AI-powered e-commerce platforms scale SMB operations by providing sophisticated pricing analysis and inventory management. Encryption and blockchain applications significantly mitigate concerns about data security and privacy by enhancing data protection and ensuring the integrity and confidentiality of information.

A 2024 survey of 530 small and medium-sized businesses (SMBs) reveals that AI adoption remains modest, with only 39% leveraging this technology. Content creation seems to be the main use case, with 58% of these businesses leveraging AI to support content marketing and 49% to write social media prompts.

Despite reported satisfaction with AI’s time and cost-saving benefits, the predominant use of ChatGPT or Google Gemini mentioned in the survey suggests that these SMBs have been barely scratching the surface of AI’s full potential. Indeed, AI offers far more advanced capabilities, namely pricing analysis and inventory management. Businesses willing to embrace these tools stand to gain an immense first-mover advantage.

However, privacy and security concerns raised by many SMBs regarding deeper AI integration merit attention. The counterargument suggests that the e-commerce platforms offering smart pricing and inventory management solutions would also provide encryption and blockchain applications to mitigate risks. 

Regressions and trees: AI under the hood

Every SMB knows that setting optimal product or service prices and effectively managing inventory are crucial for growth. Price too low to beat competitors, and profits suffer. Over-order raw materials, and capital gets tied up unnecessarily. But what some businesses fail to realize is that AI-powered e-commerce platforms can perform all these tasks in real time without the risks associated with human error.

At the center is machine learning, which iteratively refines algorithms and statistical models based on input data to determine optimal prices and forecast inventory demand. The types of machine learning models employed vary across industries, but two stand out in the context of pricing and inventory management.

Regression analysis has been the gold standard in determining prices. This method involves predicting the relationship between the combined effects of multiple explanatory variables and an outcome within a multidimensional space. It achieves this by plotting a “best-fit” hyperplane through the data points in a way that minimizes the differences between the actual and predicted values. In the context of pricing, the model may consider how factors like region, market conditions, seasonality, and demand collectively impact the historical sales data of a given product or service. The resulting best-fit hyperplane would denote the most precise price point for every single permutation or change in the predictors (which could number in the millions).

What machine learning contributes to this traditional tried-and-true econometric technique is scope and velocity. Whereas human analysts would manually deploy this tool within Excel, using relatively simple data sets from prior years, machine learning conducts regression analysis on significantly more comprehensive data sets. Moreover, it can continuously adapt its analysis in real-time by feeding it the latest data. This eliminates the need for a human to spend countless hours every quarter redoing the work.

In summary, machine-learning regression ensures that price points are constantly being updated in real time with a level of precision that far surpasses human capability.

As for inventory management, an effective methodology within machine learning’s arsenal would be decision trees.

Decision trees resolve inventory challenges using a flowchart-like logic. The analysis begins by asking a core question, such as whether there is a need to order more products to prevent understocking. Next, a myriad of factors that are suspected to have an effect on this decision are fed to the model, such as current stock, recent sales, seasonal trends, economic influences, storage space, etc. Each of these factors become a branch in the decision tree. As the tree branches out, it evaluates the significance of each factor in predicting the need for product orders against historical data. For example, if data indicates that low stock levels during certain seasons consistently lead to stockouts, the model may prioritize the “current stock” branch and recommend ordering more products when stock levels are low during those seasons.

Ultimately, the tree reaches a final decision node where it determines whether to order more products. This conclusion is based on the cumulative analysis of all factors and their historical impact in similar situations.

The beauty of decision trees is that they provide businesses an objective decision-making framework that systematically and simultaneously weigh a large number of variables — a task that humans would struggle to replicate given the large volumes of data that must be processed.

The machine learning techniques discussed earlier are just examples for illustration purposes; real-world applications are considerably more advanced. The key takeaway is that e-commerce platforms offering AI-powered insights can scale any SMB— regardless of its needs.

Balancing AI with data security

With great power comes great responsibility, as the saying goes. An e-commerce platform harnesses the wondrous capabilities of AI must also guarantee the protection of its users and customers’ data. This is especially relevant given that AI routinely accesses large amounts of data, increasing the risk of data breaches. Without proper security measures, sensitive information can be exposed through cyber-attacks.

When customers are browsing an online marketplace, data privacy and security are top of mind. According to a PwC survey, 71% of consumers will not purchase from a business they do not trust. Along the same lines, 81% would cease doing business with an online company following a data breach, and 97% have expressed concern that businesses might misuse their data.

Fortunately, e-commerce platforms provide various cybersecurity measures, addressing security compromises and reassuring both customers and the SMBs that host their products on these platforms.

Encryption is a highly effective method for securing data transmission and storage. By transforming plaintext data into scrambled ciphertext, the process renders the data indecipherable to anyone without the corresponding decryption key. Therefore, even if hackers somehow manage to intercept data exchanges or gain access to databases, they will be unable to make sense of the data. Sensitive information such as names, birthdays, phone numbers, and credit card information will appear as meaningless jumble. Research from Ponemon Institute shows that encryption technologies can save businesses an average of $1.4 million per cyber-attack.

Block chain technology contributes an extra level of security to e-commerce platforms. Transaction data is organized into blocks, which are in turn linked together in a chain. Once a block joins the chain, it becomes difficult to tamper with the data within. Furthermore, copies of this “blockchain” are distributed across multiple systems worldwide so that the latter can detect any attempts to illegitimately access the data. An IDC survey suggests that American bankers are the biggest users of block chain, further underscoring confidence in this technology.

The argument here is that SMBs can enjoy the benefits of AI while maintaining data privacy and security. The right e-commerce platforms offer tried-and-true measures to safeguard data and prevent breaches.

Having your cake and eating it too

The potential of AI in SMBs remains largely untapped. As such, those daring enough to exploit machine learning to empower their business logics may reap a significant dividend over competitors who insist on doing things the old-fashioned way. By automating essential functions like pricing analysis and inventory management, businesses can achieve unprecedented levels of efficiency and accuracy. The e-commerce platforms providing these services are equipped with robust cybersecurity features, providing valuable peace of mind for SMBs.

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The post Revolutionizing SMBs: AI Integration and Data Security in E-Commerce first appeared on AI-Tech Park.

Introduction
1. Quantum Computing
2. Revolutionizing with AI
3. Blockchain Technology
4. Quantum Computing’s Opportunities and Challenges for Blockchain Technology
4.1. Security
4.2. Development of Quantum-Resistant Cryptography
5. Implications of Quantum Computing in the Bitcoin and Crypto World
5.1. Efficiency and Speed
5.2. Crypto Upgrades and Hard Forks
6. Can Quantum Computing, Blockchain, and AI Create a Powerful Synergy?
Wrap Up

Introduction

In the ever-evolving landscape of theology, three revolutionary forces have gained momentum and have a promising future in reshaping industries. These three are quantum computing (QC), artificial intelligence (AI), and blockchain technology, which have already left a mark in various domains. Thus, by combining these three technologies organizations can benefit researchers by improving scalability, efficiency, and security when implemented in the real world. 

So, in this article, we will explore the future of quantum computing, AI, and blockchain technology by exploring the potential and powerful synergies, challenges, and opportunities.

1. Quantum Computing 

As discussed in our previous articles, quantum computing has the potential to address the traditional computing methods that the modern technological industry needs, for example, in manufacturing, finance, astronomy, and many more. QCs are capable of performing complex calculations at a much faster magnitude than traditional computers. For example, quantum computing can be used to optimize the supply chain, enhance financial risk management, improve drug discovery, and optimize e-commerce logistics.

2. Revolutionizing with AI

Artificial intelligence has made a remarkable contribution to our industry by enabling machines to perform tasks that were previously conducted by humans. AI has a bright future for making daily work autonomous, self-improvement, unstructured data, and understanding complex equations. With quantum computing and quantum machine learning algorithms, we can process and analyze massive datasets with efficiency, empowering AI systems to predict accurately and make correct decisions.

3. Blockchain Technology

On the other hand, blockchain technology is a distributed ledger that enables transparent and secured transactions without the need for banks or financial institutions by introducing decentralized cryptocurrencies like Bitcoin. Blockchain technology comes with the concept of “proof-of-work” used in many blockchains, which requires computation tasks. By adding new blocks, tampering with the blockchain becomes even more difficult. Blockchain technology can be used in other areas as well, like smart contracts, supply chain monitoring, the delivery of secure medical records, and voting systems.

4. Quantum Computing’s Opportunities and Challenges for Blockchain Technology

The combination of quantum computing and blockchain technology could create new opportunities and challenges in the 21st century. Here are some of the factors that can impact the growth of blockchain technology:

4.1. Security

Quantum computers have the potential to break several encryption algorithms, including ones that are used in many blockchains to keep transactions secure. However, quantum computers can become powerful as they can decrypt sensitive data and even private keys in blockchain, which is a threat to security.

4.2. Development of Quantum-Resistant Cryptography

The threat to security has led to work on post-quantum cryptography, or quantum-resistant cryptographic algorithms, which are cryptographic systems that are secured even if they face quantum computer attacks. However, once quantum-resistant cryptography is developed and incorporated properly into the blockchain, it makes the blockchain immune to the security threats that quantum computers pose.

5. Implications of Quantum Computing in the Bitcoin and Crypto World

5.1. Efficiency and Speed 

Quantum computers use quantum bits, which allows these computers to solve complex problems faster than traditional computers, which implies that quantum computers can easily mine cryptocurrency at a faster rate. This level of speed and efficiency revolutionizes mining processes, making them faster and less demanding.

5.2. Crypto Upgrades and Hard Forks

To counter QC threats, cryptocurrencies introduced new stands in quantum computers that cannot easily crack, resulting in hard forks where cryptocurrencies can split to update about such incidents and software rules.

6. Can Quantum Computing, Blockchain, and AI Create a Powerful Synergy?

The trio of quantum computing, AI, and blockchain technology each have their unique strengths and applications that have led researchers to explore new possibilities in this field. As discussed above, QC has the power to improve the efficiency of AI and blockchain, while blockchain can provide a secured framework during AI transactions and data operations.

So, to harness the full power of these technologies, research institutions, startups, and established tech giants should collaborate to explore the application areas and address the challenges that might arise while integrating them. The regulatory bodies and governments of different countries also play an important role in shaping the legal and ethical framework for embracing these technologies to make them powerful.

Wrap Up

Overall, blockchain technology offers a secure and immune way to manage and store data related to the Quantum machine learning system. By harnessing the power of blockchain technology, financial organizations can ensure that the data is safe and up-to-date. As quantum computing is continuously advancing, blockchain technology has become an important tool for securing QML systems.

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The post The Future Potential for Blockchain, AI, and Quantum Computing first appeared on AI-Tech Park.

The report also covers the following areas:

• Blockchain Technology Market size
• Blockchain Technology Market trends
• Blockchain Technology Market industry analysis

Blockchain Technology Market 2023-2027: Segmentation

The blockchain technology market is segmented as follows:

• End-user 
  • BFSI
  • Government
  • Healthcare
  • Others
• Type 
  • Private
  • Public
  • Hybrid
• Geography 
  • North America
  • Europe
  • APAC
  • South America
  • Middle East And Africa

The market share growth by the BFSI segment will be significant during the forecast period. Some of the main applications of blockchain in BFSI segments include reducing fraud, executing smart contracts, processing payments, and performing know-your-customer (KYC) due diligence. There is an increase in the adoption of blockchain technology across enterprises for post-trade settlement, payments, reference data, and trade finance. Hence, such applications are expected to drive the growth of this segment which in turn drives the global blockchain technology market during the forecast period.

Detail insights on the impact of each segment and make informed business decisions, request a sample report now!

Blockchain Technology Market 2023-2027: Vendor Offerings

• Accenture Plc: The company offers blockchain technology such as The red string.
•  Amazon.com Inc: The company offers blockchain technology such as Amazon quantum ledger database.
• Capgemini Service SAS: The company offers blockchain technology such as service integration and agile prototyping.

Blockchain Technology Market 2023-2026: Market Dynamics

Key Driver

The rising venture capital investments in blockchain technology are driving the blockchain technology market growth. One of the key elements for the development and expansion of blockchain technology is venture capital funding. Most SMEs use these investments to expand their businesses. Besides the funding, one of the main advantages for startups working with venture capitalists is that they can access key networks and crucial resources. Hence, such factors are expected to drive global blockchain technology growth during the forecast period.

Major Trend

The emergence of artificial intelligence is a major trend shaping the global blockchain technology market. Due to the emergence of artificial intelligence and its implementation in blockchain technology, there has been a significant shift in how users interact with these networks. There is increasing implementation of artificial intelligence with smart contracts across organizations as it helps to resolve highly complex business operations and decision-making. Hence, such applications are expected to drive global blockchain technology growth during the forecast period.

Significant Challenge

The growing concern for security, privacy, and blockchain transactions may hinder the blockchain technology market growth. As the transactions on the blockchain are verified and validated by a network of nodes, it is impossible for any one group to take control of the blockchain ecosystem. Thus, blockchain technology offers decentralized control and a transparent platform, which can be prone to severe cyber security attacks. Hence, such concerns are expected to hinder global blockchain technology growth during the forecast period.

What’s New? –

• Special coverage on the Russia-Ukraine war; global inflation; recovery analysis from COVID-19; supply chain disruptions, global trade tensions; and risk of recession
• Global competitiveness and key competitor positions
• Market presence across multiple geographical footprints – Strong/Active/Niche/Trivial – Buy the report!

Blockchain Technology Market 2023-2027: Key Highlights

• CAGR of the market during the forecast period 2023-2027
• Detailed information on factors that will assist blockchain technology market growth during the next five years
• Estimation of the blockchain technology market size and its contribution to the parent market
• Predictions on upcoming trends and changes in consumer behavior
• The growth of the blockchain technology market
• Analysis of the market’s competitive landscape and detailed information on vendors
• Comprehensive details of factors that will challenge the growth of blockchain technology market vendors

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Related Reports:
Blockchain technology in the healthcare market is estimated to grow at a CAGR of 32.79% between 2022 and 2027. The market size is forecasted to increase by USD 1,939.31 million. This blockchain technology in healthcare market report extensively covers market segmentation by type (private, public, and hybrid), end-user (pharmaceutical and medical device companies, healthcare payers, and healthcare providers), and geography (North America, Europe, APAC, South America, and Middle East and Africa). The growing inclination toward data security is notably driving market growth.

The blockchain technology in energy market size is expected to increase by USD 919.5 million from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 66.37%. Furthermore, this report extensively covers blockchain technology in energy market segmentation by end-user (power and oil and gas) and geography (Europe, North America, APAC, Middle East and Africa, and South America). The use of blockchain technology to prevent failure in power grids is one of the key drivers supporting blockchain technology in energy market growth

Table of Contents

1 Executive Summary

• 1.1 Market overview 
  • Exhibit 01: Executive Summary – Chart on Market Overview
  • Exhibit 02: Executive Summary – Data Table on Market Overview
  • Exhibit 03: Executive Summary – Chart on Global Market Characteristics
  • Exhibit 04: Executive Summary – Chart on Market by Geography
  • Exhibit 05: Executive Summary – Chart on Market Segmentation by End-user
  • Exhibit 06: Executive Summary – Chart on Market Segmentation by Type
  • Exhibit 07: Executive Summary – Chart on Incremental Growth
  • Exhibit 08: Executive Summary – Data Table on Incremental Growth
  • Exhibit 09: Executive Summary – Chart on Vendor Market Positioning

2 Market Landscape

• 2.1 Market ecosystem 
  • Exhibit 10: Parent market
  • Exhibit 11: Market Characteristics

3 Market Sizing

• 3.1 Market definition 
  • Exhibit 12: Offerings of vendors included in the market definition
• 3.2 Market segment analysis 
  • Exhibit 13: Market segments
• 3.3 Market size 2022 
• 3.4 Market outlook: Forecast for 2022-2027
  • Exhibit 14: Chart on Global – Market size and forecast 2022-2027 (USD million)
  • Exhibit 15: Data Table on Global – Market size and forecast 2022-2027 (USD million)
  • Exhibit 16: Chart on Global Market: Year-over-year growth 2022-2027 (%)
  • Exhibit 17: Data Table on Global Market: Year-over-year growth 2022-2027 (%)

4 Historic Market Size

• 4.1 Global blockchain technology market 2017 – 2021
  • Exhibit 18: Historic Market Size – Data Table on global blockchain technology market 2017 – 2021 (USD million)
• 4.2 End-user Segment Analysis 2017 – 2021
  • Exhibit 19: Historic Market Size – End-user Segment 2017 – 2021 (USD million)
• 4.3 Type Segment Analysis 2017 – 2021 
  • Exhibit 20: Historic Market Size – Type Segment 2017 – 2021 (USD million)
• 4.4 Geography Segment Analysis 2017 – 2021
  • Exhibit 21: Historic Market Size – Geography Segment 2017 – 2021 (USD million)
• 4.5 Country Segment Analysis 2017 – 2021
  • Exhibit 22: Historic Market Size – Country Segment 2017 – 2021 (USD million)

5 Five Forces Analysis

• 5.1 Five forces summary 
  • Exhibit 23: Five forces analysis – Comparison between 2022 and 2027
• 5.2 Bargaining power of buyers 
  • Exhibit 24: Chart on Bargaining power of buyers – Impact of key factors 2022 and 2027
• 5.3 Bargaining power of suppliers 
  • Exhibit 25: Bargaining power of suppliers – Impact of key factors in 2022 and 2027
• 5.4 Threat of new entrants 
  • Exhibit 26: Threat of new entrants – Impact of key factors in 2022 and 2027
• 5.5 Threat of substitutes 
  • Exhibit 27: Threat of substitutes – Impact of key factors in 2022 and 2027
• 5.6 Threat of rivalry 
  • Exhibit 28: Threat of rivalry – Impact of key factors in 2022 and 2027
• 5.7 Market condition 
  • Exhibit 29: Chart on Market condition – Five forces 2022 and 2027

6 Market Segmentation by End-user

• 6.1 Market segments 
  • Exhibit 30: Chart on End-user – Market share 2022-2027 (%)
  • Exhibit 31: Data Table on End-user – Market share 2022-2027 (%)
• 6.2 Comparison by End-user 
  • Exhibit 32: Chart on Comparison by End-user
  • Exhibit 33: Data Table on Comparison by End-user
• 6.3 BFSI – Market size and forecast 2022-2027
  • Exhibit 34: Chart on BFSI – Market size and forecast 2022-2027 (USD million)
  • Exhibit 35: Data Table on BFSI – Market size and forecast 2022-2027 (USD million)
  • Exhibit 36: Chart on BFSI – Year-over-year growth 2022-2027 (%)
  • Exhibit 37: Data Table on BFSI – Year-over-year growth 2022-2027 (%)
• 6.4 Government – Market size and forecast 2022-2027
  • Exhibit 38: Chart on Government – Market size and forecast 2022-2027 (USD million)
  • Exhibit 39: Data Table on Government – Market size and forecast 2022-2027 (USD million)
  • Exhibit 40: Chart on Government – Year-over-year growth 2022-2027 (%)
  • Exhibit 41: Data Table on Government – Year-over-year growth 2022-2027 (%)
• 6.5 Healthcare – Market size and forecast 2022-2027
  • Exhibit 42: Chart on Healthcare – Market size and forecast 2022-2027 (USD million)
  • Exhibit 43: Data Table on Healthcare – Market size and forecast 2022-2027 (USD million)
  • Exhibit 44: Chart on Healthcare – Year-over-year growth 2022-2027 (%)
  • Exhibit 45: Data Table on Healthcare – Year-over-year growth 2022-2027 (%)
• 6.6 Others – Market size and forecast 2022-2027
  • Exhibit 46: Chart on Others – Market size and forecast 2022-2027 (USD million)
  • Exhibit 47: Data Table on Others – Market size and forecast 2022-2027 (USD million)
  • Exhibit 48: Chart on Others – Year-over-year growth 2022-2027 (%)
  • Exhibit 49: Data Table on Others – Year-over-year growth 2022-2027 (%)
• 6.7 Market opportunity by End-user 
  • Exhibit 50: Market opportunity by End-user (USD million)
  • Exhibit 51: Data Table on Market opportunity by End-user (USD million)

7 Market Segmentation by Type

• 7.1 Market segments 
  • Exhibit 52: Chart on Type – Market share 2022-2027 (%)
  • Exhibit 53: Data Table on Type – Market share 2022-2027 (%)
• 7.2 Comparison by Type 
  • Exhibit 54: Chart on Comparison by Type
  • Exhibit 55: Data Table on Comparison by Type
• 7.3 Private – Market size and forecast 2022-2027
  • Exhibit 56: Chart on Private – Market size and forecast 2022-2027 (USD million)
  • Exhibit 57: Data Table on Private – Market size and forecast 2022-2027 (USD million)
  • Exhibit 58: Chart on Private – Year-over-year growth 2022-2027 (%)
  • Exhibit 59: Data Table on Private – Year-over-year growth 2022-2027 (%)
• 7.4 Public – Market size and forecast 2022-2027
  • Exhibit 60: Chart on Public – Market size and forecast 2022-2027 (USD million)
  • Exhibit 61: Data Table on Public – Market size and forecast 2022-2027 (USD million)
  • Exhibit 62: Chart on Public – Year-over-year growth 2022-2027 (%)
  • Exhibit 63: Data Table on Public – Year-over-year growth 2022-2027 (%)
• 7.5 Hybrid – Market size and forecast 2022-2027
  • Exhibit 64: Chart on Hybrid – Market size and forecast 2022-2027 (USD million)
  • Exhibit 65: Data Table on Hybrid – Market size and forecast 2022-2027 (USD million)
  • Exhibit 66: Chart on Hybrid – Year-over-year growth 2022-2027 (%)
  • Exhibit 67: Data Table on Hybrid – Year-over-year growth 2022-2027 (%)
• 7.6 Market opportunity by Type 
  • Exhibit 68: Market opportunity by Type (USD million)
  • Exhibit 69: Data Table on Market opportunity by Type (USD million)

8 Customer Landscape

• 8.1 Customer landscape overview 
  • Exhibit 70: Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria

9 Geographic Landscape

• 9.1 Geographic segmentation 
  • Exhibit 71: Chart on Market share by geography 2022-2027 (%)
  • Exhibit 72: Data Table on Market share by geography 2022-2027 (%)
• 9.2 Geographic comparison 
  • Exhibit 73: Chart on Geographic comparison
  • Exhibit 74: Data Table on Geographic comparison
• 9.3 North America – Market size and forecast 2022-2027
  • Exhibit 75: Chart on North America – Market size and forecast 2022-2027 (USD million)
  • Exhibit 76: Data Table on North America – Market size and forecast 2022-2027 (USD million)
  • Exhibit 77: Chart on North America – Year-over-year growth 2022-2027 (%)
  • Exhibit 78: Data Table on North America – Year-over-year growth 2022-2027 (%)
• 9.4 Europe – Market size and forecast 2022-2027
  • Exhibit 79: Chart on Europe – Market size and forecast 2022-2027 (USD million)
  • Exhibit 80: Data Table on Europe – Market size and forecast 2022-2027 (USD million)
  • Exhibit 81: Chart on Europe – Year-over-year growth 2022-2027 (%)
  • Exhibit 82: Data Table on Europe – Year-over-year growth 2022-2027 (%)
• 9.5 APAC – Market size and forecast 2022-2027
  • Exhibit 83: Chart on APAC – Market size and forecast 2022-2027 (USD million)
  • Exhibit 84: Data Table on APAC – Market size and forecast 2022-2027 (USD million)
  • Exhibit 85: Chart on APAC – Year-over-year growth 2022-2027 (%)
  • Exhibit 86: Data Table on APAC – Year-over-year growth 2022-2027 (%)
• 9.6 South America – Market size and forecast 2022-2027
  • Exhibit 87: Chart on South America – Market size and forecast 2022-2027 (USD million)
  • Exhibit 88: Data Table on South America – Market size and forecast 2022-2027 (USD million)
  • Exhibit 89: Chart on South America – Year-over-year growth 2022-2027 (%)
  • Exhibit 90: Data Table on South America – Year-over-year growth 2022-2027 (%)
• 9.7 Middle East and Africa – Market size and forecast 2022-2027 
  • Exhibit 91: Chart on Middle East and Africa – Market size and forecast 2022-2027 (USD million)
  • Exhibit 92: Data Table on Middle East and Africa – Market size and forecast 2022-2027 (USD million)
  • Exhibit 93: Chart on Middle East and Africa – Year-over-year growth 2022-2027 (%)
  • Exhibit 94: Data Table on Middle East and Africa – Year-over-year growth 2022-2027 (%)
• 9.8 US – Market size and forecast 2022-2027
  • Exhibit 95: Chart on US – Market size and forecast 2022-2027 (USD million)
  • Exhibit 96: Data Table on US – Market size and forecast 2022-2027 (USD million)
  • Exhibit 97: Chart on US – Year-over-year growth 2022-2027 (%)
  • Exhibit 98: Data Table on US – Year-over-year growth 2022-2027 (%)
• 9.9 China – Market size and forecast 2022-2027
  • Exhibit 99: Chart on China – Market size and forecast 2022-2027 (USD million)
  • Exhibit 100: Data Table on China – Market size and forecast 2022-2027 (USD million)
  • Exhibit 101: Chart on China – Year-over-year growth 2022-2027 (%)
  • Exhibit 102: Data Table on China – Year-over-year growth 2022-2027 (%)
• 9.10 UK – Market size and forecast 2022-2027
  • Exhibit 103: Chart on UK – Market size and forecast 2022-2027 (USD million)
  • Exhibit 104: Data Table on UK – Market size and forecast 2022-2027 (USD million)
  • Exhibit 105: Chart on UK – Year-over-year growth 2022-2027 (%)
  • Exhibit 106: Data Table on UK – Year-over-year growth 2022-2027 (%)
• 9.11 Canada – Market size and forecast 2022-2027
  • Exhibit 107: Chart on Canada – Market size and forecast 2022-2027 (USD million)
  • Exhibit 108: Data Table on Canada – Market size and forecast 2022-2027 (USD million)
  • Exhibit 109: Chart on Canada – Year-over-year growth 2022-2027 (%)
  • Exhibit 110: Data Table on Canada – Year-over-year growth 2022-2027 (%)
• 9.12 Germany – Market size and forecast 2022-2027
  • Exhibit 111: Chart on Germany – Market size and forecast 2022-2027 (USD million)
  • Exhibit 112: Data Table on Germany – Market size and forecast 2022-2027 (USD million)
  • Exhibit 113: Chart on Germany – Year-over-year growth 2022-2027 (%)
  • Exhibit 114: Data Table on Germany – Year-over-year growth 2022-2027 (%)
• 9.13 Market opportunity by geography 
  • Exhibit 115: Market opportunity by geography (USD million)
  • Exhibit 116: Data Tables on Market opportunity by geography (USD million)

10 Drivers, Challenges, and Trends

• 10.1 Market drivers 
• 10.2 Market challenges 
• 10.3 Impact of drivers and challenges 
  • Exhibit 117: Impact of drivers and challenges in 2022 and 2027
• 10.4 Market trends 

11 Vendor Landscape

• 11.1 Overview 
• 11.2 Vendor landscape 
  • Exhibit 118: Overview on Criticality of inputs and Factors of differentiation
• 11.3 Landscape disruption 
  • Exhibit 119: Overview on factors of disruption
• 11.4 Industry risks 
  • Exhibit 120: Impact of key risks on business

12 Vendor Analysis

• 12.1 Vendors covered 
  • Exhibit 121: Vendors covered
• 12.2 Market positioning of vendors 
  • Exhibit 122: Matrix on vendor position and classification
• 12.3 Accenture Plc 
  • Exhibit 123: Accenture Plc – Overview
  • Exhibit 124: Accenture Plc – Business segments
  • Exhibit 125: Accenture Plc – Key offerings
  • Exhibit 126: Accenture Plc – Segment focus
• 12.4 Amazon.com Inc. 
  • Exhibit 127: Amazon.com Inc. – Overview
  • Exhibit 128: Amazon.com Inc. – Business segments
  • Exhibit 129: Amazon.com Inc. – Key news
  • Exhibit 130: Amazon.com Inc. – Key offerings
  • Exhibit 131: Amazon.com Inc. – Segment focus
• 12.5 Capgemini Service SAS 
  • Exhibit 132: Capgemini Service SAS – Overview
  • Exhibit 133: Capgemini Service SAS – Business segments
  • Exhibit 134: Capgemini Service SAS – Key news
  • Exhibit 135: Capgemini Service SAS – Key offerings
  • Exhibit 136: Capgemini Service SAS – Segment focus
• 12.6 ConsenSys Software Inc. 
  • Exhibit 137: ConsenSys Software Inc. – Overview
  • Exhibit 138: ConsenSys Software Inc. – Product / Service
  • Exhibit 139: ConsenSys Software Inc. – Key offerings
• 12.7 Deloitte Touche Tohmatsu Ltd. 
  • Exhibit 140: Deloitte Touche Tohmatsu Ltd. – Overview
  • Exhibit 141: Deloitte Touche Tohmatsu Ltd. – Business segments
  • Exhibit 142: Deloitte Touche Tohmatsu Ltd. – Key offerings
  • Exhibit 143: Deloitte Touche Tohmatsu Ltd. – Segment focus
• 12.8 HCL Technologies Ltd. 
  • Exhibit 144: HCL Technologies Ltd. – Overview
  • Exhibit 145: HCL Technologies Ltd. – Business segments
  • Exhibit 146: HCL Technologies Ltd. – Key news
  • Exhibit 147: HCL Technologies Ltd. – Key offerings
  • Exhibit 148: HCL Technologies Ltd. – Segment focus
• 12.9 Huawei Technologies Co. Ltd. 
  • Exhibit 149: Huawei Technologies Co. Ltd. – Overview
  • Exhibit 150: Huawei Technologies Co. Ltd. – Business segments
  • Exhibit 151: Huawei Technologies Co. Ltd. – Key news
  • Exhibit 152: Huawei Technologies Co. Ltd. – Key offerings
  • Exhibit 153: Huawei Technologies Co. Ltd. – Segment focus
• 12.10 Infosys Ltd. 
  • Exhibit 154: Infosys Ltd. – Overview
  • Exhibit 155: Infosys Ltd. – Business segments
  • Exhibit 156: Infosys Ltd. – Key news
  • Exhibit 157: Infosys Ltd. – Key offerings
  • Exhibit 158: Infosys Ltd. – Segment focus
• 12.11 Intel Corp. 
  • Exhibit 159: Intel Corp. – Overview
  • Exhibit 160: Intel Corp. – Business segments
  • Exhibit 161: Intel Corp. – Key news
  • Exhibit 162: Intel Corp. – Key offerings
  • Exhibit 163: Intel Corp. – Segment focus
• 12.12 International Business Machines Corp.
  • Exhibit 164: International Business Machines Corp. – Overview
  • Exhibit 165: International Business Machines Corp. – Business segments
  • Exhibit 166: International Business Machines Corp. – Key news
  • Exhibit 167: International Business Machines Corp. – Key offerings
  • Exhibit 168: International Business Machines Corp. – Segment focus
• 12.13 Oracle Corp. 
  • Exhibit 169: Oracle Corp. – Overview
  • Exhibit 170: Oracle Corp. – Business segments
  • Exhibit 171: Oracle Corp. – Key news
  • Exhibit 172: Oracle Corp. – Key offerings
  • Exhibit 173: Oracle Corp. – Segment focus
• 12.14 PixelPlex Ltd 
  • Exhibit 174: PixelPlex Ltd – Overview
  • Exhibit 175: PixelPlex Ltd – Product / Service
  • Exhibit 176: PixelPlex Ltd – Key offerings
• 12.15 SAP SE 
  • Exhibit 177: SAP SE – Overview
  • Exhibit 178: SAP SE – Business segments
  • Exhibit 179: SAP SE – Key news
  • Exhibit 180: SAP SE – Key offerings
  • Exhibit 181: SAP SE – Segment focus
• 12.16 Tata Sons Pvt. Ltd. 
  • Exhibit 182: Tata Sons Pvt. Ltd. – Overview
  • Exhibit 183: Tata Sons Pvt. Ltd. – Business segments
  • Exhibit 184: Tata Sons Pvt. Ltd. – Key offerings
  • Exhibit 185: Tata Sons Pvt. Ltd. – Segment focus
• 12.17 Wipro Ltd. 
  • Exhibit 186: Wipro Ltd. – Overview
  • Exhibit 187: Wipro Ltd. – Business segments
  • Exhibit 188: Wipro Ltd. – Key news
  • Exhibit 189: Wipro Ltd. – Key offerings
  • Exhibit 190: Wipro Ltd. – Segment focus

13 Appendix

• 13.1 Scope of the report 
• 13.2 Inclusions and exclusions checklist
  • Exhibit 191: Inclusions checklist
  • Exhibit 192: Exclusions checklist
• 13.3 Currency conversion rates for USUSD
  • Exhibit 193: Currency conversion rates for USUSD
• 13.4 Research methodology 
  • Exhibit 194: Research methodology
  • Exhibit 195: Validation techniques employed for market sizing
  • Exhibit 196: Information sources
• 13.5 List of abbreviations 
  • Exhibit 197: List of abbreviations

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The post Blockchain Technology Market to Grow by $11.04 Billion (2022-2027) first appeared on AI-Tech Park.

This investment comes at a time of significant development for the digital assets and blockchain industry in Hong Kong. In June 2023, the Hong Kong Securities and Futures Commission (SFC) introduced a new regulatory framework for virtual asset trading platforms which is expected to further boost the adoption of cryptocurrencies in the city. The government of Hong Kong has also established the Task Force on Promoting Web3 Development, aiming to foster the adoption of blockchain technology in finance, trade, business operations and other consumer applications.

Zetrix is well-positioned to capitalise on this growth, given its unique focus on enabling global trade through its connection to Xinghuo BIF. Developed by the Chinese Academy of Information & Communication Technology (“CAICT”), a state owned research institute under the Ministry of Industry and Information Technology, Xinghuo BIF is China’s national blockchain infrastructure and facility that provides a secure and reliable platform for businesses and governments to develop and deploy blockchain applications.

By connecting to Xinghuo BIF, Zetrix provides users with access to China’s immense digital economy. This makes Zetrix an ideal platform for businesses that are looking to expand their operations into China or to trade with Chinese partners.

“We are excited to partner with Zetrix to help them achieve their mission of enabling global trade, leveraging access to China’s national blockchain, Xinghuo BIF,” said Joseph Chee, Chairman of Summer Capital. “With Zetrix building the foundational tools for the adoption of blockchain technology by industries, we believe that they are well-positioned to catalyse the next wave of web3 innovation.”

Summer Capital, together with its affiliated entities, count several market leading startups within their portfolio especially in Hong Kong, including Asia’s leading regulated virtual asset service provider Hashkey Group, Web3 leader in establishing digital property rights and open metaverse Animoca Brands, and SEBA Bank, which recently received approval-in-principal licenses from the Securities and Futures Commission to offer virtual asset services in Hong Kong.

“We are honoured to have Summer Capital as our strategic partner” said TS Wong, Co-Founder of Zetrix. “Summer Capital’s portfolio and proven track record of investments in leading web3 companies will bring tremendous value. Leveraging on their presence and network in Hong Kong will help us achieve the stated objectives of Zetrix.”

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The post Summer Capital Announces Zetrix Blockchain Network Node Hosting first appeared on AI-Tech Park.