The blockchain AI trade was estimated to be around US$ 358.4 million in 2022. The overall market is expected to be around US$ 440 million in 2023. According to the analysis, the global blockchain AI market is anticipated to secure US$ 3,536.2 million in 2032, while flourishing at a 22.9% CAGR from 2023 to 2033.
Increasing adoption of AI-based blockchain platforms among SMEs to enhance blockchain applications like smart contracts, payment systems, and others is projected to fuel the market. Also, the development of cryptocurrency is projected to play a vital role in strengthening the market.
Increasing adoption of AI-based blockchain platforms and services among SMEs to augment blockchain applications like smart contracts, payment systems, and others is anticipated to drive the market in the forecast period.
Attribute | Details |
---|---|
Global Blockchain AI Market Valuation in 2022 | US$ 358.4 million |
Estimated Global Market Share in 2023 | US$ 440 million |
Forecasted Global Market Size by 2033 | US$ 3,536.2 million |
Projected Global Market Growth Rate from 2023 to 2033 | 22.9% CAGR |
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Increasing Monetization of Customer Data with the Application of Blockchain to Support Market Growth
Blockchain AI technologies enable data monetization, which is expected to be a significant factor driving the market during the forecast period. Data monetization would make AI and advanced blockchain easily accessible to emerging companies. A decentralized market would make such space for smaller companies which, otherwise, would have been very expensive. Also, developments in artificial intelligence (AI), the Internet of Things (IoT), and big data technologies are projected to boost the application of data monetization solutions among organizations.
Key participants of players are targeted at launching new products to meet the growing demands. In an occurrence, in February 2019, Continental AG and Hewlett Packard Enterprise (HPE) launched a new blockchain-based platform known as the Data Monetization Platform. It assists car manufacturers to monetize their data and offers data security to meet issues related to the sharing of vehicle data.
Growing demand for the combination of blockchain and AI-based natural language processing (NLP) solutions among established is anticipated to be the major emerging trend for the market expansion. The fault-tolerant features along with the non-modifiable, and immutable specifics of blockchain are crucial for the security of sensitive data produced by NLP solutions and algorithms.
NLP blockchain solutions also witness considerable demand in the healthcare sector owing to their ability to enhance patient experience and care by using advanced NLP platforms that offers significant insights from medical data. The amalgamation of these two technologies can offer precise results.
For instance, in September 2019, Zensar Technologies Limited launched its blockchain-based management solutions- DICES (Distributed Intelligent Contract Enforcement System) and ZenConfluence- for several organizations. The objective is to assist end-users track the contractual goals without manual intervention efficiently.
The lack of blockchain AI experts is anticipated to act as a significant restraint to the market in the forecast period. Blockchain AI is at a nascent stage and is complex in nature. Therefore, organizations demand expertise in managing blockchain solutions powered by AI. The technology offers various benefits, however, lack of awareness, inadequate funding, and poor investments are likely to hamper the market growth in the forecast period. Also, uncertain regulations are also projected to hinder the industry growth.
Decentralization and data control are likely to hinder privacy and act as a significant challenge to the market. When the need for an intermediary is eliminated, decentralization puts the user completely in charge of their data. That is why various data sets are acquired by several organizations, users retain their data ownership and can determine who has access to the same.
Blockchain AI Market:
Attributes | Blockchain AI Market |
---|---|
CAGR (2023 to 2033) | 22.9% |
Market Value (2033) | US$ 3.5 billion |
Growth Factor | Increasing demand for intelligent virtual assistants is expected to propel the industry |
Opportunity | Growing acceptance of cloud-based security solutions is projected to offer significant opportunities for market expansion. |
Blockchain Market:
Attributes | Blockchain Market |
---|---|
CAGR (2023 to 2033) | 68% |
Market Value (2033) | US$ 1.25 billion |
Growth Factor | Increasing venture capital funding in blockchain technology and the rapidly rising adoption of blockchain solutions for smart contracts, payment, and digital identities are expected to boost market growth. |
Opportunity | Integration of blockchain, IoT, and AI is expected to offer lucrative market opportunities for market growth in the coming time. |
Artificial Intelligence Market:
Attributes | Artificial Intelligence Market |
---|---|
CAGR (2023 to 2033) | 39% |
Market Value (2033) | US$ 2.178 billion |
Growth Factor | The expansion of data-based AI and development in deep learning is expected to drive the market in the forecast period. |
Opportunity | Increasing application and easy implementation methods of AI have encouraged investments by the government in AI and other associated technologies, which are projected to offer significant opportunities to the market. |
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Based on Components, the global market can be segmented into services and platforms/tools. Based on organization size, the global blockchain AI market can be segmented into SMEs and Large Enterprises. As per the analysis, by component, the platform segment is likely to expand at a CAGR of 21.3% during the forecast period.
The platform segment is expected to flourish owing to the increasing demand for blockchain artificial AI-based platforms across various spheres of enterprises to assure safe transaction models in their business units. On the other hand, the services segment is projected to witness significant demand in the coming time.
Based on Application, the global market can be segmented into Smart Contracts, Payment and Settlement, Data Security, Data Sharing/Communication, Asset Tracking and Management, Logistics and Supply Chain Management, Business Process Optimization, and others.
The BFSI industry is projected to offer lucrative opportunities for market expansion in the forecast period. The scope of expansion can be attributed to the increasing adoption of decentralized applications based on AI technology across fintech and financial institutions. The banking sector is focused on implementing various projects dependent on blockchain services.
Category | By Component |
---|---|
Top Segment | Platform or Tool |
Market Share in Percentage | 71.2% |
Category | By Technology |
---|---|
Top Segment | ML-based Blockchain AI |
Market Share in Percentage | 36.4% |
Based on technology, the global market can be segmented into ML, NLP, Context-Aware Computing, and Computer Vision. Based on Vertical, the global blockchain AI market can be segmented into BFSI, Telecom and IT, Healthcare and Life Science, Manufacturing, Media and Entertainment, Automotive, and others.
The growth can be attributed to the growing demand for blockchain services like support & maintenance, systems integration & deployment, & technology advisory & consulting from several industries is expected to boost the segment growth.By deployment, the cloud segment is projected to record a 20.6% CAGR in the forecast period. The segment is projected to garner a larger market share in the coming time. The growth of the segment can be attributed to the growing adoption of cloud-based solutions and services.
Based on deployment mode, the global market can be segmented into cloud and on-premises. The cloud also offers trained network solutions and services which strengthens building blockchain applications based on AI. On the other hand, the on-premise segment is expected to record significant growth due to the growing investments in AI blockchain platforms by SMEs and governments.
Regional Market Comparison | Global Market Share in Percentage |
---|---|
North America | 29.4% |
Europe | 22.6% |
According to the analysis, the global market is estimated to be dominated by North America. The USA is anticipated to garner the largest market share in the forecast period. It is estimated at US$ 917.7 million, recording a CAGR of 22.2% during the forecast period.
There were nearly 2,000 blockchain projects in the USA from 2014 to 2017, reveals the China Academy of Information and Communications Technology (CAICT). Also, the government in the USA is focused on deploying blockchain artificial intelligence-based solutions in various spheres.
Europe is likely to garner considerable market share with the United Kingdom contributing US$ 123.5 million, expanding at 21.5% CAGR. Sectors such as ITC, automotive, media, and entertainment, among others, are some of the most significant consumers. Also, rapid digitalization is expected to positively benefit the market in the region in the coming time.
Regional Market Comparison | Global Market Share in Percentage |
---|---|
United States | 20.1% |
Germany | 8.6% |
Japan | 6.1% |
Australia | 2.2% |
Growing partnerships among players are expected to augment the market in the United Kingdom. For instance, in March 2020, London-based West Ham United FC announced an AI partnership with British Blockchain firm Fetch Ai.
Asia Pacific is projected to be the most lucrative market in the assessment period. The region is witnessing rapid adoption of advanced technologies, which acts as a salient factor boosting the market in Asia Pacific. Emerging nations such as China, Japan, and South Korea are recognized to be the most remunerative markets.
As per the analysis, China, Japan, and South Korea are projected at US$ 208.2 million, US$ 175.5 million, and US$ 111.4 million respectively. Also, the three countries are expected to flourish at a healthy CAGR with China expanding at 22.1%, Japan at 21.4%, and South Korea at 21.1% in the forecast period.
The development of the region can be attributed to the increasing investments by governments. For instance, in May 2020, Tencent Holdings Ltd., the parent company of WeChat, made an investment of USD 70 billion into AI, Cybersecurity, Blockchain, and others in pursuit of new infrastructures.
Countries | Estimated CAGR (2023 to 2033) |
---|---|
India | 20.3% |
United Kingdom | 21.7% |
China | 22.4% |
Japan | 21.4% |
South Korea | 21.1% |
Key players in the global blockchain AI business include Core Scientific, BurstIQ, Alpha Networks, Cyware, NeuroChain Tech, and Core Scientific among others.
Recent developments among key players are:
The market is valued at US$ 440 million in 2023.
Platform or Tool is said to dominate the market.
India is likely to expand at a CAGR of 20.3% from 2023 to 2033.
The United Kingdom market is likely to account for a CAGR of 21.7% from 2023 to 2033.
The lack of blockchain AI experts restrains the market from 2023 to 2033.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033 4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022 4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Component 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Component, 2018 to 2022 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Component, 2023 to 2033 5.3.1. Services 5.3.2. Platform 5.4. Y-o-Y Growth Trend Analysis By Component, 2018 to 2022 5.5. Absolute $ Opportunity Analysis By Component, 2023 to 2033 6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment Mode 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Deployment Mode, 2018 to 2022 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Mode, 2023 to 2033 6.3.1. Cloud-based 6.3.2. On-premises 6.4. Y-o-Y Growth Trend Analysis By Deployment Mode, 2018 to 2022 6.5. Absolute $ Opportunity Analysis By Deployment Mode, 2023 to 2033 7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Organization Size 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Organization Size , 2018 to 2022 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Organization Size , 2023 to 2033 7.3.1. Large Enterprises 7.3.2. SMEs 7.4. Y-o-Y Growth Trend Analysis By Organization Size , 2018 to 2022 7.5. Absolute $ Opportunity Analysis By Organization Size , 2023 to 2033 8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Technology 8.1. Introduction / Key Findings 8.2. Historical Market Size Value (US$ Million) Analysis By Technology, 2018 to 2022 8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Technology, 2023 to 2033 8.3.1. ML-based 8.3.2. NLP-based 8.3.3. Context-Aware Computing-based 8.3.4. Computer Vision-based 8.4. Y-o-Y Growth Trend Analysis By Technology, 2018 to 2022 8.5. Absolute $ Opportunity Analysis By Technology, 2023 to 2033 9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Vertical 9.1. Introduction / Key Findings 9.2. Historical Market Size Value (US$ Million) Analysis By Vertical, 2018 to 2022 9.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Vertical, 2023 to 2033 9.3.1. Telecom and IT 9.3.2. BFSI 9.3.3. Healthcare and Life Sciences 9.3.4. Manufacturing 9.3.5. Media and Entertainment 9.3.6. Automotive 9.3.7. Others 9.4. Y-o-Y Growth Trend Analysis By Vertical, 2018 to 2022 9.5. Absolute $ Opportunity Analysis By Vertical, 2023 to 2033 10. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Application 10.1. Introduction / Key Findings 10.2. Historical Market Size Value (US$ Million) Analysis By Application, 2018 to 2022 10.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2023 to 2033 10.3.1. Smart Contracts 10.3.2. Payment and Settlement 10.3.3. Data Security 10.3.4. Data Sharing 10.3.5. Asset Tracking and Management 10.3.6. Logistics and Supply Chain Management 10.3.7. Business Process Optimization 10.3.8. Others 10.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022 10.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033 11. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region 11.1. Introduction 11.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022 11.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033 11.3.1. North America 11.3.2. Latin America 11.3.3. Europe 11.3.4. South Asia 11.3.5. East Asia 11.3.6. Oceania 11.3.7. MEA 11.4. Market Attractiveness Analysis By Region 12. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 12.2.1. By Country 12.2.1.1. The USA 12.2.1.2. Canada 12.2.2. By Component 12.2.3. By Deployment Mode 12.2.4. By Organization Size 12.2.5. By Technology 12.2.6. By Vertical 12.2.7. By Application 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Component 12.3.3. By Deployment Mode 12.3.4. By Organization Size 12.3.5. By Technology 12.3.6. By Vertical 12.3.7. By Application 12.4. Key Takeaways 13. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 13.2.1. By Country 13.2.1.1. Brazil 13.2.1.2. Mexico 13.2.1.3. Rest of Latin America 13.2.2. By Component 13.2.3. By Deployment Mode 13.2.4. By Organization Size 13.2.5. By Technology 13.2.6. By Vertical 13.2.7. By Application 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Component 13.3.3. By Deployment Mode 13.3.4. By Organization Size 13.3.5. By Technology 13.3.6. By Vertical 13.3.7. By Application 13.4. Key Takeaways 14. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 14.2.1. By Country 14.2.1.1. Germany 14.2.1.2. United Kingdom 14.2.1.3. France 14.2.1.4. Spain 14.2.1.5. Italy 14.2.1.6. Rest of Europe 14.2.2. By Component 14.2.3. By Deployment Mode 14.2.4. By Organization Size 14.2.5. By Technology 14.2.6. By Vertical 14.2.7. By Application 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Component 14.3.3. By Deployment Mode 14.3.4. By Organization Size 14.3.5. By Technology 14.3.6. By Vertical 14.3.7. By Application 14.4. Key Takeaways 15. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 15.2.1. By Country 15.2.1.1. India 15.2.1.2. Malaysia 15.2.1.3. Singapore 15.2.1.4. Thailand 15.2.1.5. Rest of South Asia 15.2.2. By Component 15.2.3. By Deployment Mode 15.2.4. By Organization Size 15.2.5. By Technology 15.2.6. By Vertical 15.2.7. By Application 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Component 15.3.3. By Deployment Mode 15.3.4. By Organization Size 15.3.5. By Technology 15.3.6. By Vertical 15.3.7. By Application 15.4. Key Takeaways 16. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 16.2.1. By Country 16.2.1.1. China 16.2.1.2. Japan 16.2.1.3. South Korea 16.2.2. By Component 16.2.3. By Deployment Mode 16.2.4. By Organization Size 16.2.5. By Technology 16.2.6. By Vertical 16.2.7. By Application 16.3. Market Attractiveness Analysis 16.3.1. By Country 16.3.2. By Component 16.3.3. By Deployment Mode 16.3.4. By Organization Size 16.3.5. By Technology 16.3.6. By Vertical 16.3.7. By Application 16.4. Key Takeaways 17. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 17.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 17.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 17.2.1. By Country 17.2.1.1. Australia 17.2.1.2. New Zealand 17.2.2. By Component 17.2.3. By Deployment Mode 17.2.4. By Organization Size 17.2.5. By Technology 17.2.6. By Vertical 17.2.7. By Application 17.3. Market Attractiveness Analysis 17.3.1. By Country 17.3.2. By Component 17.3.3. By Deployment Mode 17.3.4. By Organization Size 17.3.5. By Technology 17.3.6. By Vertical 17.3.7. By Application 17.4. Key Takeaways 18. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 18.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 18.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 18.2.1. By Country 18.2.1.1. GCC Countries 18.2.1.2. South Africa 18.2.1.3. Israel 18.2.1.4. Rest of MEA 18.2.2. By Component 18.2.3. By Deployment Mode 18.2.4. By Organization Size 18.2.5. By Technology 18.2.6. By Vertical 18.2.7. By Application 18.3. Market Attractiveness Analysis 18.3.1. By Country 18.3.2. By Component 18.3.3. By Deployment Mode 18.3.4. By Organization Size 18.3.5. By Technology 18.3.6. By Vertical 18.3.7. By Application 18.4. Key Takeaways 19. Key Countries Market Analysis 19.1. USA 19.1.1. Pricing Analysis 19.1.2. Market Share Analysis, 2022 19.1.2.1. By Component 19.1.2.2. By Deployment Mode 19.1.2.3. By Organization Size 19.1.2.4. By Technology 19.1.2.5. By Vertical 19.1.2.6. By Application 19.2. Canada 19.2.1. Pricing Analysis 19.2.2. Market Share Analysis, 2022 19.2.2.1. By Component 19.2.2.2. By Deployment Mode 19.2.2.3. By Organization Size 19.2.2.4. By Technology 19.2.2.5. By Vertical 19.2.2.6. By Application 19.3. Brazil 19.3.1. Pricing Analysis 19.3.2. Market Share Analysis, 2022 19.3.2.1. By Component 19.3.2.2. By Deployment Mode 19.3.2.3. By Organization Size 19.3.2.4. By Technology 19.3.2.5. By Vertical 19.3.2.6. By Application 19.4. Mexico 19.4.1. Pricing Analysis 19.4.2. Market Share Analysis, 2022 19.4.2.1. By Component 19.4.2.2. By Deployment Mode 19.4.2.3. By Organization Size 19.4.2.4. By Technology 19.4.2.5. By Vertical 19.4.2.6. By Application 19.5. Germany 19.5.1. Pricing Analysis 19.5.2. Market Share Analysis, 2022 19.5.2.1. By Component 19.5.2.2. By Deployment Mode 19.5.2.3. By Organization Size 19.5.2.4. By Technology 19.5.2.5. By Vertical 19.5.2.6. By Application 19.6. United Kingdom 19.6.1. Pricing Analysis 19.6.2. Market Share Analysis, 2022 19.6.2.1. By Component 19.6.2.2. By Deployment Mode 19.6.2.3. By Organization Size 19.6.2.4. By Technology 19.6.2.5. By Vertical 19.6.2.6. By Application 19.7. France 19.7.1. Pricing Analysis 19.7.2. Market Share Analysis, 2022 19.7.2.1. By Component 19.7.2.2. By Deployment Mode 19.7.2.3. By Organization Size 19.7.2.4. By Technology 19.7.2.5. By Vertical 19.7.2.6. By Application 19.8. Spain 19.8.1. Pricing Analysis 19.8.2. Market Share Analysis, 2022 19.8.2.1. By Component 19.8.2.2. By Deployment Mode 19.8.2.3. By Organization Size 19.8.2.4. By Technology 19.8.2.5. By Vertical 19.8.2.6. By Application 19.9. Italy 19.9.1. Pricing Analysis 19.9.2. Market Share Analysis, 2022 19.9.2.1. By Component 19.9.2.2. By Deployment Mode 19.9.2.3. By Organization Size 19.9.2.4. By Technology 19.9.2.5. By Vertical 19.9.2.6. By Application 19.10. India 19.10.1. Pricing Analysis 19.10.2. Market Share Analysis, 2022 19.10.2.1. By Component 19.10.2.2. By Deployment Mode 19.10.2.3. By Organization Size 19.10.2.4. By Technology 19.10.2.5. By Vertical 19.10.2.6. By Application 19.11. Malaysia 19.11.1. Pricing Analysis 19.11.2. Market Share Analysis, 2022 19.11.2.1. By Component 19.11.2.2. By Deployment Mode 19.11.2.3. By Organization Size 19.11.2.4. By Technology 19.11.2.5. By Vertical 19.11.2.6. By Application 19.12. Singapore 19.12.1. Pricing Analysis 19.12.2. Market Share Analysis, 2022 19.12.2.1. By Component 19.12.2.2. By Deployment Mode 19.12.2.3. By Organization Size 19.12.2.4. By Technology 19.12.2.5. By Vertical 19.12.2.6. By Application 19.13. Thailand 19.13.1. Pricing Analysis 19.13.2. Market Share Analysis, 2022 19.13.2.1. By Component 19.13.2.2. By Deployment Mode 19.13.2.3. By Organization Size 19.13.2.4. By Technology 19.13.2.5. By Vertical 19.13.2.6. By Application 19.14. China 19.14.1. Pricing Analysis 19.14.2. Market Share Analysis, 2022 19.14.2.1. By Component 19.14.2.2. By Deployment Mode 19.14.2.3. By Organization Size 19.14.2.4. By Technology 19.14.2.5. By Vertical 19.14.2.6. By Application 19.15. Japan 19.15.1. Pricing Analysis 19.15.2. Market Share Analysis, 2022 19.15.2.1. By Component 19.15.2.2. By Deployment Mode 19.15.2.3. By Organization Size 19.15.2.4. By Technology 19.15.2.5. By Vertical 19.15.2.6. By Application 19.16. South Korea 19.16.1. Pricing Analysis 19.16.2. Market Share Analysis, 2022 19.16.2.1. By Component 19.16.2.2. By Deployment Mode 19.16.2.3. By Organization Size 19.16.2.4. By Technology 19.16.2.5. By Vertical 19.16.2.6. By Application 19.17. Australia 19.17.1. Pricing Analysis 19.17.2. Market Share Analysis, 2022 19.17.2.1. By Component 19.17.2.2. By Deployment Mode 19.17.2.3. By Organization Size 19.17.2.4. By Technology 19.17.2.5. By Vertical 19.17.2.6. By Application 19.18. New Zealand 19.18.1. Pricing Analysis 19.18.2. Market Share Analysis, 2022 19.18.2.1. By Component 19.18.2.2. By Deployment Mode 19.18.2.3. By Organization Size 19.18.2.4. By Technology 19.18.2.5. By Vertical 19.18.2.6. By Application 19.19. GCC Countries 19.19.1. Pricing Analysis 19.19.2. Market Share Analysis, 2022 19.19.2.1. By Component 19.19.2.2. By Deployment Mode 19.19.2.3. By Organization Size 19.19.2.4. By Technology 19.19.2.5. By Vertical 19.19.2.6. By Application 19.20. South Africa 19.20.1. Pricing Analysis 19.20.2. Market Share Analysis, 2022 19.20.2.1. By Component 19.20.2.2. By Deployment Mode 19.20.2.3. By Organization Size 19.20.2.4. By Technology 19.20.2.5. By Vertical 19.20.2.6. By Application 19.21. Israel 19.21.1. Pricing Analysis 19.21.2. Market Share Analysis, 2022 19.21.2.1. By Component 19.21.2.2. By Deployment Mode 19.21.2.3. By Organization Size 19.21.2.4. By Technology 19.21.2.5. By Vertical 19.21.2.6. By Application 20. Market Structure Analysis 20.1. Competition Dashboard 20.2. Competition Benchmarking 20.3. Market Share Analysis of Top Players 20.3.1. By Regional 20.3.2. By Component 20.3.3. By Deployment Mode 20.3.4. By Organization Size 20.3.5. By Technology 20.3.6. By Vertical 20.3.7. By Application 21. Competition Analysis 21.1. Competition Deep Dive 21.1.1. Core Scientific 21.1.1.1. Overview 21.1.1.2. Product Portfolio 21.1.1.3. Profitability by Market Segments 21.1.1.4. Sales Footprint 21.1.1.5. Strategy Overview 21.1.1.5.1. Marketing Strategy 21.1.2. BurstIQ 21.1.2.1. Overview 21.1.2.2. Product Portfolio 21.1.2.3. Profitability by Market Segments 21.1.2.4. Sales Footprint 21.1.2.5. Strategy Overview 21.1.2.5.1. Marketing Strategy 21.1.3. Alpha Networks 21.1.3.1. Overview 21.1.3.2. Product Portfolio 21.1.3.3. Profitability by Market Segments 21.1.3.4. Sales Footprint 21.1.3.5. Strategy Overview 21.1.3.5.1. Marketing Strategy 21.1.4. Cyware 21.1.4.1. Overview 21.1.4.2. Product Portfolio 21.1.4.3. Profitability by Market Segments 21.1.4.4. Sales Footprint 21.1.4.5. Strategy Overview 21.1.4.5.1. Marketing Strategy 21.1.5. NeuroChain Tech 21.1.5.1. Overview 21.1.5.2. Product Portfolio 21.1.5.3. Profitability by Market Segments 21.1.5.4. Sales Footprint 21.1.5.5. Strategy Overview 21.1.5.5.1. Marketing Strategy 21.1.6. IBM 21.1.6.1. Overview 21.1.6.2. Product Portfolio 21.1.6.3. Profitability by Market Segments 21.1.6.4. Sales Footprint 21.1.6.5. Strategy Overview 21.1.6.5.1. Marketing Strategy 21.1.7. Oracle 21.1.7.1. Overview 21.1.7.2. Product Portfolio 21.1.7.3. Profitability by Market Segments 21.1.7.4. Sales Footprint 21.1.7.5. Strategy Overview 21.1.7.5.1. Marketing Strategy 21.1.8. Amazon Web Services (AWS) 21.1.8.1. Overview 21.1.8.2. Product Portfolio 21.1.8.3. Profitability by Market Segments 21.1.8.4. Sales Footprint 21.1.8.5. Strategy Overview 21.1.8.5.1. Marketing Strategy 21.1.9. ConsenSys 21.1.9.1. Overview 21.1.9.2. Product Portfolio 21.1.9.3. Profitability by Market Segments 21.1.9.4. Sales Footprint 21.1.9.5. Strategy Overview 21.1.9.5.1. Marketing Strategy 21.1.10. Google 21.1.10.1. Overview 21.1.10.2. Product Portfolio 21.1.10.3. Profitability by Market Segments 21.1.10.4. Sales Footprint 21.1.10.5. Strategy Overview 21.1.10.5.1. Marketing Strategy 22. Assumptions & Acronyms Used 23. Research Methodology
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