Artificial Intelligence Market Size, Share | Forecast – 2033

The AI Infrastructure Global Market Report 2024 by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).

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According to The Business Research Company’s AI Infrastructure Global Market Report 2024, The ai infrastructure market size has grown exponentially in recent years. It will grow from $44.28 billion in 2023 to $58.07 billion in 2024 at a compound annual growth rate (CAGR) of 31.2%.  The  growth in the historic period can be attributed to increased data generation, advancements in deep learning, demand for real-time processing, regulatory compliance requirements, data privacy and security concerns..

The ai infrastructure market size is expected to see exponential growth in the next few years. It will grow to $169.16 billion in 2028 at a compound annual growth rate (CAGR) of 30.6%.  The growth in the forecast period can be attributed to quantum computing advances, energy efficiency considerations, growth of explainable ai standards, personalization in customer experience, rapid growth in ai applications.. Major trends in the forecast period include rapid growth in ai adoption across industries, expansion of edge ai, development of ai-specific hardware, hybrid and multi-cloud deployments, ai-optimized storage solutions, ai security and ethical considerations, collaboration between ai and cloud providers..

The increase in data traffic and need for high computing power are expected to propel the growth of the AI infrastructure market going forward. Data traffic refers to the amount of data moving across a computer network at any given time. In contrast, high computing power refers to the ability of systems to process data and perform complex calculations at high speeds. HPC infrastructure helps AI models with storage, networking, and data processing to make AI projects work at scale by processing workloads quickly, significantly speeding up the training stage, and boosting the accuracy and reliability of AI models in minimum time. For instance, in June 2022, according to Ericsson, a Sweden-based networking and telecommunications company, the company reported that mobile network data traffic grew 10% between the fourth quarter of 2021 and the first quarter of 2022. For the year-over-year comparison, that growth reached 40%. Further, in May 2022, according to International Data Corporation (IDC), a US-based advisory services provider in information technology and telecommunications, approximately 50% of startups in Asia-Pacific focus on high-performance computing infrastructure to address genomic data challenges in life sciences due to its high computing capabilities. Therefore, the increasing data traffic and need for high computing power are driving the growth of the AI infrastructure market.

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The ai infrastructure market covered in this report is segmented –

1) By Offerings: Hardware, Server Software

2) By Function: Training, Inference

3) By Technology: Machine Learning, Deep Learning

4) By Deployment Type: On-Premises, Cloud, Hybrid

5) By End User: Enterprises, Government Organizations, Cloud Service Providers

Technological advancement is the key trend that is gaining popularity in the AI infrastructure market. Major companies operating in the AI infrastructure market are focused on developing new technological solutions to strengthen their position. For instance, in June 2021, Nvidia Corporation, a US-based company operating in AI infrastructure, introduced NVIDIA AI Launchpad, an end-to-end, cloud-native suite of AI and data analytics software, to streamline the entire AI lifecycle and deploy AI infrastructure quicker and support every aspect of AI virtually such as data center training and inference to full-scale deployment at the edge. Moreover, NVIDIA AI LaunchPad is compatible with GPUs and DPUs-based systems, and this combination will help enterprises with the ability to accelerate AI workloads and also advantage of security, isolation, and performance enhancements provided by DPUs.

The ai infrastructure market report table of contents includes:

 

1. Executive Summary
2. AI Infrastructure  Market Characteristics
3. AI Infrastructure  Market Trends And Strategies
4. AI Infrastructure  Market – Macro Economic Scenario
5. Global AI Infrastructure  Market Size and Growth

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31. Global AI Infrastructure  Market Competitive Benchmarking
32. Global AI Infrastructure  Market Competitive Dashboard
33. Key Mergers And Acquisitions In The AI Infrastructure  Market
34. AI Infrastructure  Market Future Outlook and Potential Analysis
35. Appendix

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