Next AI Investment Target: Cryptocurrency, Franklin Templeton Suggests

Key Points of This Article

• Analysis suggests that the demand for cryptocurrency will expand with the proliferation of AI.
• Cryptocurrencies necessary for AI agents' transactions are the next investment theme.

Evolution of AI and Investment Targets

On the 21st, Franklin Templeton, a major U.S. asset management firm, published an essay by Sandy Kaul, the head of digital assets and innovation, titled "Agent-Based AI—Killer Use Cases for Blockchain and Cryptocurrency" on X.

Kaul believes that the proliferation of agent-based AI will elevate cryptocurrency and blockchain to a new growth area in AI investments.

The emergence of AI has created the most significant investment trend in the stock market in recent years. Currently, the top 10 AI-related stocks account for about 40% of the total market capitalization of the S&P 500, a concentration level not seen since the dot-com bubble.

Institutional investors are actively funding AI infrastructure-related stocks such as semiconductors and data centers. However, Kaul warns that traditional stock-led investment approaches may not fully capture the next growth opportunities brought by agent-based AI.

Just as generative AI has made significant leaps from early AI tools, Kaul predicts that agent-based AI will have an even greater impact on our daily lives. Unlike generative AI, which generates text, images, and code based on prompts, agent-based AI will evolve into autonomous systems that "perceive the environment, plan, and autonomously execute multi-step tasks to achieve higher-level goals."

According to Capgemini's predictions, by 2028, 38% of companies will utilize AI agents as "human team members." AI agents are expected to autonomously handle more transactions, from initiating, tracking, and executing tasks to managing results, with the market size for agent-based commerce projected to reach $3 trillion to $5 trillion by 2030 (according to Nevermined estimates).

Such transactions and payments are likely to occur within enterprise software, with predictions that by 2028, 33% of software products will incorporate agent-based AI, processing up to 15% of everyday decision-making through AI agents.

Infrastructure to support these machine-to-machine (M2M) automated payments is also rapidly advancing. In addition to building machine-to-machine payment protocols by Visa and Stripe, the open standard "x402" from Coinbase includes participation from major payment companies like Google and AWS, as well as several Web3 companies, establishing a system where "software pays software" without human intervention.

Advantages of Blockchain in Machine-to-Machine Payments

To realize M2M transactions where AI agents autonomously conduct payments, a secure, autonomous, and high-throughput (processing capacity) record-keeping system is essential.

A typical transaction by AI agents (such as a single data query or purchasing computational resources for one second) results in a payment of only about $0.001. Therefore, the traditional credit card payment system, which incurs a fixed fee of about $0.30 plus 2-3%, is unsuitable for such high-frequency, ultra-low-value payments.

Kaul argues that blockchain and cryptocurrency infrastructure are the most suitable payment foundations to support the autonomous economic activities of AI agents. He cites the following characteristics:

• Autonomous Contract Generation and Execution: Embedding transaction rules (merchant restrictions, spending limits, validity periods) into single-use tokens generated by AI, allowing for automatic execution and invalidation like smart contracts.
• Decentralized Digital ID: Using cryptographically verifiable AI agent IDs. Each token generated by the agent includes authentication information to verify legitimacy.
• Auditability: Recording all decisions and transactions in an immutable ledger to ensure transparency and traceability.
• Decentralized Computing and Data Access: Reducing dependence on centralized cloud services and utilizing distributed resources like GPU networks to lower AI operational costs.

In terms of transaction processing speed, chains like Aptos (up to 12,933 TPS), Solana (6,284 TPS), and BNB Chain (3,252 TPS) achieve high throughput compared to major chains like Bitcoin (about 7 TPS) and Ethereum (about 75 TPS).

This is considered comparable to Visa, which processes 1,700 to 10,000 transactions per second under normal conditions, but there is a fundamental difference. Visa only records transaction information and requires 1 to 3 business days for actual fund settlement, while blockchain achieves recording and settlement almost simultaneously.

Considering these characteristics, Kaul points out that blockchain will play a crucial role in enabling agent-based AI to unleash its potential in consumer transactions. Furthermore, he stated that the future development of agent-based AI is likely to become a "killer use case" driving the adoption of blockchain.

Potential for AI Proliferation to Boost Cryptocurrency Demand

Kaul predicts that the proliferation of agent-based AI will create direct demand in the cryptocurrency market.

When AI agents utilize blockchain, native tokens of each chain will be required to pay network fees (gas fees). For example, to conduct transactions on Solana, one must hold SOL, so if the transaction volume by AI agents increases, the demand for native tokens may also rise.

Moreover, the increase in network usage fees will lead to revenue growth for each blockchain foundation. These foundations can reinvest their funds into developer grants, bug bounties, and rewards for validators, fostering the development of new applications and projects, creating a positive cycle of growth for the entire ecosystem, as analyzed by Kaul.

Additionally, by autonomously handling payments and operations, AI agents can allow users to enjoy "Web2-like convenience" while maintaining "Web3's unique ownership" without making them conscious of cryptocurrency, Kaul believes.

He points out that the changes brought about by the proliferation of AI agents resemble the transition from web servers and static websites (Web1) to cloud-based businesses and interactive applications (Web2). Just as cloud and mobile companies once drove new growth on the internet, blockchain and decentralized applications (dApps) are expected to become the foundation of the next-generation internet.

Kaul likens this change to the following: In centralized companies, stocks represent corporate value, while in decentralized networks, native tokens and altcoins carry value. Therefore, to benefit from the value generated by decentralized ecosystems, it is essential to hold the native tokens of the respective network and related cryptocurrencies.

In particular, for investors looking to capture growth opportunities in agent-based AI, these cryptocurrencies are likely to become one of the core assets in their portfolios.

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