In recent years, notable progress has been made by blockchain explorers, and their functionality has been further enhanced by the emergence of generative artificial intelligence (AI). Highlighted below are two prominent blockchain explorers that have adopted AI to convert complex transaction data into formats easily understood by users.
From Investigation to Insight: The Role of AI in Revolutionizing Blockchain Exploration
Generative AI has been transformative across various fields—ranging from visual creation and content enhancement to simplifying web development—and has now extended its influence to the blockchain industry. This technology has been integrated into the user interfaces of two blockchain explorer platforms. Among them is Arkham Intelligence, a blockchain analytics platform developed to make complex on-chain data more accessible across multiple networks, including Bitcoin, Ethereum, BNB Chain, Tron, Avalanche, Base, Arbitrum, Polygon, Optimism, and others.
AI-powered techniques are utilized by Arkham to conduct transaction analysis and entity recognition, processing both on-chain and off-chain data to associate wallet addresses with identifiable real-world entities. For instance, in a recent transaction carried out through Binance, Arkham’s AI determined that 0.3065368295589717 BNB was received by a particular address in exchange for WBNB Token, then forwarded the same amount to Pancakeswap Router v2, ultimately reaching the signer—an action accompanied by a withdrawal instruction.
A detailed breakdown of the involved addresses is also provided through AI analysis. For blockchain investigators in particular, the rapid identification of real-world entities, integration of both on-chain and external data, and the capability to trace funds across multiple networks significantly accelerate the investigative process. The reliance on manually reviewing block explorer data line-by-line is minimized, enabling quicker conclusions. Additionally, Blockchair—a multi-chain analytics and explorer platform—has been developed to support 48 different blockchain networks.
An AI assistant has also been incorporated into Blockchair. Users are welcomed with the message, “Hi! I’m Cuborg, your AI Assistant. How can I help you today? It looks like you’re viewing a transaction. Feel free to ask me anything about it!” When reviewing a specific Bitcoin transaction—such as one involving a long-inactive address created on May 22, 2017, that transferred 94.729 BTC for the first time in nearly eight years at block height 895,197—Cuborg is able to provide a comprehensive explanation.
As AI-driven explorers continue to evolve, the need for painstaking forensic analysis to interpret cryptographic ledgers is being eliminated; conversational queries can now yield actionable insights within moments. This transformation is reshaping expectations for transparency across all blockchain networks, compelling exchanges, protocols, and even governmental bodies to operate under the assumption that their transaction flows are immediately accessible. The increased accessibility to such data may foster more balanced markets and potentially hasten broader public participation in the years ahead.
However, the detailed transparency introduces a paradox: the same AI-powered dashboards that assist genuine observers can also be exploited by malicious actors. As attribution techniques become more advanced, users may increasingly turn to privacy-focused coins, mixing services, zero-knowledge technologies, or alternative protocols to conceal their transactions. The protection of privacy—and the technologies that support anonymity—is considered a basic human right. Nonetheless, the inherent openness of most major blockchains turns that right into a double-edged sword, where efforts to ensure accountability frequently compromise personal discretion.
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