Artificial intelligence (AI) is rapidly transforming industries, from facial recognition on your smartphone to self-driving cars. But the brains behind this revolution are tiny — AI chipsets. These specialized processors are designed to handle the complex calculations needed for AI applications, and the market for these powerful components is experiencing explosive growth.

Market Boom Fueled by Innovation

The AI chipsets market, valued at USD 51.2 billion in 2023, is projected to reach a staggering USD 131.8 billion by 2028. This translates to a compound annual growth rate (CAGR) of 20.8%, highlighting the rapid pace of adoption. Several factors are fueling this market expansion:

  • Surging Demand for AI Applications: The increasing use of AI in various sectors like healthcare, manufacturing, and finance creates a significant demand for efficient AI chipsets. These applications require high processing power and specialized architecture to handle massive datasets and complex algorithms.
  • Advancements in AI Technology: As AI algorithms become more sophisticated, the demand for chipsets capable of handling ever-increasing workloads grows. AI chip developers are continuously innovating, creating new architectures and functionalities to meet the evolving needs of AI applications.
  • Growth of Edge Computing: The rise of edge computing, where data processing occurs closer to its source, necessitates the development of low-power and efficient AI chipsets. These edge AI chips enable real-time decision-making and faster response times in applications like autonomous vehicles and industrial automation.
  • Cloud Adoption and Data Centers: The growing reliance on cloud computing for AI applications drives the demand for high-performance AI chipsets in data centers. These data center-specific chipsets offer superior processing power and scalability for large-scale AI workloads.

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Market Landscape and the Future

The AI chipsets market comprises various players, including:

  • Established semiconductor giants like Intel, Nvidia, and AMD are investing heavily in developing next-generation AI chipsets.
  • Specialized AI chip startups are emerging, offering innovative architectures tailored to specific AI applications.
  • Cloud service providers like Google and Amazon are designing custom AI chipsets for their cloud platforms.

Looking ahead, the AI chipsets market is expected to witness exciting advancements in several areas:

  • Neuromorphic Computing: This technology mimics the structure and function of the human brain, promising significant performance improvements for specific AI tasks.
  • Increased Focus on Efficiency: The development of low-power AI chipsets will be crucial for battery-powered devices and edge computing applications.
  • Integration with Other Technologies: We may see greater integration of AI chipsets with other components like memory and storage, creating more powerful and compact AI processing units.

In Conclusion

The AI chipsets market is a dynamic and rapidly growing sector. As AI technology continues to evolve and penetrate new industries, the demand for these specialized processors will undoubtedly soar. By powering the next generation of intelligent devices and applications, AI chipsets are poised to be a cornerstone of the technological revolution in the years to come.

1 INTRODUCTION (Page No. — 29)

1.1 STUDY OBJECTIVES

1.2 MARKET DEFINITION

1.2.1 INCLUSIONS AND EXCLUSIONS

1.3 STUDY SCOPE

1.3.1 MARKETS COVERED

FIGURE 1 AI CHIPSETS MARKET SEGMENTATION

1.3.2 REGIONAL SCOPE

1.3.3 YEARS CONSIDERED

1.4 CURRENCY CONSIDERED

1.5 STAKEHOLDERS

1.6 SUMMARY OF CHANGES

1.7 RECESSION IMPACT

FIGURE 2 GDP GROWTH PROJECTION UNTIL 2023 FOR MAJOR ECONOMIES

FIGURE 3 PROJECTIONS FOR AI CHIPSETS MARKET, 2019–2028

2 RESEARCH METHODOLOGY (Page No. — 36)

2.1 RESEARCH DATA

FIGURE 4 AI CHIPSETS MARKET: RESEARCH DESIGN

2.1.1 SECONDARY DATA

2.1.1.1 Major secondary sources

2.1.1.2 Key data from secondary sources

2.1.2 PRIMARY DATA

2.1.2.1 Primary interviews with experts

2.1.2.2 Key data from primary sources

2.1.2.3 Key industry insights

2.1.2.4 Breakdown of primaries

2.1.3 SECONDARY AND PRIMARY RESEARCH

2.2 MARKET SIZE ESTIMATION

FIGURE 5 RESEARCH FLOW FOR MARKET SIZE ESTIMATION

FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY (SUPPLY SIDE): REVENUE GENERATED FROM SALES OF AI CHIPSETS (FOR CLOUD & DATA CENTRE)

2.2.1 BOTTOM-UP APPROACH

2.2.1.1 Approach to derive market size using bottom-up analysis

FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH

2.2.2 TOP-DOWN APPROACH

2.2.2.1 Approach to derive market size using top-down analysis

FIGURE 8 TOP-DOWN APPROACH

2.3 DATA TRIANGULATION

FIGURE 9 DATA TRIANGULATION

2.4 RESEARCH ASSUMPTIONS

2.5 RISK ASSESSMENT

TABLE 1 RISK FACTOR ANALYSIS

2.6 ASSUMPTIONS TO ANALYZE RECESSION IMPACT

TABLE 2 ASSUMPTIONS: RECESSION IMPACT

2.7 RESEARCH LIMITATIONS