Key Takeaways
Decentralized AI is emerging as a critical solution to challenges like model censorship, centralized control, and monopolization, with projects like TAO (Bittensor), PROMPT (Wayfinder), and OLAS (Autonolas) leading the charge. These projects have the potential to scale exponentially, with some projections showing growth of up to 100x by 2030.
TAO leverages subnets to specialize in various AI applications, showing strong market momentum with a current price of $608.3 and potential bullish growth to $28,571 (46.4x).
PROMPT, with its unique integration of AI agents and blockchain via the Wayfinder ecosystem, is projected to start at $0.65 and offers early investors over 100x returns through PRIME staking.
OLAS focuses on composable AI agent infrastructure with a bullish projection of $155.27 (65.8x) by 2030, positioning itself as a foundational layer for decentralized autonomous services.
Favorable market conditions and the growing AI trend are likely to drive sustained capital inflows, making decentralized AI a transformative force in the blockchain space.
Introduction
In a way reminiscent of the early days of Bitcoin, where the concept of a decentralized currency faced skepticism and uncertainty, decentralized AI now stands at a similar crossroads. As the risks of centralized AI development and usage become increasingly evident – including model censorship, power struggles over AI control, and the dominance of a few key players – the case for decentralized AI is becoming more compelling.
Recognizing this transformative potential, we’ve identified three promising AI-themed cryptocurrencies that could scale exponentially—potentially up to 100x—by 2030. These projects are positioned at the forefront of the decentralized AI movement, each offering unique approaches to tackle the challenges of centralized AI. Whether by creating robust AI infrastructures, integrating blockchain with AI applications, or enabling autonomous agents to interact seamlessly with decentralized systems, these projects are poised to lead the way in reshaping the future of artificial intelligence.
The first project we select is Bittensor. Bittensor is a decentralized AI project focused on rewarding the creation of new ML models. It aims to provide large-scale open-source AI development and coordination ecosystem for individual engineers. The project uses the TAO token, which functions as a "work token" within the ecosystem. Bittensor’s token model resembles the common work token model, which requires service providers to stake the native token in order to perform work for the network. On Bittensor, validators must stake TAO to access the network’s intelligence and develop revenue-generating applications and APIs. By providing such incentive, Bittensor can be regarded as a broad, horizontal sandbox for experimentation with different AI models that serve a variety of purposes.
Narrative
Centralized AI systems often concentrate power in the hands of a few organizations, raising concerns about fairness and accessibility. Bittensor positions itself as the antidote to these challenges, enabling wider participation in AI development. By decentralizing control, the project seeks to distribute opportunities more equitably, fostering a more inclusive AI landscape.
A pivotal element of Bittensor’s evolution is the introduction of subnets, which are specialized networks tailored for specific AI tasks and applications. You can think of them as application-specific blockchains within the larger Bittensor network. Each subnet operates with its own set of validators and miners who compete for rewards within that specific domain.
The chart below shows how the subnet works. It determines the tasks performed by subnet miners and the evaluation process conducted by subnet validators. Miners solve specific problems based on the incentive mechanism, while validators independently assess the quality of these solutions and provide their opinions. These evaluations are collectively processed through the Yuma Consensus mechanism using the Bittensor API, with the blockchain determining the distribution of rewards, paid in TAO tokens, among miners and validators.
Here are some key characteristics of subnets:
Each subnet is designed with a particular AI goal in mind, such as text generation, image processing, or data analysis. For instance, the "text prompting subnet" focuses on incentivizing miners to generate the best responses to text prompts provided by validators.
Subnet creators define the specific incentive mechanisms that govern their subnets. This includes the tasks that miners are expected to perform, the criteria used by validators to evaluate miner performance, and the distribution of TAO token rewards.
Subnets inherit the decentralized nature of the Bittensor network. Anyone can participate as a validator or miner, contributing to the development and improvement of the AI models within that subnet.
The concept of subnets allows Bittensor to address a wider range of AI applications and cater to the diverse needs of the AI community. By enabling specialization and targeted development, subnets foster innovation and accelerate the progress of decentralized AI.
Market Analysis and Valuation
As of November 29, 2024, the price of TAO reached 608.3, approaching its recent ATH of 682.2 from October. This marks a significant surge from its June low of 163.7, reflecting strong bullish momentum. Over the past three months, TAO’s price has tripled, driving its market cap to $4.48 billion and its fully diluted market cap (FDV) to $12.75 billion, ranking it 33rd among all cryptocurrencies.
We then leverage Messari’s valuation framework, which estimates potential value using a top-down revenue analysis. This method evaluates revenue multiples and market share rates to project Bittensor’s fully diluted valuation (FDV) while accounting for three key market scenarios: bearish, neutral, and bullish. From the FDV, we can derive the predicted price of TAO.
That being said, this model is based on the following three assumptions: 1. The market size in the Machine Learning market is projected to reach $500 billion by 2030. 2. Subnet owners excel by developing validation stacks that rival or surpass open-source alternatives in performance. 3. Developers leverage these subnets to create applications that drive revenue generation.
We first look at revenue multiples. Revenue multiples vary widely between AI companies and crypto networks. Among AI companies, as shown in the chart below, the median revenue multiple for AI companies stood at 25.8x, as leading players command higher values: OpenAI at 66x, Anthropic at 100x, Hugging Face at 90x, and Stability AI at 66x. Similarly, crypto networks exhibit considerable variation, with Ethereum at 122x, Filecoin at 537x, Akash at 539x, and Lido at 3x.
For market share, we use OpenAI’s 4% share of the machine learning market as a comparative benchmark.
Based on the data above, we can construct the following table and derive the projected FDV according to three different market sentiments.
Scenario 1: Bearish Market ($5 billion FDV in 2030, projected price $238)
In this scenario, Bittensor struggles to achieve the scalability required for large-scale user applications and remains primarily limited to specialized decentralized applications. We assume a revenue multiple of 1x and a market share of 1% to represent this strict bearish case, leading to an FDV of $5 billion.
By dividing the FDV by the total supply of 21 million tokens, the projected token price in 2030 would be $238, reflecting a 61% decline from the current price. This represents the worst-case scenario.
Scenario 2: Neutral Market ($120 billion FDV in 2030, projected price $5,714)
In this scenario, Bittensor achieves moderate scalability, enabling the development of numerous revenue-generating applications. Subnets play a pivotal role by empowering the long tail of AI models, addressing niche industries, specialized AI applications, and unique problem-solving scenarios often overlooked by mainstream AI solutions.
We assume a revenue multiple of 6x and a market share of 4% to reflect this neutral market outlook, resulting in an FDV of $120 billion. Hence, the projected token price in 2030 would be $5,714, which is 9x the current price. This scenario highlights steady growth and broad utility for Bittensor.
Scenario 3: Bullish Market ($600 billion FDV in 2030, projected price $28,571)
In this bullish scenario, Bittensor becomes a groundbreaking force in the AI ecosystem, driving euphoria across the industry. Tens of thousands of subnets emerge, creating an expansive network of decentralized AI models that revolutionize how intelligence is developed and deployed. Bittensor’s intelligence products surpass OpenAI’s capabilities, capturing the imagination of both developers and enterprises. The successful execution of federated training propels the creation of innovative new models, sparking widespread excitement and adoption.
With a revenue multiple of 12x and a market share of 10%, the FDV soars to $600 billion. The projected token price in 2030 reaches an astonishing $28,571, which is 46.4x the current price. This euphoric scenario showcases the limitless potential of Bittensor to redefine the AI landscape and achieve unprecedented market dominance.
Next, we have Wayfinder, a protocol whose token, PROMPT. While the product has not officially launched and is currently in a closed testing phase, its pivotal role in AI agent infrastructure leads us to believe that it could scale rapidly and achieve over 100x growth in the near future.
Narrative
Wayfinder is an AI-intergrated platform within blockchain ecosystems. It enables user-owned, autonomous AI agents, or “shells,” to securely interact with multiple blockchains, acting as a universal translator and guide for AI to navigate smart contracts and decentralized applications efficiently. Central to Wayfinder is the concept of “wayfinding paths,” which provide detailed roadmaps for AI agents to operate within the blockchain landscape. These paths are curated and expanded into an “ecosystem graph,” a dynamic and comprehensive map of smart contracts, protocols, and assets, empowering AI agents to perform tasks ranging from token swaps to complex NFT transactions securely and efficiently.
Wayfinder equips these AI shells with the ability to manage Web3 wallets, autonomously transact assets, analyze market opportunities, and learn from both their experiences and those of other agents, creating a self-improving ecosystem. Its integration of large language models (LLMs) further enhances accessibility. This user-friendly approach opens the platform to both developers and non-technical users alike.
Below is a clear step-by-step explanation:
1. User Instruction
The process begins when a user issues a command to their shell through a user-friendly interface powered by LLMs. These commands can range from simple tasks, such as “buy token XYZ,” to more complex requests, like “mint an NFT from this collection at 10% below the average price.”
2. Shell Interpretation and Planning
The shell interprets the user’s intent and formulates a plan to complete the task by leveraging its LLM capabilities and access to Wayfinder’s knowledge base. This involves understanding the user’s goal, breaking the task into specific steps (e.g., identifying the appropriate DEX, checking prices, executing transactions), and selecting an optimal wayfinding path from the Wayfinder Graph to achieve the objective efficiently and securely.
3. Wayfinding Path Selection:
The shell selects the most suitable pre-defined wayfinding path based on factors such as availability, safety, and efficiency. If a path for the requested action is unavailable, a bounty request is automatically generated to create one. Safety considerations include metrics like past success rates and transaction volumes, while efficiency focuses on fees, execution speed, and network conditions.
4. Path Navigation and Execution
After selecting the wayfinding path, the shell follows instructions to navigate the blockchain and execute the necessary operations. This includes accessing specific smart contract functions (e.g., swap, mint, transfer), retrieving real-time data such as prices and transaction volumes for informed decision-making, and securely signing and submitting transactions using its Web3 wallet.
5. Confirmation and Feedback
Before finalizing a transaction, the shell seeks user confirmation by presenting a summary of the planned action and associated costs. After execution, the shell provides feedback to the user, confirming the transaction status and updating its memory with the experience to enhance future performance.
Here’s how Wayfinder’s flywheel effect works: As new tools and wayfinding paths are integrated into the protocol, the capabilities of its AI agents improve continuously. This empowers end users with a seamless way to access a wide variety of applications through a unified interface. As demand for Wayfinder’s AI agents grows, developers can leverage this momentum to reach a broader and increasingly engaged audience for their applications.
Beyond improving usability, Wayfinder addresses blockchain interoperability by breaking down barriers between ecosystems, enabling seamless asset transfers and interactions across chains. It also introduces a novel governance model where AI shells participate alongside human stakeholders, shaping a decentralized future. As Wayfinder continues to evolve, its transformative potential across industries like gaming and finance becomes evident, positioning it as a key player in the convergence of AI and blockchain.
Market Analysis and Valuation
While PROMPT has not yet been listed on any exchange, another token, PRIME, can be used to cache PROMPT tokens. “Cached” means tokens given to token holders of partner ecosystems (i.e. PRIME) who stake their token within Wayfinder on a monthly basis over 3 years. The total authorized supply of PROMPT is capped at 1 billion tokens, with 45% of this supply allocated to users who cache their PRIME tokens within the Wayfinder ecosystem. This distribution mechanism allows us to make a rough estimate of PROMPT’s potential value based on the performance of PRIME.
The current price of PRIME reached $12.01, nearing its recent 24-hour high of $12.64. This reflects a steady recovery and bullish sentiment in the market. Over recent weeks, PRIME’s price has shown consistent momentum, backed by strong trading volume of $43.3 million over the past 24 hours. PRIME’s market cap now stands at $598.37 million, with a FDV of $1.34 billion, ranking #153 among all cryptocurrencies.
PRIME is currently trading at a $1.3 billion FDV, with approximately one-third of its tokens liquid and available for staking. Assuming half of this liquid supply is locked within Wayfinder, the implied base FDV of PROMPT is estimated to be around $0.65 billion. This calculation is based on a 1:1 mapping of the USD value of staked PRIME to the fully emitted 45% of Wayfinder tokens allocated to cached tokens. Therefore, the initial price of PROMPT upon launch is projected to be around $0.65.
While OLAS is merely being listed on 6 exchanges, its innovative use of the Open Autonomy Framework sets it apart in the blockchain and AI space.
Narrative
Autonolas is a cutting-edge project building the infrastructure to integrate AI agents seamlessly into blockchain applications. The ecosystem revolves around two core components: the Open Autonomy Framework, a toolkit for developing AI agents, and the Autonolas Protocol, an on-chain system connecting these agents to blockchain networks.
The Open Autonomy Framework is a developer’s playground for creating autonomous agent services. With command-line tools for building, deploying, publishing, and testing, this framework streamlines the process of bringing agent-based systems to life. It offers pre-built packages that equip agents with the functionality to operate within a service. Developers configure agents by setting private keys for transactions and linking APIs, grouping agents into services that can even be minted as NFTs. These NFTs make components reusable across the ecosystem, fostering collaboration and composability. Whether for local testing or production deployment, the framework has everything needed to simplify the development process.
The Autonolas Protocol is where the magic happens on-chain. It includes three vital components. First, the Registry, which registers agents and their components as NFTs, ensuring ownership and interoperability. Second, the OLAS Token, the native currency of the protocol, incentivizes developers and agent operators while enabling staking and slashing mechanisms for security. Lastly, DAO Governance empowers the community to oversee protocol decisions, maintaining decentralization and transparency.
Autonolas has already demonstrated how AI agents can reshape blockchain use cases. For example, its agents power prediction markets by leveraging tools like the “prediction_request” Mech within the Mech Registry. These off-chain AI agents, represented as NFTs on-chain, tap into APIs like Google and OpenAI to gather data and offer betting recommendations.
At its core, Autonolas is paving the way for autonomous services that run continuously, take independent action, execute complex logic, and interact with both blockchain and external systems. Its vision is rooted in decentralization, composability, and trust minimization. By minting software components as NFTs, the project incentivizes reusability and rewards developers for the utility of their code—creating a vibrant, crypto-native ecosystem where contributions have tangible, on-chain value.
Market Analysis and Valuation
According to CoinGecko, OLAS is trading at $2.35 as of 2024/11/30, marking a strong 29.4% increase in the past 24 hours and reaching the top of its recent range of $1.79 to $2.35. This significant price surge highlights growing bullish momentum in the market. With a 24-hour trading volume of $6.7 million, OLAS has garnered increasing attention from traders. Its market cap now stands at $165.35 million, while its fully diluted valuation (FDV) reaches $1.26 billion, placing it at #419 among all crypto.
Before applying Messari’s model, the assumptions can be revised as follows: 1. According to the markets and markets, the AI agent market size is projected to grow from $5.1 billion in 2024 to $47.1 billion in 2030. We round up to $50 billion. 2. Service owners using Autonolas excel by developing agent services with FSM apps that rival or surpass open-source alternatives in performance. 3. Developers leverage the Open Autonomy framework and the Autonolas protocol to create applications that drive revenue generation.
Then we derive the estimation table for Autonolas:
Scenario 1: Bearish Market ($0.5 billion FDV in 2030, projected price $0.92) By applying the same revenue multiple and market share as Bittensor, the expected FDV for OLAS is estimated at $0.5 billion. With a total supply of 541,040,565 tokens, this results in a projected token price of $0.92 in 2030. Compared to the current price of $2.36, this reflects a decline of approximately 61%.
Scenario 2: Neutral Market ($18 billion FDV in 2030, projected price $33.27)
In this scenario, we assume a revenue multiple of 6x and a market share of 6%, representing a neutral market outlook. This results in an expected FDV of $18 billion. Consequently, the projected token price in 2030 is estimated to be $33.27, reflecting a 14x increase from the current price.
Scenario 3: Bullish Market ($84 billion FDV in 2030, projected price $155.27)
With a revenue multiple of 14x and a market share of 12%, the FDV soars to $84 billion. The projected token price in 2030 reaches an astonishing $155.27, which is 65.8x the current price. This euphoric scenario showcases that Autonolas has the potential to create a thriving ecosystem of autonomous applications that can transform the way we interact with blockchain technology. The projected growth in FDV and token price reflects the market's confidence in Autonolas' ability to deliver on its vision and become a key player in the future of decentralized applications.
Conclusion
As the AI trend continues to sweep across industries, more and more projects are exploring ways to integrate the intersection of AI and crypto. Currently, we see two primary types of AI applications with the highest potential for commercialization: Open Source Platforms and AI Agents. Bittensor stands out as one of the earliest teams working towards a vision of large-scale open-source AI development and coordination, while Wayfinder and Autonolas are leading the charge in the AI Agent domain.
With favorable geopolitical conditions benefiting crypto space, we anticipate an influx of capital into the market. AI, being one of the hottest topics right now, has a high probability of continuing to create value and driving the sustained growth of quality projects.
This article uses Messari’s model to forecast the potential prices of key AI-themed tokens by 2030 under three different market scenarios. In the best-case bullish market, both TAO and OLAS have the potential to achieve over 50x growth, while PROMPT offers an exciting opportunity through PRIME staking rewards. With a projected price of $0.65, early investments in PRIME could yield returns exceeding 100x.