Edge AI Hardware Market Size - By Device, By Process, By Packaging Type, By End Use Industry - Global Forecast, 2025 - 2034

Edge AI Hardware Market Size

The global edge AI hardware market was estimated at USD 4.8 Billion in 2024. The market is expected to grow from USD 5.2 Billion in 2025 to USD 10.1 Billion in 2030 and USD 20.4 Billion by 2034, at a CAGR of 16.3% during the forecast period of 2025 to 2034.

• The rising demand for low-latency, high-efficiency processing at the edge is significantly driving the growth of the market. Enterprises across sectors are deploying edge AI hardware to enable real-time analytics and enhance data privacy as these devices combine AI accelerators, CPUs, and neural processing units (NPUs) on a single chip minimizing latency, reducing bandwidth usage, and supporting energy-efficient, on-device intelligence. This is particularly crucial in autonomous vehicles, industrial automation systems, and smart surveillance, where fast decision-making and efficient power management are essential for operational performance and cost control.
   
• As per IEEE (Institute of Electrical and Electronics Engineers), edge AI hardware will be revolutionizing how artificial intelligence applications are deployed by moving intelligence from the cloud to local embedded artificial intelligence devices. In 2025, trend of new AI chips and edge computing modules is empowering AI at the edge – from drones and smart cameras to IoT sensors and industrial robots – with high efficiency and performance
   
• The emergence of intelligent and multifunctional edge AI chips is transforming next-generation embedded system architectures. Modern edge AI hardware now integrates advanced features such as on-chip training, dynamic workload management, thermal throttling, and security encryption while supporting compatibility with system-on-module (SoM) and heterogeneous computing platforms. These capabilities streamline system integration, reduce operational complexity, and improve reliability in use cases ranging from automotive ADAS and collaborative robots to medical imaging systems and retail analytics. Demand is especially high in industrial and transportation sectors where safety, real-time inference, and ruggedized computing are key priorities.
   
• Accelerated deployment of smart infrastructure and Industry 4.0 initiatives is catalyzing the expansion of the market. Government-led programs—such as the EU’s Horizon Europe initiative and the U.S. CHIPS Act—are promoting investments in edge computing, autonomous systems, and intelligent manufacturing. Simultaneously, widespread rollout of 5G networks, smart cities, and distributed data centers across Asia-Pacific, North America, and Europe is fueling adoption of edge AI hardware with capabilities such as low-power processing, enhanced thermal performance, and robust I/O connectivity.
   
• Based on end-user industry, the edge AI hardware market is segmented into Manufacturing, Healthcare, BFSI, Government, Retail & E-commerce, Telecommunication, Transport & Logistics, and Others. Among these, the Smartphone segment accounted for the largest share of 33.3% in 2024. The proliferation of AI-driven functionalities such as voice assistants, facial recognition, real-time translation, and intelligent photography in modern smartphones is a key driver behind this dominance. Edge AI hardware integrated into mobile chipsets offers low-latency processing, power efficiency, and on-device intelligence—enabling enhanced user experiences without compromising data privacy or requiring continuous cloud connectivity. The increasing penetration of 5G and rising consumer demand for high-performance, AI-enabled mobile devices continue to bolster growth in this segment.
   
• In 2024, North America led the global edge AI hardware market with a share of 37.6%, driven by the rapid adoption of AI-enabled devices, strong presence of leading technology firms, and early deployment of 5G networks. The region benefits from significant investments in autonomous systems, smart infrastructure, and industrial automation across the United States and Canada. Moreover, advancements in chip design, edge computing platforms, and AI accelerator technologies are being spearheaded by major players headquartered in this region. The increasing integration of edge AI hardware in sectors such as automotive, healthcare, defense, and retail, along with supportive government initiatives like the CHIPS Act, continue to strengthen North America's leadership in innovation, deployment, and commercial adoption of edge AI solutions.
   

Edge AI Hardware Market Trends

• The proliferation of purpose-built edge AI accelerators such as NPUs, VPUs, and edge-focused ASICs is rapidly transforming the landscape of edge computing. Since 2022, companies like NVIDIA and Qualcomm have introduced highly efficient, compact chipsets designed to deliver low-latency inference in constrained environments. These accelerators now power a range of applications from smart surveillance and industrial robotics to autonomous systems—enabling real-time AI processing at the device level while minimizing power and thermal footprints.
   
• Miniaturization and modular hardware design are becoming defining features of the edge AI hardware market. Since 2023, vendors have accelerated the development of compact, hot-swappable SoMs (System-on-Modules) that allow real-time chipset upgrades and flexible deployment across applications like wearable medical devices, drones, and automated retail kiosks. This shift is drastically shortening development cycles and supporting application-specific customizations at scale.
   
• Hardware-software co-optimization is becoming a key differentiator in the Edge AI ecosystem as developers seek to maximize performance per watt and reduce time-to-inference. Since 2023, leading players like Apple, Google, and Hailo have invested heavily in AI-optimized compilers, quantization-aware training, and firmware-level acceleration to tightly align edge hardware with specific workloads. This trend is enabling real-time video analytics, predictive maintenance, and contextual language processing in edge devices while lowering latency and improving thermal efficiency—especially critical for wearables, autonomous machines, and smart infrastructure.
   

Edge AI Hardware Market Analysis

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Based in device type, the market is segmented into smartphones, cameras, robots, wearables, smart speaker and other devices. The smartphones segment accounts for the highest market share of 33.3% and also has the highest CAGR of 17.7% during the forecast period.
 

• The smartphones segment was the largest in the market in 2024, with a market value of USD 1.6 billion. Edge AI hardware in smartphones enables advanced features such as on-device voice recognition, real-time translation, intelligent photography, and facial authentication—delivering faster performance, enhanced user experience, and improved privacy without cloud dependency. This segment leads the market due to the mass adoption of AI-capable smartphones, widespread integration of neural processing units (NPUs), and the growing demand for AI-enhanced mobile applications across all user demographics.
   
• Also, the smartphones segment is the fastest-growing category in the edge AI hardware market and is projected to expand to a CAGR of 17.7% during the forecast period. This growth is driven by the widespread adoption of AI-driven features such as intelligent voice assistants, real-time language translation, advanced photography enhancements, and biometric authentication enabled by edge AI chips. As smartphones evolve into AI-centric devices, demand for high-performance, energy-efficient AI hardware is accelerating. The segment’s rapid expansion is further supported by the rollout of 5G connectivity, increasing user expectations for on-device intelligence, and continuous innovation in mobile AI chipsets by major players.

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Based on process, the market is segmented into training and inference. The inference segment accounts for the highest market share of 68.9%.
 

• The inference segment was the largest in the edge AI hardware market in 2024, accounting for a market value of USD 3.2 billion. This segment continues to dominate due to the widespread deployment of edge devices that perform real-time inferencing for applications such as object detection, facial recognition, predictive maintenance, and natural language processing. Inference hardware is optimized for low latency, power efficiency, and fast model execution—making it critical for edge scenarios where cloud connectivity is limited or undesirable.
   
• The inference-focused edge AI platforms support stable, high-performance processing across diverse environments—from smartphones and surveillance cameras to industrial machines and autonomous vehicles. Their scalability, mature software support, and compatibility with popular AI frameworks make them a preferred choice for OEMs and developers aiming to deploy intelligent, responsive systems across automotive, retail, healthcare, and IoT applications.
   
• Also, the inference segment is the fastest-growing category in the edge AI hardware market and is projected to grow at a CAGR of 16.8% during the forecast period. This growth is fueled by the rising demand for real-time AI processing at the edge, where tasks such as object detection, speech recognition, and behavioral analytics must be executed instantly without relying on cloud connectivity. Inference chips are increasingly adopted in smart devices, industrial sensors, surveillance systems, and automotive electronics, where low latency and high energy efficiency are critical.
   
• As the need for intelligent, power-optimized edge devices grows, inference-focused hardware offers a robust solution with optimized architectures for neural network execution and AI model deployment. These platforms also benefit from a well-established ecosystem of AI frameworks and software toolchains, enabling faster development cycles and greater deployment flexibility. Their scalability and reliability make them ideal for sectors like healthcare diagnostics, smart retail, and autonomous mobility—where real-time decision-making and cost-effective AI acceleration are paramount.
   

Based on the end-user industry type, the market is segmented into manufacturing, healthcare, BSFI, government, retail & e-commerce, telecommunication, transport & logistics, Others. The manufacturing segment accounts for the highest market share of 26.3% and is projected to grow with a CAGR of 16.1% during the forecast period.
 

• The manufacturing segment was the largest in the edge AI hardware market, accounting for a market value of USD 1.2 billion in 2024. This dominance is driven by the rapid adoption of smart factories, industrial automation, and predictive maintenance systems—where edge AI hardware enables real-time decision-making, machine vision, and intelligent process control. Manufacturers are leveraging edge AI to enhance operational efficiency, reduce downtime, and improve product quality, especially in high-throughput environments.
   
• Edge AI hardware in the manufacturing sector is widely deployed across assembly lines, robotic systems, and quality inspection stations due to its low latency processing, localized intelligence, and reduced reliance on cloud infrastructure. As the shift toward Industry 4.0 accelerates, demand for rugged, high-performance edge AI solutions is growing—supporting applications in CNC machines, programmable logic controllers (PLCs), and condition monitoring systems. This trend is further reinforced by the need for scalable AI integration in constrained industrial environments where energy efficiency, security, and real-time responsiveness are critical.
   
• The healthcare segment is the fastest-growing segment in the Edge AI Hardware Market and is projected to expand at a CAGR of 18.6% during the forecast period. This growth is driven by the increasing adoption of AI-enabled diagnostic tools, remote patient monitoring systems, and wearable medical devices that require low-latency, on-device intelligence for real-time decision-making. Edge AI hardware supports critical healthcare applications by enabling faster imaging analysis, anomaly detection, and personalized treatment without depending on cloud connectivity.
   
• As digital health technologies evolve and demand rises for privacy-preserving, real-time analytics, edge AI hardware is becoming integral to smart medical devices and connected care ecosystems. From AI-assisted ultrasound systems to intelligent insulin pumps and portable ECG monitors, edge AI ensures secure, energy-efficient processing close to the patient. Its growing role in clinical workflows, hospital automation, and point-of-care diagnostics highlights its value in enhancing accuracy, responsiveness, and efficiency across modern healthcare infrastructure.

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North America accounted for 37.6% of the edge AI hardware market in 2024 and is projected to grow at a CAGR of 15% during the forecast period. This growth is fueled by the strong presence of leading technology companies, rapid advancements in AI chip development, and early adoption of edge computing across key sectors such as automotive, healthcare, manufacturing, and smart cities. The region is also benefiting from large-scale investments in AI infrastructure, 5G deployment, and government-backed semiconductor initiatives, which are accelerating the commercialization and integration of edge AI solutions across a broad range of applications.
 

• The U.S. market reached a valuation of USD 1.5 billion in 2024 and is projected to grow at a CAGR of 15.4% during the forecast period. Growth is driven by the country’s leadership in AI innovation, robust adoption of smart manufacturing, and rapid deployment of edge computing across automotive, healthcare, defense, and telecom sectors. The U.S. is also benefiting from advancements in 5G infrastructure, real-time AI-enabled medical diagnostics, and intelligent transportation systems—all of which require high-performance, low-latency edge AI solutions.
   
• Federal initiatives like the CHIPS and Science Act, aimed at bolstering domestic semiconductor production, along with increasing private investments in AI hardware R&D, are further strengthening the U.S. market landscape. These developments are opening new growth avenues for edge AI chipmakers and system integrators focused on delivering scalable, energy-efficient, and secure AI acceleration at the edge.
   
• The Canada edge AI hardware market was valued at USD 289 million in 2024 and is projected to grow at a CAGR of 12.3% during the forecast period. Growth is being driven by Canada’s increasing adoption of smart technologies in sectors such as healthcare, transportation, and manufacturing. Edge AI is playing a key role in enabling real-time decision-making, predictive analytics, and operational efficiency across both urban and remote settings—particularly in applications requiring data privacy and low-latency processing.
   
• Government support for AI innovation, along with national strategies focused on digital transformation, smart infrastructure, and clean technology, are fostering favourable conditions for market expansion. The growing integration of edge AI hardware in use cases such as autonomous vehicles, medical diagnostics, and intelligent grid systems reflects Canada's broader push toward technological modernization, sustainability, and decentralized computing.
   

Europe held a 24.3% share of the edge AI hardware market in 2024 and is projected to grow at a CAGR of 15.9% during the forecast period. The region is witnessing rapid growth driven by rising adoption of autonomous mobility solutions, smart manufacturing technologies, and AI-powered healthcare systems. Countries like Germany, France, and the Netherlands are at the forefront of integrating edge AI into industrial automation, urban mobility, and energy management—spurred by strong government support and digital transformation initiatives.
 

• The Germany edge AI hardware market reached a valuation of USD 295.4 million in 2024 and is projected to grow at a CAGR of 15.5% during the forecast period. Growth is driven by Germany’s strong industrial base, leadership in automotive innovation, and widespread adoption of Industry 4.0 technologies. Edge AI hardware is playing a pivotal role in enabling real-time control, predictive maintenance, and intelligent automation across sectors such as manufacturing, mobility, and energy.
   
• Demand is particularly robust for edge AI-enabled systems in autonomous vehicles, robotics, smart factory environments, and AI-assisted energy management. Germany’s strategic focus on AI innovation, supported by national and EU-level funding for semiconductor and digital infrastructure, is accelerating the deployment of edge computing solutions. As sustainability, operational efficiency, and data localization gain prominence, Germany is emerging as a key hub for advanced edge AI hardware development and adoption.
   
• The U.K. edge AI hardware market was valued at USD 272 million in 2024 and is projected to grow at a CAGR of 17.6% during the forecast period. Growth is being fueled by the UK's focus on AI-driven innovation across sectors such as healthcare, smart mobility, energy, and manufacturing. As the country advances its digital transformation agenda and net-zero commitments, demand for real-time, on-device AI processing is accelerating across edge devices used in diagnostics, autonomous systems, and infrastructure monitoring.
   
• Opportunities are expanding in areas like AI-enabled medical technologies, intelligent traffic systems, and predictive industrial automation supported by government initiatives including the UK AI Strategy and increased funding for semiconductor and R&D capabilities. The country's emphasis on technological sovereignty, data privacy, and resilient supply chains is further reinforcing the adoption of edge AI hardware designed for high-performance, low-latency, and energy-efficient applications.
   

The Asia-Pacific region accounted for 25.6% of the Edge AI Hardware Market in 2024, positioning it as one of the key regional contributors. This strong presence is fueled by rapid digital transformation, increasing adoption of smart manufacturing technologies, and growing investments in AI-driven consumer electronics across countries such as China, Japan, South Korea, Taiwan, and India. The demand for low-latency, energy-efficient AI processing in edge devices is rising sharply across sectors including automotive, healthcare, industrial automation, and retail.
 

• The China edge AI hardware market held the largest national share at 33.27% in 2024 and is projected to grow at a CAGR of 20.2% during the forecast period. China’s leadership in the market is driven by its expanding AI ecosystem, large-scale adoption of smart devices, and aggressive investments in intelligent manufacturing, autonomous mobility, and surveillance infrastructure. The push for technological self-reliance and edge intelligence is fueling demand for high-performance, localized AI processing across industrial, consumer, and public-sector applications.
   
• Edge AI hardware is seeing large-scale deployment in China across use cases such as smart city development, factory automation, smart healthcare, and AI-enabled logistics. National initiatives like “Made in China 2025”, AI Development Plans, and increased investment in domestic chip manufacturing and edge computing infrastructure are strengthening the ecosystem. As China accelerates innovation in real-time, low-latency AI capabilities, it remains a global hub for scalable, energy-efficient edge AI hardware solutions.
   
• The Japan Edge AI Hardware Market accounted for a 19.60% share in 2024 and is projected to grow at a CAGR of 18.90% during the forecast period. Growth is driven by Japan’s leadership in automotive electronics, robotics, and precision manufacturing, where real-time intelligence and reliability are paramount. The increasing deployment of edge AI in autonomous vehicles, factory automation, and service robotics is fueling demand for compact, low-latency AI hardware that delivers high accuracy and efficiency.
   
• Backed by robust R&D capabilities and strong collaboration between industry and academia, Japan is advancing the development of next-generation edge AI solutions tailored for mission-critical applications. Government initiatives aimed at revitalizing the domestic semiconductor ecosystem and accelerating digital transformation are further supporting edge hardware adoption. With its strategic focus on quality, innovation, and AI-enabled infrastructure, Japan is emerging as a vital hub for edge AI deployment across both consumer and industrial sectors.
   
• India Edge AI Hardware Market was valued at USD 205.2 million in 2024 and is projected to grow at a CAGR of 21.3% during the forecast period. Growth is being driven by the country’s rapid digital transformation, increasing adoption of smart manufacturing, and expansion of AI use cases in sectors such as healthcare, agriculture, transportation, and defense. Demand for low-latency, real-time processing in edge environments is accelerating as industries seek scalable, energy-efficient AI hardware solutions.
   
• National initiatives such as Digital India, Make in India, and the PLI scheme for semiconductors are fostering a robust ecosystem for localized edge AI innovation and hardware production. India is emerging as a dynamic market for edge AI chips used in applications like surveillance systems, remote diagnostics, autonomous machines, and smart city infrastructure. The growing emphasis on cost-effective, compact, and rugged AI solutions—adapted for India’s diverse operating conditions—is positioning the country as a significant growth hub for the global edge AI hardware landscape.
   

Latin America held a 6.5% share of the edge AI hardware market in 2024 and is projected to grow at a CAGR of 14% during the forecast period. Growth is being driven by the region’s accelerating digitalization across sectors such as manufacturing, agriculture, transportation, and public safety. Countries like Brazil, Mexico, and Chile are increasingly adopting edge AI solutions to enhance productivity, enable real-time decision-making, and reduce reliance on cloud infrastructure—especially in remote or bandwidth-constrained environments.
 

The Middle East & Africa Market was valued at USD 286.1 million in 2024, driven by growing investments in smart infrastructure, industrial automation, and AI-enabled public services. Countries across the Gulf Cooperation Council (GCC) and South Africa are accelerating digital transformation initiatives, with a strong focus on edge computing for applications in surveillance, smart mobility, energy management, and healthcare.
 

• The Saudi Arabia Edge AI hardware market was valued at USD 127.8 million in 2024, fueled by the country’s strategic advancements in electric mobility, industrial automation, and smart infrastructure under Vision 2030. Accelerated investments in AI localization, digital transformation, and next-gen mobility are driving demand for edge AI hardware that delivers low-latency, real-time intelligence across distributed environments.
   
• The integration of edge AI systems in EV platforms, intelligent surveillance, predictive maintenance, and smart energy management is positioning Saudi Arabia as a leading adopter of decentralized AI technologies. As the country intensifies efforts around technology sovereignty, sustainability, and AI-driven public services, edge AI hardware is playing a pivotal role in enabling secure, responsive, and efficient computing across critical national initiatives and industry verticals.
   
• The United Arab Emirates (UAE) Edge AI hardware market was valued at USD 87.3 million in 2024, driven by the country's strong focus on smart infrastructure, digital transformation, and AI-powered solutions under UAE Vision 2031. As the nation accelerates its adoption of edge computing in sectors like transportation, energy, and smart cities, demand is rising for compact, low-latency, and energy-efficient AI hardware capable of real-time processing at the device level.
   
• Government initiatives such as the Dubai Smart City program, Clean Energy Strategy, and Abu Dhabi’s Industry 4.0 drive are fostering widespread deployment of edge AI systems across EV platforms, surveillance networks, predictive maintenance solutions, and autonomous utilities. The UAE’s growing role as a regional technology and innovation hub is creating significant opportunities for edge AI hardware providers supporting mission-critical, decentralized, and intelligent computing applications across public and private sectors.
   

Edge AI Hardware Market Share

• The top 5 companies—NVIDIA Corporation, Qualcomm Incorporated, Apple Inc., Huawei Technologies Co., Ltd., and Samsung Electronics Co., Ltd.—collectively account for approximately 42.4% of the global market, reflecting a moderately fragmented yet competitive landscape. This leadership is underpinned by their expertise in AI-accelerated processing, vertical integration, and innovation in semiconductor design for edge-centric applications across mobility, consumer electronics, and industrial sectors.
   
• NVIDIA Corporation leads the market with an 11.15% share, driven by its dominance in GPU-accelerated edge computing. Its Jetson series powers a wide array of applications—from autonomous robotics and drones to smart surveillance and medical imaging—thanks to its scalable AI performance, CUDA support, and ecosystem development tools. NVIDIA’s continued investment in transformer-based edge platforms and industrial AI has further reinforced its leadership.
   
• Qualcomm Incorporated holds a 9.65% market share, bolstered by its Snapdragon platforms, which combine edge AI engines, 5G connectivity, and low-power design. The company’s solutions are widely used in smartphones, automotive infotainment, and embedded IoT systems. Its robust IP portfolio and partnerships with OEMs and ODMs position Qualcomm as a key enabler of distributed intelligence.
   
• Apple Inc. accounts for 8.02% of the market, primarily through its Neural Engine integrated within A- and M-series chipsets. Apple’s focus on on-device processing for enhanced privacy, responsiveness, and energy efficiency has popularized edge AI across consumer applications such as facial recognition, augmented reality, and voice assistance in iPhones, iPads, and wearables.
   
• Huawei Technologies Co., Ltd. commands a 7.11% share, leveraging its Ascend and Kirin AI chipsets, which serve applications in smart cities, telecom edge computing, and AIoT devices. Despite supply chain restrictions, Huawei maintains a strong presence in Asia and emerging markets, where its AI hardware supports edge inference in surveillance, mobility, and public infrastructure.
   
• Samsung Electronics Co., Ltd. holds a 6.43% share, with growth driven by its Exynos chipsets and integrated NPU architectures. Samsung’s edge AI capabilities cater to mobile, smart home, and connected appliances markets. The company’s vertical manufacturing capacity, combined with innovation in imaging, sensor fusion, and memory technologies, supports its edge AI hardware expansion.
   

Edge AI Hardware Market Companies

Some prominent market participants operating in the edge AI hardware industry include:
 

• NVIDIA Corporation
• Google (Alphabet Inc.)
• Intel Corporation
• Huawei Technologies Co., Ltd.
• Apple Inc.
• Qualcomm Incorporated
• Samsung Electronics Co., Ltd.
• IBM Corporation
• Dell Technologies Inc.
• Microsoft Corporation
• ARM
• Hailo
• MediaTek Inc.
• Xilinx Inc.
• Micron Technology
   
• NVIDIA Corporation dominates the market with its Jetson series, offering GPU-accelerated computing, real-time AI inference, and a mature development ecosystem that serves robotics, surveillance, and autonomous systems.
   
• Samsung Electronics Co., Ltd. is strengthening its edge AI portfolio with Exynos chipsets and ISOCELL sensors, advancing applications in smart homes, consumer devices, and mobile computing.
   
• Dell Technologies Inc. supports the edge AI market with industrial-grade hardware and edge servers that power AI workloads in manufacturing, energy, and logistics, though primarily focused on enterprise IT integration.
   
• Hailo specializes in low-power edge AI accelerators, with its Hailo-8 chip offering high TOPS/W for applications in surveillance, robotics, and embedded systems, gaining momentum among startups and mid-tier integrators.
   

Edge AI Hardware Market News

• In February 2025, NVIDIA Corporation introduced the Jetson Thor platform, its most advanced edge AI module to date, designed for robotics, autonomous machines, and industrial edge computing. Built on the latest GPU architecture and integrated with transformer engines, the platform delivers over 800 TOPS of AI performance, enabling real-time decision-making for smart factories, mobility systems, and edge analytics.
   
• In March 2025, Qualcomm Incorporated partnered with Foxconn Industrial Internet to deploy Snapdragon-powered AI edge gateways across smart manufacturing sites in Taiwan and India. These gateways combine AI inference, 5G connectivity, and sensor fusion to optimize factory automation and predictive maintenance. The large-scale deployment is aligned with Industry 4.0 initiatives and Qualcomm’s expansion into edge industrial IoT.
   
• In May 2025, Google (Alphabet Inc.) expanded its Coral Edge TPU lineup with the launch of Coral Dev Board Max, delivering up to 8 TOPS of AI performance in a compact, fanless design. This next-gen board supports TensorFlow Lite and PyTorch, targeting use cases in retail analytics, smart security, and healthcare monitoring. The device is also optimized for offline inferencing, enhancing data privacy in edge environments.
   

The edge AI hardware market research report includes in-depth coverage of the industry with estimates and forecasts in terms of revenue in (USD billion) and volume (units) from 2021 – 2034 for the following segments:

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Market, By Device Type

• Smartphones
• Cameras
• Robots
• Wearables
• Smart Speaker
• Other Devices

Market, By Process Type

• Training
• Inference

Market, By End Use Industry

• Manufacturing
• Healthcare
• BSFI
• Government
• Retail & e-commerce
• Telecommunication
• Transport & logistics
• Others

The above information is provided for the following regions and countries: 

• North America 
  • U.S.
  • Canada 
• Europe
  • Germany
  • UK
  • France
  • Spain
  • Italy
  • Netherlands 
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea 
• Latin America
  • Brazil
  • Mexico
  • Argentina 
• Middle East and Africa
  • Saudi Arabia
  • South Africa
  • UAE