Artificial Intelligence Chip Market Ppt, Size, Share, Trends & Forecast 2030

Leander, Texas and Tokyo, Japan - Feb.04.2026
As per DataM intelligence research report "The global Artificial Intelligence (AI) Chip market was valued at US$ 25.12 billion in 2022 and is estimated to grow at a CAGR of 38.41% during the forecast period (2023-2030) to reach a value of US$ 335.02 billion in 2031."

Growth is fueled by rapid adoption of AI in data centers, edge computing, and consumer electronics. GPUs, ASICs, and neuromorphic chips dominate demand. Technology companies, cloud service providers, and automotive OEMs are key end-users. Advancements in machine learning and semiconductor innovation drive expansion.

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Artificial Intelligence Chip Market: Competitive Intelligence
NVIDIA Corporation, Intel Corporation, Advanced Micro Devices Inc.(AMD), MediaTek Inc, Google, Samsung Electronics Co Ltd, Qualcomm Technologies Inc., Alphabet Inc., INTERNATIONAL BUSINESS MACHINES CORPORATION, Cambricon Technologies

The Artificial Intelligence (AI) Chip Market is being powerfully shaped by NVIDIA Corporation, Intel Corporation, Advanced Micro Devices Inc. (AMD), MediaTek Inc., Google, Samsung Electronics Co. Ltd., Qualcomm Technologies Inc., Alphabet Inc., International Business Machines Corporation, and Cambricon Technologies, as these companies collectively accelerate compute performance, energy efficiency, and AI scalability. Their chip innovations support critical workloads across data centers, cloud computing, edge AI, consumer electronics, and autonomous systems. By enabling faster model training, real-time inference, and optimized power consumption, these companies directly contribute to the growth, competitiveness, and structural evolution of the Artificial Intelligence (AI) Chip Market. This collective progress strengthens AI adoption across enterprise, industrial, and consumer ecosystems.

The combined strengths of these players create strong momentum within the Artificial Intelligence (AI) Chip Market by aligning high-performance computing, semiconductor manufacturing, and AI software integration. NVIDIA Corporation, AMD, and Intel Corporation drive leadership in GPUs, CPUs, and accelerators for data center and enterprise AI workloads. Google, Alphabet Inc., and IBM integrate custom AI chips with cloud platforms and AI frameworks, accelerating end-to-end AI deployment. Samsung Electronics Co. Ltd., Qualcomm Technologies Inc., MediaTek Inc., and Cambricon Technologies complement this landscape with advanced system-on-chip solutions for mobile, edge, and region-specific AI applications.

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Fund Raisings

✅ January 2026 - NVIDIA Corporation (North America)
NVIDIA invested $65 million in expanding AI chip R&D and advanced fabrication partnerships. The funding strengthens next-generation data center and edge AI capabilities.

✅ December 2025 - Graphcore Ltd. (Europe)
Graphcore raised $48 million to scale AI accelerator development and commercial deployment. The capital supports chip architecture optimization and enterprise adoption.

✅ November 2025 - Cerebras Systems (North America)
Cerebras secured $72 million to advance wafer-scale AI processor manufacturing. The funding accelerates high-performance computing applications.

Product Launches & Partnerships

✅ January 2026 - NVIDIA Corporation (North America)
NVIDIA launched a new AI inference chip optimized for energy-efficient data centers. Partnerships with cloud providers support rapid commercial deployment.

✅ December 2025 - Graphcore Ltd. (Europe)
Graphcore released next-generation IPU processors for large-scale AI workloads. The launch includes collaborations with research institutions.

✅ October 2025 - Intel Corporation (North America)
Intel partnered with enterprise customers to deploy AI accelerators in edge computing. The initiative improves AI workload efficiency and scalability.

Mergers & Acquisitions

✅ January 2026 - NVIDIA Corporation (North America)
NVIDIA acquired an AI chip design startup to strengthen custom silicon capabilities. The acquisition enhances performance optimization for specialized workloads.

✅ November 2025 - Intel Corporation (Europe)
Intel acquired a European AI semiconductor firm to expand R&D presence. The deal supports advanced chip manufacturing strategies.

✅ October 2025 - AMD (North America)
AMD acquired an AI software optimization company to complement its chip portfolio. The move enhances system-level performance and adoption.

Segment Covered in the Artificial Intelligence Chip Market:
By Chip Type
The market is segmented into graphics processing units (GPU) 40%, application-specific integrated circuits (ASIC) 30%, field-programmable gate arrays (FPGA) 15%, central processing units (CPU) 10%, and others 5%, with GPUs dominating due to their high parallel processing capability and widespread use in AI training and inference. ASICs are rapidly growing owing to energy efficiency and performance optimization for specific AI workloads. FPGAs are used for flexible and low-latency applications, while CPUs support hybrid AI computing environments. Increasing AI workload complexity drives diversified chip adoption.

By Processing
Processing modes include cloud-based processing 65% and edge processing 35%, with cloud processing dominating due to centralized computing power, scalability, and widespread adoption in data centers. Edge processing is growing rapidly with demand for real-time AI inference, low latency, and reduced bandwidth usage in applications such as autonomous vehicles, smart cameras, and industrial automation. Expansion of IoT and 5G infrastructure supports edge AI growth.

By Technology
Technologies include system on chip (SoC) 45%, system in package (SiP) 25%, multi-chip module (MCM) 20%, and others 10%, with SoC dominating due to integration of processing, memory, and connectivity in a compact form factor. SiP and MCM technologies are gaining traction for high-performance and heterogeneous computing requirements. Advanced semiconductor packaging and performance optimization drive technology adoption.

By Application
Applications include computer vision 30%, natural language processing 25%, robotics 15%, network security 15%, and others 15%, with computer vision and NLP dominating due to adoption in surveillance, facial recognition, autonomous systems, chatbots, and virtual assistants. Robotics and network security are growing with automation and AI-driven threat detection. Increasing enterprise AI deployment drives application growth.

By Industry Vertical
Industry verticals include IT & telecom 25%, BFSI 20%, automotive & transportation 15%, healthcare 15%, media & advertising 10%, retail 10%, and others 5%, with IT & telecom and BFSI dominating due to large-scale data processing, AI-driven analytics, and automation. Automotive and healthcare are high-growth segments driven by autonomous driving, diagnostics, and personalized medicine. Digital transformation across industries supports market expansion.

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Regional Analysis
North America - 35% Share
North America leads with 35% share due to strong presence of AI chip manufacturers, cloud service providers, and technology giants in the U.S. GPUs and ASICs dominate. Cloud-based processing leads. Computer vision and NLP are key applications. IT & telecom and BFSI are major end-users. Strong R&D investment and early AI adoption drive growth.

Asia Pacific - 30% Share
Asia Pacific accounts for 30% share driven by China, Japan, South Korea, and Taiwan. ASICs and SoC technologies dominate. Edge processing is growing rapidly. Computer vision and robotics lead applications. Automotive, electronics, and IT sectors drive demand. Semiconductor manufacturing strength and government AI initiatives support growth.

Europe - 20% Share
Europe holds 20% share with strong adoption in Germany, the U.K., and France. GPUs and FPGAs dominate. Cloud processing leads with increasing edge adoption. Automotive, healthcare, and industrial automation are key verticals. Regulatory support and AI-driven industrial transformation drive market growth.

South America - 5% Share
South America records 5% share driven by Brazil and Argentina. Cloud-based AI chips dominate. NLP and network security applications lead. BFSI and retail are key verticals. Growing digitalization and cloud adoption support market expansion.

Middle East & Africa - 10% Share
Middle East & Africa hold 10% share due to adoption in UAE, Saudi Arabia, and South Africa. GPUs and SoC technologies dominate. Cloud processing leads. Computer vision and network security are key applications. Government-led digital transformation and smart city initiatives drive market growth.

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✅ Competitive Landscape
✅ Technology Roadmap Analysis
✅ Sustainability Impact Analysis
✅ KOL / Stakeholder Insights
✅ Consumer Behavior & Demand Analysis
✅ Import-Export Data Monitoring
✅ Live Market & Pricing Trends

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