert opinions of leading Chief Economists (14,949), Think Tanks (62), Trade & Industry bodies (171) worldwide, as they assess impact and address new market realities for their ecosystems. Experts and economists from every major country are tracked for their opinions on tariffs and how they will impact their countries.

We expect this chaos to play out over the next 2-3 months and a new world order is established with more clarity. We are tracking these developments on a real time basis.

As we release this report, U.S. Trade Representatives are pushing their counterparts in 183 countries for an early closure to bilateral tariff negotiations. Most of the major trading partners also have initiated trade agreements with other key trading nations, outside of those in the works with the United States. We are tracking such secondary fallouts as supply chains shift.

To our valued clients, we say, we have your back. We will present a simplified market reassessment by incorporating these changes!

APRIL 2025: NEGOTIATION PHASE

Our April release addresses the impact of tariffs on the overall global market and presents market adjustments by geography. Our trajectories are based on historic data and evolving market impacting factors.

JULY 2025 FINAL TARIFF RESET

Complimentary Update: Our clients will also receive a complimentary update in July after a final reset is announced between nations. The final updated version incorporates clearly defined Tariff Impact Analyses.

Reciprocal and Bilateral Trade & Tariff Impact Analyses:

USA
CHINA
MEXICO
CANADA
EU
JAPAN
INDIA
176 OTHER COUNTRIES.

Leading Economists - Our knowledge base tracks 14,949 economists including a select group of most influential Chief Economists of nations, think tanks, trade and industry bodies, big enterprises, and domain experts who are sharing views on the fallout of this unprecedented paradigm shift in the global econometric landscape. Most of our 16,491+ reports have incorporated this two-stage release schedule based on milestones.

Please note: Reports are sold as single-site single-user licenses. Electronic versions require 24-48 hours as each copy is customized to the client with digital controls and custom watermarks. The Publisher uses digital controls protecting against copying and printing is restricted to one full copy to be used at the same location.

The latest version of Adobe Acrobat Reader is required to view the report. Upon ordering an electronic version, the Publisher will provide a link to download the purchased report.

Prior to fulfillment of an order, the client will be required to sign a document detailing the purchase terms for a publication from this publisher.