Blockchain And Big Data: Exploring The Synergies

Artificial intelligence (AI) and blockchain are two disruptive technologies that are predicted to have a profound impact on society over the next decade. According to a Facts and Factors market research analysis, the global AI market size was predicted to expand from $29.86 billion in 2020 to $299.64 billion in 2026, and the worldwide blockchain market from $3 billion in 2020 to $39.7 billion in 2025. While these analyses are subject to change due to market conditions, it’s clear that there is a growing demand for AI, especially after the emergence of ChatGpt. Who knows what the future holds? This may very well be the most significant innovation of the decade. Let’s examine some of the potential applications that could arise from the integration of AI and Blockchain. These possibilities could lead to new advancements that were previously unimaginable.

Brief Definition of Terms

AI is the attempt to replicate human intelligence in machines, to mimic human problem-solving skills, and to make decisions based on historical data and information. It seeks to go beyond the traditional strengths of computers, such as speed and accuracy, to encompass a more human-like approach to decision-making. However, while AI is capable of learning from historical data and making decisions based on that data, it can also make mistakes or be subject to fraudulent inputs. This is where Blockchain comes in.

Blockchain is a distributed ledger that uses cryptography to ensure the security and transparency of transactions. It is often associated with cryptocurrencies such as Bitcoin, but its applications extend far beyond that. Blockchain can create a secure and transparent record of transactions, which cannot be altered or deleted. This means that once a transaction is recorded, it becomes a permanent part of the blockchain.

Everything being equal, in a perfect scenario, if AI and Blockchain are combined, the result is a system that can learn from historical data and make decisions based on that data, while at the same time ensuring the security and transparency of the data. Blockchain can create a tamper-proof record of the data used by AI systems, making it easier to audit and verify the data. This can lead to greater trust in the decisions made by AI systems, as the data used to make those decisions can be verified as accurate and trustworthy.

Some Case Studies

Microsoft Xbox and EY

By leveraging AI and blockchain technology, Xbox was able to automate many of the processes involved in managing rights and royalties. This reduced the need for manual intervention and increased efficiency. AI was also used to analyze transaction data and identify patterns and anomalies, helping to prevent fraudulent activities.

Smart contracts were used to accurately and transparently process the royalties for Microsoft Xbox’s partners. The next step was to securely and transparently share the information with them in near real-time, cutting access to royalties from 45 days to 4 minutes which lead to a more enriching experience for the partners. The use of AI and blockchain technology greatly improved Xbox’s royalty management system, creating an efficient and secure platform for managing rights and royalties. Read more here

According to Jeff Wong the Global Chief Innovation Officer at EY, this system has the potential to become the highest volume blockchain in the world, surpassing even Bitcoin and Ethereum on a daily basis.


BurstIQ created a comprehensive solution to manage patient data, known as the “Health Wallet.” It combines AI, blockchain, and big data to provide a holistic approach to managing patients’ health records and wellness programs. Through the Burst IQ wallet, healthcare providers can access a patient’s health information securely. Moreover, healthcare professionals can leverage this information for scientific research and gain a better understanding of various ailments. Patients have the option to share their aggregate health data while keeping their sensitive information secure through blockchain technology. Read more here

IBM and IPwe

By combining AI and blockchain technologies, IPwe with the help of IBM was able to create a Global Patent Registry (GPR) that is automated and transparent. The GPR is unique as it is the world’s first blockchain-based registry that consolidates current, active, and past patent records into a single, publicly accessible repository. This technology is useful in eliminating the challenges associated with comprehending the critical components of patent information. Moreover, it facilitates both record-keeping and smart contract creation for the underlying asset. Read more here

What are other Possibilities?

  • Financial services : IBM highlights that blockchain and AI technologies are boosting trust and speeding up multiparty transactions. In the context of the loan process, applicants can grant consent to access their personal records stored on a blockchain, enabling trust in the data and allowing AI-powered automated processes to evaluate the loan application quickly. This ultimately leads to faster loan approvals, resulting in improved customer satisfaction. Financial institutions looking to ensure the security and speed of their transactions can leverage Bitpowr’s blockchain infrastructure. Bitpowr’s platform creates a secure and tamper-proof ledger that tracks every transaction in real time, promoting transparency and reducing the risk of fraudulent activities. With faster transaction processing capabilities, Bitpowr’s solution can also help financial institutions reduce their operational costs while enhancing the customer experience.

  • Secured Multi-Party Computations can be used to securely distribute and compute AI models: Secured Multi-Party Computations (sMPC) is a cryptographic technique that enables multiple parties to jointly compute a function while keeping their inputs private. In the context of AI and blockchain, sMPC can be used to securely distribute and compute AI models across multiple parties without revealing the underlying data. This allows organizations to collaborate and share data for AI training and modeling purposes without compromising the privacy of the data. sMPC architectures can be used to enable secure and private computations of AI models, such as training and prediction, on data stored on a blockchain. This ensures that the data is not exposed to any third parties and that the computations are performed in a trustless and decentralized manner. sMPC can also be used to enable secure and private data sharing between multiple parties without exposing the data.

  • Improved data quality: AI algorithms rely heavily on high-quality data to generate accurate predictions and insights. Blockchain technology can help improve the quality of data by ensuring that it is accurate, up-to-date, and tamper-proof. This is especially important in industries like healthcare and finance, where the quality of data can have a significant impact on decision-making.

  • Data Privacy: Another area where AI and Blockchain can create synergy is in the field of data privacy. With the rise of big data, there are growing concerns about how data is collected, stored, and used. AI can help to analyze this data and identify patterns and trends, but there are concerns about the privacy of this data. By using Blockchain to create a secure and transparent record of data usage, it may be possible to address these concerns and create a more trustworthy system for the collection and analysis of data.

  • Creation and Running of DAOs: One of the main advantages of combining AI and Blockchain is the potential to create decentralized autonomous organizations (DAOs). These are organizations that are run entirely by software, without the need for human intervention. By using AI to make decisions and Blockchain to ensure the transparency and security of those decisions, DAOs can create a new paradigm for how organizations are run. This could lead to more efficient and effective decision-making, as well as greater transparency and accountability.

  • Predictive Analytics: AI can be used to extract insights from the vast amounts of data stored on the blockchain, enabling predictive analytics to be performed. For example, AI could analyze data about the transaction history of a cryptocurrency to predict future price movements or analyze data about a company’s supply chain to predict future demand for its products.

  • Smart Contracts: Smart contracts are self-executing contracts with the terms of the agreement between buyer and seller being directly written into code. AI can help to enhance smart contracts by enabling them to automatically adapt to changing conditions or execute certain conditions based on data stored on the blockchain. For example, an AI-powered smart contract could adjust the terms of an insurance policy based on data about the performance of the insured asset, such as a vehicle or machine.

  • Fraud Detection: Blockchain’s immutability and transparency make it an ideal platform for detecting and preventing fraud. AI can be used to analyze blockchain data in real-time to detect unusual patterns of behavior, such as a sudden influx of transactions or a large transfer of funds. This can help to identify potential fraud or cyber-attacks and enable proactive measures to be taken.

  • Supply Chain Management: AI can be used to enhance supply chain management on the blockchain by enabling real-time tracking of goods and services. AI-powered sensors can be used to collect data about the location, condition, and quality of goods as they move through the supply chain, with this data being stored on the blockchain. This can help to improve supply chain transparency and reduce the risk of fraud or counterfeiting.

  • Insight into Cryptocurrency Monetization: Cryptocurrency traders rely heavily on a variety of indicators. However, manually producing reliable signals may be impossible given the ubiquity of unstructured data in the digital world. Before being evaluated for investing insights, large amounts of data must be clean, relevant, and correct. Data scientists and engineers can use AI to create strategies for traders to obtain relevant and clean data on a platform. Natural language processing techniques can classify and extract data based on criteria like currency name, document kind, currency founder, and more. Data scientists can utilize AI to give accurate trading information in a dashboard or interface that non-technical traders or investors can understand. Investors and traders can then use the knowledge to increase their earnings.

  • Accurate Cryptocurrency Market Predictions: When the number of investment options expands, manual inquiry, extraction, and analysis approaches are no longer effective in discovering investments and buy/sell signals. AI has become a popular tool in the financial industry, and when combined with blockchain, it becomes even more effective. Larger financial firms, such as Goldman Sachs, Citigroup, and Barclays, have already begun incorporating AI into their workflows, while small and medium-sized businesses follow suit.

What are the possible constraints to this synergy?

As with every innovation, it is not without its challenges there are several potential constraints to the synergy between AI and blockchain, which could include:

  1. Scalability: Both AI and blockchain require significant computational resources, which can make it challenging to scale their use cases to a large number of users.
  2. Data privacy: While blockchain provides a secure and decentralized storage solution, it is difficult to ensure data privacy when multiple parties are involved in the storage and processing of data.
  3. Regulatory challenges: The use of AI and blockchain may face regulatory challenges as governments and other regulatory bodies seek to balance innovation with privacy and security concerns.
  4. Interoperability: Different blockchain networks and AI systems may have different protocols and standards, which can make it difficult to integrate them seamlessly.
  5. Adoption: Adoption of new technologies always takes time and requires significant investment, both in terms of financial resources and education and training for users.
  6. Security: The security of blockchain and AI systems can be compromised by hackers or other malicious actors, which could result in loss of data, identity theft, or other types of fraud.
  7. Complexity: The combination of AI and blockchain technologies can result in complex systems that require specialized skills and expertise to develop, maintain, and use effectively.

Wrapping up

In conclusion, the combination of AI and blockchain has the potential to revolutionize the way we store, process, and analyze data. From enhancing smart contracts to detecting fraud, managing supply chains, and improving decision-making in DAOs, the possibilities are endless. As these technologies continue to evolve, we can expect to see more innovative solutions that harness their combined power to drive new levels of efficiency, transparency, and security in various industries.

Bitpowr remains your safest institutional MPC-protected Wallet- Built from the ground up to enable financial institutions to leverage the Blockchain to ease financial transactions. With this, you can focus on what matters most: delivering more value and innovative products to your customers. Reach out to us if you need more information, we are happy to help.