Without a doubt, the two most destructive technologies of the last 10 years have been the development of the blockchain, otherwise known as distributed layer technology, and artificial intelligence. The convergence of these two technologies are set to unlock unprecedented opportunities in 2025 and beyond.
The aim of this article is to explore the evolving synergy between the blockchain and artificial intelligence, and also to provide some insight as to how the integration of these two technologies is not only transforming the way we live, work, and play, but is also creating new tradable opportunities for discerning investors.
AI: Artificial intelligence is defined as the ability of machines to simulate the thought processes and actions of human intelligence through the process of learning, reasoning, and problem solving. Artificial intelligence has been around for several decades, but mostly in developmental phase and limited use. However, it is now becoming more mainstream, and the evolution of various new technologies and various new ways of doing things in the world is now incorporating the use of artificial intelligence in those fields.
Blockchain: The blockchain is also known as the decentralized ledger technology and it offers a process whereby information can be stored on various systems in a manner that is transparent, immutable, and highly secure. The coming of the blockchain has disrupted several traditional systems such as those found in logistics and governance.
There are now emerging discussions as to how the blockchain and AI can be synergized to provide secure, efficient and scalable solutions that can be deployed for use by individuals, businesses and governments. Human activities which involve work, learning, recreation and socialization will all require some form of triangular interaction between individuals, the private sector (businesses and service providers) and the public sector (government).
By creating products and services that integrate both technologies, the power of AI to make intelligent, independent analysis and automation can be merged with decentralized systems that ensure data integrity and immutability of processes, which have created several current and emerging use cases.
As investors, several of these use cases already exist to enable you to profit from the evolution that is taking place in terms of AI-blockchain synergy.
The following are ecosystems that already feature systems that integrate the blockchain and AI.
There are decentralized marketplaces where AI services can be exchanged from one party to another without the intervention of an intermediary. These platforms offer developers the opportunity to sell their proprietary AI algorithms to end users, who can also seek for customization of such solutions to suit their use. The tokens of such decentralized platforms provide an investment opportunity if there is sufficient traction from the intended end-users. SingularityNET (AGIX) is an example of such a decentralized marketplace.
What benefits are derivable from introduction of AI into decentralized marketplaces? One such benefit is cost reduction. The use of intermediaries always introduces an extra cost. The elimination of intermediaries eliminates this cost. Buying and selling AI services on blockchain platforms on a peer-to-peer basis offers diversity, customization and fair compensation in an environment of security, transparency and immutability.
Decentralized finance simply means, financial transactions that exclude a centralized entity. DeFi requires three components: the medium of exchange (cryptocurrencies), the technology backbone for such transactions (blockchain) and the applications that drive the transactions (software, smart contracts, dApps).
Transactions include payments, lending, staking, investment, farming, etc. AI-based systems can be created to automate and provide predictive analytics for the effective performance of these transactions. For instance, it is possible to use AI-powered predictive algorithms to manage crypto portfolios, providing an emotion-free system that manages portfolios effectively in a risk-mitigated manner. This is where AI-powered platforms like SingularityDAO (SDAO) come in.
Components that provide for efficiency in financial systems such as security, privacy, efficiency and user experience, can all be enhanced on blockchain systems by introduction of AI. Traders can also use AI systems to assess credit worthiness of borrowing entities in crypto lending platforms, or can use large data models to predict market trends and automate trading strategies. The ultimate goal of AI-blockchain integration in DeFi is to improve risk management, customize services and products for users, automate processes for better efficiency and enhance security of transactions.
Data sharing is provision of data resources to multiple users or organizations, or provision of similar data to multiple applications. Data can be shared on marketplaces (commercial basis), as collaboratives or as commonly held resources which are accessible to all. The sharing of has legal, ethical and cultural ramifications. Various legal frameworks have made it mandatory to ensure data integrity and privacy during such authorized sharing processes.
AI can be used to automate the process of extracting, analyzing and validating any data from various sources, and can also be used to make this data available in an atmosphere that ensures privacy and integrity. The end result is that only high quality data is available, and it is shared or traded without breaking extant laws. The Ocean Protocol (OCEAN) is an example of how AI models are used to facilitate secure and high-quality data sharing on a blockchain backbone. Such data can then be monetized on a decentralized marketplace.
The role of the blockchain in supply chain and logistics is well documented. Efficiency and cost reduction are two ways in which AI can improve the use of the blockchain in supply chain management. Using the blockchain in supply chain management introduces a safe, immutable and secure way of storing records throughout all layers of the process, in addition to ensuring transparency. Adding aspects of AI here can unlock the massive use case potential that exists in this ecosystem.
AI can be used in automation of warehouse tasks (which reduces labor costs), optimization of stocks, demand forecasting, predictive maintenance and automation of document processing.
Other aspects of AI integration with blockchain that bring improvements in supply chain and logistics management include risk mitigation, optimization of inventory and predictive analytics. Inventory sorting, packing and tracking are all aspects of logistics that lend themselves to AI use. VeChain is a blockchain project that already has an AI integration for predictive maintenance and enhancement of package tracking capabilities.
Tokenization is fast becoming the hottest property in the world of the blockchain, and adding AI algorithms to enhance the tokenization of intellectual property with a view to convert them to tradable assets on blockchain platforms is the next level move. Imagine a situation where the Beatles' catalogue which made Michael Jackson a billionaire even in death is tokenized and put on an AI-blockchain marketplace for sale... how cool would this be? Using proprietary AI platforms to tokenize intellectual property instantly converts an illiquid asset into a liquid one. Think of how this benefits both the owner of the illiquid asset looking to raise cash, and those wishing to buy into such an asset.
Non-fungible tokens are set to hit the next level of their application, which is in their deployment to use cases that actually solve problems in the real world and not to remain as cartoon projects and cartoon marketplaces. In order to solve a major societal problem or a major business problem or a technology problem, there is a need to incorporate AI into these blockchain-based NFTs.
For instance, artificial intelligence models can convert NFTs into smart learning tools. By inserting a generative pre-trained transformer tool into an NFT smart contract, it is possible to come out with an AI NFT that can be used for speech recognition or as a visual learning aid.
People are getting increasingly concerned as to what happens with the food they eat from when the products leave the farms to when they hit the table. This is where AI and the blockchain can be used synergistically to solve one of the world's most talked about issues. Are the food products ethically sourced or produced? Where do these food products go between the point of production and the table? This all has to do with data and tracking. By combining the blockchain's transparency feature and the data handling capabilities that AI brings, it is possible to generate an immutable and comprehensive data track of how food products have moved from the farm to the plate.
Through a process of data collection from every stage within the supply chain, analyzing and cleaning the data with AI models before storing it on the blockchain, an immutable record of the food's convoluted journey from the hands of farmers to the mouths of consumers can be created.
As with all disruptive new technologies, there are ethical and legal ramifications to their large-scale deployment and usage. Being the custodians of the law, governments generally view these technologies with suspicion and are usually quick to attempt to control how people adopt and use these technologies until there is a better understanding of how they work and would affect the populace.
There is still opposition to the widespread use of blockchain-based solutions by many governments, and the addition of artificial intelligence has not helped the situation. The discussion about the ethical, legal and regulatory frameworks for the adoption and deployment of AI-blockchain products and solutions continues, and a lack of standardized regulatory frameworks from one country to the next means that there is still a lot of uncertainty and lack of clarity in terms of strategies for adoption and deployment.
Challenges with computational power and developing the hardware required for running increasingly complex AI algorithms on blockchain networks present scalability challenges. For instance, as of writing this piece, the most popular chipmakers are still having challenges with developing the next-generation processors that will enable a significant ramp-up in computational power. Even companies involved in the generative AI space are reporting that the latest upgrades have not produced the significant jumps in performance that justify the huge research and development costs.
The tokenized space that features AI-blockchain tokens has not metamorphosed into an ecosystem that is driven by its own unique, sector-specific fundamentals. As such, these tokens remain highly speculative in nature and are still tied to the performance of Bitcoin and the major altcoins in the crypto market. Traders are therefore subject to the same kind of huge market volatility that occurs with trading crypto tokens, which demand great risk management performance by the investors to protect their investment.
The executives leading several companies in the AI space indicate that the entire ecosystem is still a heavily untapped goldmine, with near limitless opportunities. Indeed, we are only just scratching the surface when it comes to what can be done with AI solutions on blockchain backbones.
The growth in AI and blockchain ecosystems has been phenomenal since the pandemic. It promises to enter into a phase of exponential growth. The global AI-blockchain market size as of 2022 was estimated at $358 million. This grew to $448.5 million in 2023 and is projected to attain a CAGR of 25.3% in the years 2024-2031, putting the value in 2031 to $2.725 billion. This is according to data provided by SkyQuest in its Blockchain AI Market Insights Report of June 2024. This growth is expected to be fueled by advancements in processor technology and enhancement of machine learning capabilities and decentralized infrastructure.
New AI-blockchain products will be developed in the future in response to new use cases that will be conceived. Already, new uses are being found for existing applications. Thought NFTs were dead and buried? You thought wrong, because AI has come to bring life back to NFTs, and the new AI-driven NFTs are being used in ways that have gone beyond cartoons and artworks to real-life use case deployment. There are other examples that showcase the evolution of use cases for existing applications.
The big money lies with the institutional investors (major banks, hedge funds, etc). When they come into the market with their huge funds, they tend to provide deeper liquidity and more money that drives more research and innovation, with new possibilities. Institutional adoption tends to come in when effective, market-driven regulation is put in place. Increased institutional participation and adoption tend to increase confidence, accelerate growth and create a broader base by which the technologies can be deployed. Their money also drives up trading volumes on the tokens associated with AI and blockchain projects. tradable avenues.
Going forward, the increased adoption and deployment of AI-blockchain solutions worldwide, as governments and citizens get to understand the technologies better and plug into their advantages, is the inevitable pathway. This will only deepen the market and create more opportunity for investors. As the crypto market has shown, today's cents can become tomorrow's thousands and millions of dollars. Early investment and participation is what makes this happen.
So what are the potential trading opportunities that exist for investors? The following are areas of interest:
Most AI-blockchain projects have governance tokens which represent the units of exchange for which developers and users can exchange value. Those who put in work in developing and expanding the ecosystems of these projects can be compensated in the token that represents the medium of exchange.
There are several of these tokens in the market currently, and many others will come into existence as new projects are birthed. Investment into new AI-blockchain tokens can come with significant returns, especially when the timing of such entries coincides with a growth phase. Specifically, industries that have a significant potential for adoption such as finance, logistics and healthcare, are key areas investors can focus on.
Examples of tokens that represent various AI-blockchain projects are as follows:
There are several others in existence, and new ones will still emerge as we move along.
We spoke earlier of the opportunities that lie in the tokenization of assets to make them more liquid and lend them to being used in various ways, either for collateralization or for trading opportunities. AI-blockchain algorithms can potentially be used to tokenize real estate, intellectual property and other illiquid assets. Investors can participate in projects that have this use case, or can create projects that offer such tokenization.
Investing in AI-blockchain tokens or projects provides an alternative investment vehicle which is unaffected by geopolitics, company fundamentals or the prevailing macroeconomic data that impact traditional markets. This can serve as an investment hedge and also provide opportunities for growth in totally new areas.
The coming together of AI and the blockchain presents a potential for opportunities as the world has never known. If blockchain and AI as independent entities have been the greatest disrupting technologies of modern times, imagine what would happen when the synergy of these two new technologies is fully deployed into everyday life. It would create massive investment opportunities for all categories of investors.
This has gone beyond being a mere technological advancement; it represents a peek into how human beings would have to live, work, play and study as it would impact every area of human existence. This promises to be even bigger than when the discovery of the internal combustion engine and fossil fuels more than a century ago totally transformed the world.
