Artificial intelligence is here to stay, and since its unveiling, it has been used by many experts in different professions to ease the everyday lives of people. However, the application of AI in blockchain technology is an exciting new concept that has the potential to change the world, as we know it.
According to statista, AI technology grew by over $184 billion in 2024 and $44 billion in 2023, and its expected to grow to a cap of about $230 billion in 2030. Combining the two technologies creates opportunities for next-generation applications that have the potential to transform society completely.
AI is the ability of machines to learn from data and make deft decisions using the data that they are fed. Documenting transactions using blockchain technology is a safe, decentralised method. Combining these technologies can lead to countless options that improve productivity, security, and transparency in various businesses. In this article, we will examine seven (7) ways AI has been applied in blockchain.
What is Artificial Intelligence (AI)
In simple terms, AI is computer technology that is built to learn, reason, and solve problems in a high human intelligence capacity. Artificial intelligence is a technology that performs automated tasks that allow users to generate, classify, and perform complex tasks that are much faster than the traditional means known to users.
Scenario 1
Consider, for instance, having a smart assistant who can comprehend your query and provide an answer, aid you in locating the information, and even suggest solutions to complex daily tasks.
As of right now, artificial intelligence (AI) powers the virtual help you use on your phone, the suggestions you get when watching streaming content, and the ability to identify fraud in financial institutions. Making machines smarter is the aim of artificial intelligence (AI), which aims to improve our daily lives. Here are 7 ways AI has been applied in blockchain in 2024
7 Applications of AI in Blockchain
1. User Identification and verification
AI has improved the security, transparency, and hacker resistance of the user ID verification process. Blockchain securely and openly stores user data, and when combined with AI, it has been able to analyze enormous amounts of data fast and precisely. Financing, education, healthcare, and government are just a few of the areas that stand to gain from improvements in identity verification.
AI can be used, for instance, to validate users in real-time using behavioural analysis and recognition of facial features in biometric data. The blockchain allows for the transparent and safe storage of certain kinds of data.
2. Asset Tokenization
These days, real estate, artwork, and other tangible assets can all be converted into digital tokens on blockchains through the process of asset tokenisation, which is made possible by blockchain technology. Thus, by evaluating a variety of data, including past prices, market patterns, and asset conditions, artificial intelligence (AI) now assist in appropriately valuing these assets.
Artificial intelligence in asset tokenization also improves the administration of tokenized assets by forecasting market demand and liquidity. AI now assists investors in determining when to acquire or sell tokenized assets to maximize their return on investment by analyzing the state of the market.
3. Smart Chain Optimization
Code-written contracts, or smart contracts, take care of themselves when the predetermined circumstances are met. Artificial intelligence (AI) assists in the auditing process for smart contracts by spotting weaknesses and ensuring that they operate as intended. AI also assists in locating possible errors or gaps in the contract and provides reassurance that the smart contract operates as intended by examining the written code.
Additionally, AI in smart contracts can save time and money by substituting automatic AI audits for manual code review, thus enhancing smart contract dependability, security, and transparency.
4. Energy Consumption management
There have been many concerns about blockchain systems’ high energy consumption, especially those running on Proof-of-work. Many have considered their impact on sustainability. However, there is hope.
With the application artificial intelligence (AI), many big mining rig companies can now measure the amount of energy consumed. Aside fom this, AI can be used against grid overloads by forecasting the typical peak usage times and dynamically altering the baseline that needs to be achieved and, therefore, the power used for mining.
In addition, due to its capabilities, AI can control how many computational resources are allocated to mining and redirect them to the most active and efficient parts of the operation.
5. Predictive Analysis for Cryptocurrency
AI tools have become beneficial to the cryptocurrency market and the industry. These tools have been instrumental in forecasting trends and market predictions. AI predictions for 2025 highlight how artificial intelligence is poised to further impact financial and technological advancements globally.
For instance, Natural Language Processing (NLP) models can monitor news, social media and other forums that allow investors to have a deep understanding of sentiments that affect crypto prices, while long-short-term me mory (LSTM) models can help analysts identify complex patterns they might have missed.
With these models, traders will make decisions based on comprehensive insight; liquidity management will aid exchanges, while cryptocurrency projects will acquire the ability to comprehend market operations.
5. Decentralized Autonomous Organisations (DAO)s
Artificial Intelligence (AI) has also changed the very essence of Decentralized Autonomous Organizations (DAOs) by incorporating advanced decision-making and governance models. For example, using machine learning systems, it is possible to sift through a very large contextual dataset and develop the most effective governance proposals based on the genesis of the token, its holders, the market, and other project-related metric statistics.
Additionally, collective intelligence in the form of non-sentimental intelligence within the DAOs’ purview can offer wisdom to make informed choices by means of artificial intelligence-supported prediction markets.
The progress of the DAOs brings additional effectiveness along with the assistance of AI in governance of the elaborate token economy, incentive systems, and multi-party coordination.
6. Supply chain Management
The combination of AI and blockchain is transformative in the transformation of supply chain and logistics systems. Machine learning algorithms can predict potential disruptions, suggest the best routing strategies, and control stock levels by processing the information from sensors and IoT devices placed throughout the supply chain.
AI has improved visibility in patterns and outliers of product movement, helping track down counterfeit goods and their illegal distribution. Supply chain predictive maintenance models may recognize points in time where equipment might fail, therefore cutting excess stream outages.
Likewise, artificial intelligence has helped forecast demand more accurately, reducing waste and ensuring transparency.
Final Thought
While companies are improving on the capabilities of AI, blockchain technology is also ensuring everyday improvement. This duo is yet to reach their highest peak in terms of innovations, but one thing is for sure: every innovation will be a step closer to making the lives of users easier and promoting innovation in these industries.
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Author: Olumide Ogunjobi
Organization: The Crypto Times
Author Bio: Olumide Ogunjobi is a seasoned crypto content writer proficient in DeFi & crypto research, crafting insightful narratives that elucidate complex concepts with clarity.
