The Business Research Company’s AI-Powered Storage Global Market Report 2023 is the most detailed report available on the market, including broad forecast periods and multiple geographies. The report covers the historic period – 2010-2021, and the forecast period – 2023-2032. The AI-Powered Storage Global Market Report 2023 evaluates AI-powered storage market size, growth rate, drivers, trends, and major companies.
The report provides a global perspective by covering 60 geographies and focusing on major economies in each region – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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The global AI-Powered storage market is expected to grow from $20.77 billion in 2022 to $25.99 billion in 2023 at a compound annual growth rate (CAGR) of 25.1%. The Russia-Ukraine war disrupted the chances of global economic recovery from the COVID-19 pandemic. The war between these two countries has led to economic sanctions on multiple countries, a surge in commodity prices, and supply chain disruptions, causing inflation across goods and services and affecting many markets across the globe. The AI-Powered storage market is expected to reach $63.47 billion in 2027 at a CAGR of 25%.
The AI-powered storage market segments in the report are:
1) By Offering: Software, Hardware
2) By Storage System: Direct-attached Storage, Network-attached Storage, Storage Area Network
3) By Storage Medium: Hard Disk Drive (HDD), Solid State Drive (SSD)
4) By Storage Architecture: File and Object-Based Storage, Block Storage
5) By End-User: Enterprises, Government Bodies, Cloud Service Providers, Telecom Companies, Other End-users
North America was the dominant region in the AI-powered storage market in 2022.
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The table of contents in TBRC’s AI-powered storage market report includes:
1. Executive Summary
2. AI-Powered Storage Market Characteristics
3. AI-Powered Storage Market Trends And Strategies
4. AI-Powered Storage Market - Macro Economic Scenario
5. Global AI-Powered Storage Historic Market Size and Growth, 2017 - 2022, Value ($ Billion)
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32. Global AI-Powered Storage Market Competitive Benchmarking
33. Global AI-Powered Storage Market Competitive Dashboard
34. Key Mergers And Acquisitions In The AI-Powered Storage Market
35. AI-Powered Storage Market Future Outlook and Potential Analysis
36. Appendix
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The report "AI-Powered Storage Market by Offering (Hardware, Software), Storage System (DAS, NAS, SAN), Storage Architecture (File & Object-Based Storage), Storage Medium (SSD, HDD), & End User (Enterprises, CSP, Government, Telecom) - Global Forecast to 2024", is expected to grow from USD 10.4 billion in 2019 to USD 34.5 billion by 2024; growing at a CAGR of 27.1%.
Major factors driving the AI-powered storage market growth are the massive growth in data volumes, the need for global enterprise infrastructure to refresh their storage architecture, increasing adoption of cloud-based services, and growing demand for AI in HPC data centers.
Storage medium include solid-state drive (SSD) and hard disk drive (HDD).
File storage manages the layout, structure of files, and directories— cataloging structure, which contains references to other computer files on physical storage.
Within file- and object-based storage, object storage is gaining major market share as it helps handle huge unstructured data, unlike file storage, which is mainly used to store structured data.
It has also been the largest economy in the world, which has high disposable income leading to increased demand for modern technologies in the country, the investments in financial AI in the United States tripled from 2013 to 2014 to a total of USD 12.2 billion and also the AI deployment in the country gives them tremendous opportunities for pilot testing and future deployment.
AI-Powered Storage MarketThe sudden challenges created by the ongoing COVID-19 are captured effectively to exhibit the long term growth projections in the MRFR report on AI-Powered Storage Market.
The growth sectors of the AI-Powered Storage Market are identified with precision for a better growth perspective.Regional AnalysisThe geographical analysis of the global AI-powered storage market has been done for North America, Europe, Asia-Pacific, and the rest of the world.
The growth of the market in North America can be attributed to the high concentration of data storage market players, easy availability of proficient technical expertise, and growing penetration of AI in manufacturing, banking, telecom, and healthcare industries.
Furthermore, the US is expected to register the highest CAGR during the forecast period in the North America AI-powered storage market.In terms of market size, Europe is expected to hold the second-largest share in the AI-Powered Storage market.
The European market has been divided into the UK, Germany, France, and the rest of Europe.
The other leading countries fueling the growth of the AI-powered storage market are Russia, Norway, Sweden, Switzerland, and Spain.The market in Asia-Pacific is expected to register the highest CAGR during the review period of 2019 to 2025.
AI and machine learning workloads require vast amounts of storage to extract translate and load input data, do exploratory data analysis to see what data is relevant, create test data, build and train the models, retrain the models to reflect changing data patterns, inferences, and discoveries and keep them running.
Data does not lose value, so data must be retained for as long as there is perceived value, and regulatory requirements like GDPR may require retention of data in a form that explains the decisions made by AI.
Scalability includes the ability to minimize the footprint and cost of storage through intelligent use of deduplication, compression, virtualization, tiering, archiving, indexing cataloging, and shredding.The efficacies of AI infrastructure generally focus on computing hardware like the general-purpose CPUs, GPUs, FPGAs, and tensor processing units.
It is astute to keep a potent compute engine well-utilized, which needs feeding it with vast amounts of information as fast as possible.
It is no longer enough to deploy capacity and connect faster drives or buy an all-flash array and assume that flash resolves all consumer problems.
There are numerous phases with different processing requirements, from model deployment, data ingestion, data discovery and visualization, data engineering, model development and training, and retention, all with various performance, tiering, and protocol requirements.
