Future of business through the synthesis of blockchain technology, data and AI

Abhishek Singh5 hours agoFuture of business through the synthesis of blockchain technology, data and AIAI and blockchain are emerging technologies and have a very bright future. Both of them are at the cutting edge of innovation.285 Total views6 Total sharesListen to article 0:00Innovation CircleJoin us on social networksIn the current period, blockchain technology is predominantly used for financial transactions. However, there are emerging trends that are redefining the application of blockchains with purposes like fraud detection, AML and supply chain management. 

As emerging technologies take a big piece of global attention, all eyes are now on the convergence of blockchain technology, big data and AI. These technologies put together are creating something magical for businesses that helps them perform better. 

Furthermore, they are trying to make things cheaper for both the business and the end user. Let’s take a dive into the intersection of these emerging technologies and where they can take us in the future.  A brief introduction

Artificial intelligence (AI) is the set of technologies that helps in identifying data patterns, recommending actions and automating those actions that are to be taken on the recommendations. All steps are taken independently of or with minimal human interference.

Blockchain technology provides a distributed infrastructure that uses immutable ledgers to record data that cannot be easily erased. Big data refers to the storage, analysis and reporting of insights from vast quantities of data that come in high volumes and at a high velocity. Using AI for anti-money laundering (AML)

Detecting money laundering has always been a core regulatory concern with blockchain and crypto. Crypto exchanges spend a fortune detecting and reporting suspicious transactions in crypto. However, with human-based monitoring, things are always expensive.

Elliptic, a blockchain analytics firm has integrated AI into its tech stack to detect suspicious blockchain transactions, hackers and money laundering activities. Such activities make crypto platforms more trustworthy. Fraud detection with big data and AI

Similar to AML, fraudulent transactions also increase the cost of doing business as you have to pay higher premiums for insuring your business. Peer-to-peer platforms have a high degree of fraudulent transactions.

Binance uses real-time machine learning to detect and uncover suspicious transactions in its exchanges, P2P transactions and other marketplaces. This method called the streaming pipeline helps it uncover fraudsters with less human effort, decreasing costs. Using AI and blockchains to validate data in large databases

In the last two examples, we use crypto-native applications. However, there are many firms that use a combination of blockchain, data and AI to make their businesses more efficient and therefore incur less cost.

One such example is IBM and Walmart. These two companies run a project called the “Food Trust,” which tracks supply chain databases. 

Blockchain technology is used to track and validate points in the supply chain. AI-based data analytics is used to identify patterns in the data and patterns for further process improvement. Challenges persist

Blockchain being a new technology also faces several challenges. The following points broadly explore a few major challenges that are hindering the growth of this technology. Bitcoin dominance

The future of blockchain is intrinsically connected to Bitcoin which dominated a bit below 50% of crypto markets (at the time of writing). This poses a challenge to projects that do not involve Bitcoin because, during a bear market, most people move out of other cryptocurrencies and hoard their funds in Bitcoin, Ethereum and a few selected stablecoins.

This causes concerns that even if a project is viable, it would be difficult for it to survive a bear market as the project tokens could be dumped in favor of Bitcoin. Funding concerns

Several investment and wealth funds lost hundreds of billions of dollars in the crypto winter when projects either shut themselves down or halted operations. Very few of them recovered from that situation.

Bloomberg reports that in Q2 of 2023, crypto VC funding is witnessing an 80% fall since 2022. The core mentioned reason is the regulatory uncertainty. There have been some legal successes like in the case of Ripple and Grayscale, but regulatory concerns are still widespread.

This has caused a funding myth that crypto projects are doomed to fail. Also, a lot of blame can be put on projects that didn’t have much innovation at the core of their project and just sought funds for personal gains. Reluctance of institutional players

Institutional players have conducted numerous pilot projects, several of them satisfactorily, yet they are highly unwilling to express their intentions in public.

JPM Coin by JP Morgan has been immensely successful in cross-border payments, yet there is very little information about the project. Even the Food Trust project by IBM did not receive much attention from its founders.

The reason for such reluctance appears the same as in the previous case. There has been very low regulatory clarity with each government delaying the decision for someone else to try first. 

There have been some successes with the UAE and El Salvador, but there is a need for a major economy like in , China or India where there is a very large consumer base. Concerns around AI

Unethical aspects of AI have been a very large concern for regulators where powerful players could marginalize others. Some AI-generated artworks can be stunning and even better than most skilled artists. These artworks marginalize the human ability to innovate.

There had been a case in the US that was a copyright case, where the court ruled that artworks generated by AI without human involvement cannot be granted copyright protection under US law.

Such incidents are an example of unethical use of AI. Conclusion

AI and blockchain are emerging technologies and have a very bright future. Both of them are at the cutting edge of innovation. Together they can be used for anti-money laundering, fraud detection and handling large amounts of data. However, their successes critically depend on the challenges that they face, beyond which only the sky’s the limit to their potential.

Abhishek Singh is a serial entrepreneur currently working on Acknoleger and is a vocal advocate of crypto.

This article was published through Cointelegraph Innovation Circle, a vetted organization of senior executives and experts in the blockchain technology industry who are building the future through the power of connections, collaboration and thought leadership. Opinions expressed do not necessarily reflect those of Cointelegraph.

Learn more about Cointelegraph Innovation Circle and see if you qualify to join