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AI Infrastructure Market by Offering (Hardware, and Software), Technology (Machine learning and Deep learning), Function (Training and Inference), End-User (Enterprises, Government Organizations, and Cloud Service Providers), and Deployment (On-premises, Hybrid, and Cloud Based): Global Opportunity Analysis and Industry Forecast, 2020–2027
| A09353 | Pages: NA | May 2020 | 148 Views | | |
| Author(s) : NA | Tables: NA | Charts: NA | Formats*: | |
COVID-19
Pandemic disrupted the entire world and affected many industries.
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Artificial intelligence (AI) infrastructure are those platforms upon which organizations can build intelligent applications that are predictive, self-healing and that requires minimal human intervention. IT Infrastructure is strained by new age technologies like IoT, Mobility, and Big Data. The need for intelligent infrastructure is evident more than ever for harnessing the power of AI platforms. AI infrastructure covers every step of the machine learning workflow. It allows data engineers, data scientist, DevOps teams and software engineers to manage and access the computing resources to train, deploy and test AI algorithms. With the use of AI infrastructure, the workload is mapped to the correct configuration of virtual machines and servers. AI infrastructure is allowing organizations to work on capacity planning, storage management, resource utilization, anomaly detection, threat detection, and analysis.
AI Infrastructure Market Scope and Structure Analysis:
Report Metric | Details |
 Market size available for years |  2020–2027 |
 Base year considered |  2019 |
 Forecast period |  2021–2027 |
 Forecast units |  Value (USD) |
 Segments covered |  Offering, Technology, Function, End-User, Deployment, and Region |
 Geographies covered | North America (U.S. and Canada), Europe (Germany, UK, France, and the Rest of Europe), Asia-Pacific (China, Japan, India, and the Rest of Asia-Pacific), Latin America (Brazil, Mexico, and the Rest of LATAM) and The Middle East and Africa |
 Companies covered | Major players analyzed in the market include Amazon Web Services, Cisco Systems Inc., Dell, Google LLC, Intel Corporation, International Business Machines Corporation, Micron Technology Inc., Microsoft Corporation, Nvidia Corporation, Oracle Corporation, and Samsung Electronics Co. Ltd. |
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Impact of COVID-19 on AI Infrastructure Market
- Digital transformation using artificial intelligence and hybrid cloud is highly adopted amid the COVID-19 pandemic.
- New internet infrastructure procedure was critical in supporting retail supply chains during quarantine.
- Companies are shifting their investments to seize the opportunity offered by new infrastructure by being flexible and open-minded.
- Overall, the pandemic is expected to have a negative impact on the global AI Infrastructure market.
Top impacting factors: Market Scenario Analysis, Trends, Drivers and Impact Analysis
Growing acceptance of cloud machine learning platform in organizations and escalating demand for AI hardware in high-performance computing data centres is driving the growth of AI infrastructure market. Expanding usage of AI applications in vertical industries such as healthcare, automotive, BFSI, and tourism is expected to boost the market of AI infrastructure. Another factor driving the growth of AI infrastructure market. However, lack of AI hardware experts in the field is restraining the growth of AI infrastructure market. Contrarily, increasing shift of focus on developing human-aware AI systems is an opportunity for AI infrastructure market in the forecasted years.
Escalating demand for AI hardware and software
The advanced AI solutions regularly demand new software and hardware in order to keep pace with the rising amount of data generated from applications. For example, these AI based solutions need updates around annotation and collation of data sources, also in accessible creating or processing and fine-tuning models as newer data develops available. AI technology and specifically the deep learning has become one of the most important computational workloads for organisations and will boost the usage of AI infrastructure.
Increasing usage of high-performance computing solutions
To fully take benefit of the opportunities obtainable by AI, organizations need sufficient performance computing resources, including CPUs and GPUs. A CPU-based environment have handle basic AI workloads, but deep learning includes multiple big data sets and installing accessible neural network algorithms. For that, CPU-based computing might not be sufficient. Therefore, computing capacity and density will also increase, as higher efficiency networks, storage and AI-based infrastructure will be demanded.Â
Key segments covered:
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Key benefits of the report:
- This study presents the analytical depiction of the global AI infrastructure industry along with the current trends and future estimations to determine the imminent investment pockets.
- The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the global AI infrastructure market share.
- The current market is quantitatively analyzed from 2021 to 2027 to highlight the market growth scenario.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.Â
- The report provides a detailed global AI infrastructure market analysis based on competitive intensity and how the competition will take shape in coming years.
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