Even as blockchain and cryptoasset firms find themselves facing a barrage of legal and regulatory actions, and a much-discussed crypto winter, they are also facing down the ever-present conversation around AI. Spurred on by the rapid adoption and implementation of ChatGPT (and ChatGPT-like solutions), venture capitalists and other investors have begun to shift interest and funds toward AI projects at an accelerating rate. According to CB Insights, AI start-ups attracted over $5 billion in venture capital in Q1 2023 alone, after raising over $40 billion in 2022. While tokenization, Web3, and other blockchain-related projects are certainly being developed and built out, AI and crypto are being framed by some as adversaries.

This misses the broader point.

The reality is the mega trends of blockchain-based transactions, tokenized financial assets, and the integration of AI into virtually every business are not going away. Rather, and evidenced by recent moves and actions to further promote bitcoin and/or crypto investing options as well as the fervor around AI projects (and constructive policy), these trends are only set to accelerate moving forward. Equally as real, however, are the concerns and problems that have arisen in the cryptoasset space. A lack of trust, past-collapses, legal action taken against alleged fraudsters, and a general lack of transparency continue to prove difficult obstacles for firms in the space to overcome.

AI is not a cure-all for the ills of the crypto space, but there are some ways that AI-based tools can – and will – improve the understandability, transparency, and comfort with which firms and investors can utilize crypto where effective.

Real Time Transparency

One major issue and problem that continues to exist and that has attracted the ire of regulators and investors is the ongoing lack of transparency, real-time reporting, and comparable reporting standards in the crypto sector. Various models have been put forward, with proof of reserves briefly rising to prominence before being dragged down due to issues with the lack of standardization in how these accounting engagements were performed.

AI in its various forms, be it a large language model, neural network, or other form of advanced AI, can be leveraged to assist with these processes. Audits and other attestation engagements primarily focus on collecting, confirming, and reporting out information about the firm in question to the external marketplace. Framed in that context, AI applications appear well situated to enhance current efforts underway in the space to reduce fraud. Mastercard
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, recently having launched Mastercard Crypto Credential, is a clear example of how the push by TradFi institutions into the crypto space is being accompanied by a renewed focus on transparency and fraud detection. AI applications, trained and built through analysis of incredibly large data sets, seem a good fit to help improve current fraud detection options and help create new ones.

Smart Contract Review

Moving up the value chain in the cryptoasset sector, smart contracts play a critical role in the successful operation of most blockchain-based and cryptoasset applications. Decentralized finance applications and non-fungible tokens, for example, must be able to interoperate with other cryptoassets and counterparties, as well as with established financial institutions. These essential communications and interactions tend to be powered by smart contracts, which are programable tools that allow blockchain-based tools to automate certain tasks, interoperate with other technology tools, and ultimately provide much of the value promised by blockchain applications.

For all the promise that smart contracts hold, however, there are issues that continue to arise with implementation. Lack of widespread standards, the inability of quick changes to be make to blockchain records, and the specificity that can be required can all limit the applicability of smart contracts for many businesses.

AI, be it in the form of large language model or some other form of AI, can help firms analyze, review, and revise smart contracts – in addition to demo testing them – on an on-demand basis to streamline how these applications are implemented at the firm in question.

Bot Payments

Blockchain and cryptoassets have long been in search for a “must have” application and use case, and the spectacular rise of AI in the general market consciousness has highlighted this fact. ChatGPT, for all its imperfections, has delivered an intuitive, easy to use, no-code-required application that conveys a readily understandable value proposition to individuals and institutions. The rise of AI and the rapid increase in interest and investment in the space can also indirectly lead more payment-based applications for cryptoassets.

For example, as chat bots and other bot-augmented processes and tasks become more commonplace at firms, this creates an increasing likelihood of bots interacting, transacting, and paying each other to render services or deliver products. This is an almost ideal opportunity for blockchain-based payments – via tokenized assets – to play a pivotal role going forward. AI bots and applications have the ability to analyze and transact information on a continuous basis, outside of working hours. When layered on top of smart contracts, allowing these bots and other applications to operate across a wide range of applications and tools, presents an almost ideal testing ground for bot-to-bot payments and confirmations.

AI is attracting a lot of attention and investment, and also has the ability to help crypto find its must-have use cases sooner rather than later.

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