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There is no shortage of opportunity when it comes to monetizing AI-related assets. You can offer AI-driven tools as subscription-based services tailored to specific industries, like a content generation platform for drafting legal documents, or combine AI with blockchain by tokenizing AI models or datasets. Users purchase access to particular AI functions via tokens, creating a decentralized marketplace for AI resources.
Transforming data into tradable wealth has become easier after Kite AI, a provider of decentralized AI infrastructure, and GAIB partnered to create a decentralized AI ecosystem. High-quality models, datasets, and compute resources are widely accessible in this ecosystem. It uses blockchain for secure and fair data indexing and creates a liquid, decentralized market for GPUs and other compute assets.
The ecosystem allows stakeholders to monetize AI-related assets via lending markets, GPU-backed stablecoins, and other DeFi tools. Kite AI and GAIB are rising to challenges plaguing GPU computing and data, mainly the challenge that large corporations typically control these resources. Smaller enterprises face limited access, which hinders industry innovation.
The partnership will also help create liquid, revenue-generating assets based on real AI-driven cash flows, ensuring accessible and monetizable resources. GAIB’s economic framework transforms typically illiquid AI resources into tradable assets, potentially providing unique financial opportunities for AI and data stakeholders all over the world.
What are illiquid assets?
An illiquid asset is a service or item that is not readily convertible to cash as opposed to an asset one can exchange for currency quickly and easily. The US Securities and Exchange Commission’s (SEC) definition of an illiquid asset is one you can’t reasonably expect to sell in a week without a substantial market value difference, assuming market conditions do not change.
Examples include cryptocurrencies or derivatives that lack buyers and sellers. Illiquid resources exhibit a relatively low trading volume. The partnership between Kite AI and GAIB addresses challenges such as slippage (filling an order at a very different price than the one specified), wide bid-ask spreads (difference between selling and purchasing price), and disjointed price movements.
Benefits and challenges of monetizing data
Data monetization can come with higher revenue or significant cost reduction and a strengthened market position or competitive advantage. Consumers gain access to high-quality, diverse datasets that offer valuable predictions, insights, solutions, or recommendations.
However, platforms aiming to monetize data encounter challenges like security risks, quality issues, and privacy concerns. Data may be vulnerable to theft, cyberattacks, loss, or corruption. It can be incomplete, inaccurate, inconsistent, outdated, or duplicated. It can contain personal or otherwise sensitive elements infringing upon data subjects’ rights. Finally, it can lack clear ownership, or the policies, standards, or regulations governing it may be obscure. The challenges named hinder the full realization of data monetization potential and create trust issues between data users and owners.
AI and blockchain enhance transparency and security
The blockchain offers data transparency and sovereignty by letting owners store, manage, and share their data on a secure, decentralized platform without intermediaries. Consumers can verify the provenance, authenticity, and quality of data on the blockchain without third parties intervening. Owners leverage smart contracts to define the terms and conditions of use and access, including duration, price, purpose, and quality.
AI tools detect and prevent data manipulation, fraud, and duplication using machine learning and NLP techniques, ensuring data integrity, accuracy, and appropriate labeling.
Tokenization involves converting asset rights into a blockchain-based token. It means forming a digital representation of the ownership rights to the AI model, allowing it to be traded transparently and securely.
AI model ownership is traditionally established through intellectual property agreements and contracts, which can be challenging and complicated to enforce. Tokenization involves generating an immutable record of ownership on a blockchain, which is clear and unalterable. It reduces the risk of disputes and enhances trust.
Ownership transfers require a lot of legal work. The merger of AI and blockchain makes it possible to transfer ownership seamlessly and safely through blockchain transactions, opening up possibilities for AI model markets, where stakeholders can buy, sell, or trade models like any other digital asset.
Monetizing AI models traditionally involves licensing contracts where model developers receive royalties based on use. Tokenizing them makes the process simpler. Royalty terms are directly embedded into the smart contracts associated with the tokens. The smart contract automatically executes royalty payments to the owner every time a tokenized AI model is used, reducing administrative overhead and ensuring accurate, timely compensation.
Technical structure and steps to tokenize AI models
The technical structure for tokenizing AI models is comprised of smart contracts, token standards, and decentralized storage solutions. The agreement terms are integrated within the smart contract code. Adopting standards like ERC-1155 and ERC-721 ensures interoperability and compatibility across blockchain platforms and applications.
The InterPlanetary File System and other decentralized storage systems store AI model data security, with blockchain references maintaining integrity and accessibility.
Data engineers and scientists develop and validate an AI model, and legal frameworks are set to define terms of use, ownership rights, and royalty agreements. Developers then create and deploy smart contracts on the blockchain to manage token issuance, royalty payments, and ownership records. Stakeholders receive digital tokens representing ownership of the AI model. The tokens are listed on blockchain marketplaces, where holders can trade and transfer them.
AI and blockchain-enabled tokenization democratizes access to flexible and versatile technologies by lowering entry barriers. Smaller companies and individuals can participate in the AI ecosystem by obtaining fractional ownership of high-value AI models, as the partnership between Kite AI and GAIB set out to achieve.
