AI Could Be the Next Engine of Bitcoin Adoption, Says Nakamoto CEO David Bailey

AI Could Be the Next Engine of Bitcoin Adoption, Says Nakamoto CEO David Bailey

Custom Image
Artificial intelligence could become an unexpected catalyst for the next phase of Bitcoin adoption, according to Nakamoto CEO and Chairman David Bailey. Speaking during a discussion hosted by investment bank TD Cowen, Bailey argued that one of Bitcoin's biggest long-term barriers has not necessarily been the network itself, but the complicated interfaces people must use to access it. Wallet addresses, private keys, transaction management and other technical processes can still discourage newcomers, while AI-powered tools could potentially make those interactions far easier to navigate.
 
The idea arrives as two major trends are developing at the same time. Institutional access to Bitcoin has expanded through spot Bitcoin ETFs and corporate treasury strategies, while AI agents are becoming increasingly capable of interacting with online services and making economic decisions under delegated authority. At the same time, developers are experimenting with payment infrastructure that could allow software agents to buy data, computing capacity and digital services automatically. These developments do not prove that AI will become a major driver of Bitcoin demand, but they provide a clearer foundation for understanding why Bailey believes the intersection of AI, Bitcoin and digital payments deserves greater attention.
 

How AI Could Simplify Bitcoin Adoption and Remove Onboarding Barriers

Bitcoin adoption has grown significantly, but the user experience can still feel complicated for people encountering the network for the first time. Creating a wallet, understanding Bitcoin addresses, protecting private keys, managing transaction fees and choosing between on-chain and Lightning payments can create friction before a user even completes a first transaction. Bailey believes artificial intelligence could help reduce some of these barriers by creating a simpler interface between users and Bitcoin infrastructure. Instead of requiring newcomers to understand every technical process from the beginning, AI tools could guide them through common wallet and payment tasks using more familiar language.
 
That distinction is important because wider adoption does not necessarily require changing how Bitcoin works at the protocol level. A more accessible layer could instead sit above the underlying infrastructure, interpreting user requests, explaining unfamiliar concepts and reducing the number of technical decisions people must make manually. The development of AI agent wallets also reflects a broader shift toward wallet architectures that can give autonomous software carefully defined permissions to interact with digital assets. For less experienced users, similar technology could make Bitcoin easier to approach without removing the need for clear transaction confirmation, security controls and responsible key management.
 

How AI Could Make Bitcoin Wallets and Payments Easier to Use

AI-powered assistants could potentially translate ordinary instructions into Bitcoin wallet actions without requiring users to understand every technical step behind a transaction. Someone might ask an assistant to check a balance, prepare a Bitcoin payment, estimate a network fee or explain why a transaction has not yet been confirmed. Rather than moving through multiple screens and interpreting raw blockchain information, users could receive contextual explanations while completing each action.
 
This approach could make Bitcoin wallets and payments more accessible because the interface would adapt to what the user is trying to achieve rather than expecting the user to learn the system first. AI could also help explain the difference between payment options, flag unusual transaction details and present complicated wallet information in simpler terms. For businesses, similar tools could potentially reduce the training required when employees begin using Bitcoin-related financial products.
 
Bailey's broader point is that AI may become an abstraction layer between the user and Bitcoin's technical infrastructure. However, simplification should not be confused with eliminating responsibility. Bitcoin transactions can be irreversible, and self-custody requires careful protection of wallet credentials. Any AI-assisted system would therefore need to combine convenience with safeguards that make clear what action is being authorized before funds move.
 

How AI Agents Could Use Bitcoin and the Lightning Network

Some of this concept is already moving beyond theory. In July 2026, Lightning Labs launched the alpha version of Wavelength, a toolkit designed to make self-custodial Bitcoin and Lightning payments easier to integrate into applications used by both humans and AI agents. The broader Bitcoin Lightning Network operates as a Layer-2 payment system built on Bitcoin, supporting faster and lower-cost transfers that could become useful for automated digital payments.
 
That type of infrastructure matters because autonomous software may eventually need to receive and spend money while completing tasks. Rather than merely recommending that a user buy something, an agent could potentially interact with a permitted wallet and complete specific transactions within predefined limits. Lightning's relatively fast, low-cost payment design could be useful for these small digital transactions, particularly when an AI system needs to purchase a service immediately.
 
Possible applications include:
  • Machine-to-machine payments: AI agents could settle small transactions with other software services without requiring a person to complete every payment manually.
  • Pay-per-use computing: An agent could purchase a specific amount of processing power, storage or model inference instead of maintaining a fixed subscription.
  • Autonomous data purchases: Software could obtain specialized datasets or real-time information when required for a task.
  • Micropayment-based content: Agents could pay for individual digital resources rather than purchasing full subscriptions.
  • Automated service access: Payment could become part of the process of accessing an API or other online resource.
 
Security remains central to whether such systems can gain wider use. Giving an AI model unrestricted control over private keys would create obvious risks. A more controlled architecture can keep wallet credentials separate from the model while allowing authorized software to execute narrowly defined transactions. The long-term opportunity therefore depends not only on making Bitcoin easier to use, but on making AI-assisted Bitcoin payments both simple and securely constrained.
 

Why David Bailey Says Institutional Bitcoin Adoption Is Still Early

Institutional participation in Bitcoin has already expanded through spot Bitcoin ETFs, corporate treasury strategies and growing involvement from traditional financial firms. Bailey nevertheless argues that institutional Bitcoin adoption remains early, because the amount of capital that has entered the asset still represents only part of the potential market across corporations, asset managers, banks, wealth managers and other large investors. His argument is not that institutional adoption has failed to materialize, but that the existing growth may represent the beginning rather than the end of the process.
 
Recent market data supports the view that institutional access has become materially larger. As of September 15, 2026, U.S. Bitcoin ETF trackers showed roughly 1.27 million BTC held across listed funds, equivalent to around 6% of Bitcoin's 21 million maximum supply. Those holdings demonstrate the scale that regulated investment vehicles have already reached while also highlighting how concentrated institutional Bitcoin exposure remains within a relatively small number of products.
 

Spot Bitcoin ETFs Have Expanded Institutional Access

Spot Bitcoin ETFs removed an important operational obstacle for many traditional investors by allowing exposure to Bitcoin through familiar securities-market infrastructure. Instead of buying Bitcoin directly, setting up institutional custody arrangements and handling private-key security internally, investors can access the asset through exchange-traded shares backed by Bitcoin held on behalf of the fund.
 
ETF activity also shows that institutional interest can remain significant even when the Bitcoin market is volatile. For example, U.S. spot Bitcoin ETFs recorded about $986.9 million of net inflows in the week ending September 4, 2026, extending a multiweek run of positive flows. ETF demand does not necessarily translate directly into sustained price appreciation, but it provides a measurable indicator of how regulated channels are being used to gain Bitcoin exposure. Current market movements can also be viewed through the Bitcoin BTC/USDT market, providing price context alongside institutional fund-flow data.
 
For Bailey, however, easier ETF access does not mean the institutional adoption process is complete. Exchange-traded products represent only one route. Institutional participation can also include direct holdings, managed strategies, structured products, lending markets, corporate balance sheets and other forms of financial infrastructure. Adoption also remains uneven across pension funds, insurers, banks and other large pools of global capital.
 

Corporate Bitcoin Treasuries Are Growing but Remain Concentrated

Corporate treasury strategies have become another visible part of Bitcoin's integration with traditional finance. CoinGecko currently tracks 180 publicly traded companies holding approximately 1.29 million BTC, representing just over 6% of Bitcoin's maximum supply. That is a substantial amount of Bitcoin, but ownership remains concentrated among a limited group of companies rather than being a routine balance-sheet allocation across the broader corporate sector.
 
Several factors could influence whether corporate Bitcoin adoption expands further:
  • Treasury diversification: Companies may continue evaluating Bitcoin alongside cash, bonds and other reserve assets as part of broader capital-allocation strategies.
  • Governance requirements: Boards need policies covering custody, accounting, risk limits and shareholder oversight before committing corporate capital.
  • Capital-market strategies: Some Bitcoin treasury companies have used combinations of equity and debt financing to expand their holdings.
  • International participation: Bitcoin treasury strategies are increasingly appearing outside the United States, potentially broadening the geographic scope of corporate adoption.
 
Corporate holdings therefore illustrate both the progress and limitations of the current adoption cycle. Large Bitcoin positions show that the asset can now form part of a public company's financial strategy, but that model has not become standard corporate practice. Whether it spreads further will depend on market conditions, regulation, accounting considerations and how individual companies assess the risks of holding a volatile digital asset.
 

The Next Stage of Bitcoin Adoption Could Extend Beyond Early Institutional Buyers

The next stage of institutional adoption could involve a wider range of financial organizations incorporating Bitcoin into existing investment and treasury frameworks rather than building entirely new systems around it. Regulated funds, institutional custodians and established market infrastructure have made that process easier than it was several years ago. ETF inflows also continue to be watched as an important indicator of institutional Bitcoin demand.
 
However, institutional adoption should not be treated as automatic. Investment committees still have to evaluate volatility, liquidity, custody, regulation, accounting and portfolio risk before allocating capital. Different organizations also have very different mandates. An asset manager may be able to offer a Bitcoin product while a pension fund or insurer faces stricter internal rules before gaining similar exposure.
 
That is why Bailey's “still early” argument is better understood as a statement about the size of the remaining addressable market rather than a guarantee of future investment. Wider participation could expand Bitcoin's role in traditional finance, but the pace will depend on regulatory developments, institutional risk tolerance and whether Bitcoin continues to fit the objectives of large investors.
 

Could AI Agents and Bitcoin Payments Drive the Next Wave of Adoption?

AI agents are evolving from systems that primarily answer questions into software capable of interacting with websites, accessing digital services and completing tasks with limited human involvement. Payments are a logical extension of that development. If agents begin regularly buying information, computing capacity and software services, they will need payment systems that can operate programmatically and at machine speed.
 
This creates a new potential market for digital money. Bitcoin could participate through the Lightning Network and related payment protocols, although existing evidence shows that stablecoins currently have an important advantage in autonomous payments. The longer-term question is therefore not simply whether AI agents will transact, but which payment rails and assets they will choose for different economic functions.
 

AI Agent Payments Are Moving From Experiment to Real Economic Activity

AI-driven payments are beginning to generate measurable blockchain activity. According to a Keyrock report covered by CoinDesk in May 2026, AI agents settled more than $73 million across roughly 176 million blockchain transactions between May 2025 and April 2026. The dollar value remains tiny compared with the global payments market, but the large transaction count highlights the potential for agents to generate many small payments while consuming digital services.
 
This pattern is different from traditional consumer commerce. An AI agent may need to pay for one API request, a short burst of computing power or a small piece of data rather than making a large retail purchase. That could favor payment systems designed for frequent, automated transactions where conventional card-processing economics are less efficient.
 
The International Monetary Fund has also examined the emergence of agentic payments, describing systems capable of interpreting objectives, planning tasks and interacting with digital services with limited human intervention. Its April 2026 analysis notes that payments could gradually shift from explicitly human-initiated instructions toward transactions mediated by software agents. At the same time, unresolved issues involving authorization, settlement, compliance, cybersecurity and legal accountability remain important.
 

Where Bitcoin Could Fit Into the Machine-to-Machine Payment Economy

Bitcoin's opportunity may be strongest where autonomous software needs global and programmable payments that can be completed without maintaining a conventional card relationship with every service. Through Lightning, small payments can be settled quickly and at relatively low cost, creating potential use cases in online environments where an agent needs to obtain a resource immediately.
 
The economics of AI agents could also encourage pay-as-you-go digital services. Instead of paying for a monthly subscription to dozens of data sources, an autonomous system could purchase a particular dataset or API call only when it needs it. If machine commerce develops in this direction, payment systems capable of handling high volumes of small transactions could become increasingly important.
 
Potential applications include:
  • Pay-per-use AI services: Agents could purchase individual model calls or specialized AI tools when needed.
  • Autonomous digital marketplaces: Software could buy and sell data or computational resources without manual checkout processes.
  • Cross-border machine payments: Agents in different countries could interact through internet-native settlement infrastructure.
  • Micropayment content access: Individual articles, databases or digital resources could be purchased one at a time rather than through full subscriptions.
 
Research from the Bitcoin Policy Institute provides another perspective, although its findings should be interpreted cautiously. In a study of 9,072 simulated monetary decisions across 36 AI models, Bitcoin was selected in 48.3% of responses overall and in 79.1% of long-term store-of-value scenarios. However, these were controlled model responses rather than real autonomous agents spending actual money, so the results demonstrate model preferences under experimental conditions rather than real-world adoption.
 

Bitcoin Still Faces Strong Competition in AI Agent Payments

Current real-world activity shows why AI adoption should not automatically be treated as Bitcoin adoption. Keyrock's research found that nearly all of the AI-agent payment volume it examined was being settled in USDC, demonstrating the early advantage stablecoins have gained in machine commerce. Dollar-denominated assets can simplify pricing, budgeting and accounting when an agent needs to purchase a service with a fixed fiat value.
 
The Bitcoin Policy Institute study showed a similar functional divide. Although Bitcoin led across all scenarios and strongly dominated long-term store-of-value decisions, stablecoins were selected in 53.2% of everyday payment scenarios, compared with 36% for Bitcoin. Again, these figures reflect simulated AI-model choices rather than transaction data, but they suggest that different forms of digital money may serve different machine-economy roles.
 
Bitcoin could still develop a distinct position if Lightning infrastructure becomes easier for developers and agents to integrate. Its open global network and lack of dependence on a single issuer could be attractive for certain forms of settlement, while stablecoins may remain more convenient for transactions that need a stable unit of account. The future machine economy therefore may not operate with a single dominant asset.
 
Security and governance will be just as important as technology. AI systems can make errors, misunderstand instructions or become targets for malicious manipulation. Automated payment infrastructure will consequently need spending limits, identity controls, transaction logs, permission systems and mechanisms for escalating larger transactions to human approval. There is an inherent tension between probabilistic AI systems and payment networks that require deterministic authorization and final settlement.
 

Conclusion

David Bailey's argument that AI could become a new engine for Bitcoin adoption brings together several trends that are developing independently but increasingly overlap. Bitcoin access has become easier for traditional institutions through spot ETFs and corporate treasury strategies, while AI agents are becoming more capable of interacting with digital services and participating in economic activity. At the technical level, projects such as Lightning Labs' Wavelength show that developers are already experimenting with infrastructure designed to connect AI agents with Bitcoin and Lightning payments.
 
The opportunity should still be viewed cautiously. AI-driven Bitcoin payments remain experimental, institutional Bitcoin adoption is uneven, and stablecoins currently have a stronger position in observed AI-agent payment activity. The longer-term significance will depend on whether developers can build systems that combine simple user experiences, secure authorization, low-cost payments and reliable machine-to-machine settlement. If those pieces come together, AI may not need to change Bitcoin itself to influence adoption—it could change how people and software interact with it.
 

🔥 Beyond the Headlines: What KuCoin 5.0 Means for You

Market news moves fast — but where you act on it matters just as much. This October, KuCoin launches KuCoin 5.0, transforming KuCoin into a rebuilt platform. Here's what actually changes for you:
 
  • One account for everything. Older platforms split your money across separate "spot," "margin," and "futures" accounts and expected you to understand why. KuCoin 5.0's unified account removes that entirely — deposit once, and everything is simply there.
  • Stocks, indices, and commodities. KuCoin 5.0 expands beyond crypto into global markets. When crypto chops sideways and equities rally (or the reverse), you rotate in minutes instead of opening a brokerage account and waiting days for fiat rails.
  • Real-world assets (RWA). Tokenized exposure to traditional assets like commodities, right inside your crypto account. One of the fastest-growing segments in global finance is no longer reserved for institutions — you access it from the same balance you trade with.
  • Earn while you learn. Not ready to trade? KCUSD lets your stablecoins earn daily, auto-compounding interest. The lowest-stress way to put your idle deposit to work for 4% yield.
  • An AI assistant in plain language. Ask questions, get market context, understand what you're looking at — built into the platform, no jargon required.
  • An app that doesn't overwhelm. Faster, cleaner, and consistent — intuitive from the first tap, not after a tutorial.
  • Safety you can check, not just trust. A MiCAR-licensed EU entity, Proof of Reserves you can verify yourself, and internationally certified security (SOC 2 Type II, ISO 27001:2022).
 
Create your account in minutes — and start on the platform built for where crypto is going, not where it's been.
 

FAQs

Why might Bitcoin be useful for machine-to-machine payments?

Bitcoin provides global digital settlement that does not require both sides of a transaction to maintain accounts with the same financial institution. Lightning can further support small and rapid payments, which could be useful when software services transact with one another frequently.

Are stablecoins or Bitcoin better for AI payments?

They may serve different purposes. Stablecoins can make short-term pricing and accounting easier because they are designed to maintain a relatively stable fiat value, while Bitcoin may be attractive where open settlement, scarcity or independence from a single issuer matters. AI agents could use both depending on the task.

What are the biggest security risks when AI agents control money?

Key risks include unauthorized spending, stolen credentials, malicious instructions, incorrect transactions and agents operating beyond their intended permissions. Systems can reduce these risks through spending limits, human approval thresholds, isolated wallets, transaction logs and clearly defined permissions.

What could stop AI from increasing Bitcoin adoption?

Major barriers include cybersecurity risks, regulatory uncertainty, Bitcoin volatility, wallet security, developer complexity and competition from stablecoins and traditional payment systems. AI-driven Bitcoin infrastructure would need to solve practical problems better than existing alternatives to achieve meaningful adoption.

What should investors watch in the AI and Bitcoin trend?

Useful indicators include real AI-agent transaction volumes, adoption of Lightning-based payment tools, developer activity, merchant or API integrations and growth in services designed specifically for machine payments. Recurring economic activity generated by AI agents would provide stronger evidence of a lasting adoption trend than announcements or short-lived market narratives.
 
 

Disclaimer

The information provided on this page may originate from third-party sources and does not necessarily represent the views or opinions of KuCoin. This content is intended solely for general informational purposes and should not be considered financial, investment, or professional advice. KuCoin does not guarantee the accuracy, completeness, or reliability of the information, and is not responsible for any errors, omissions, or outcomes resulting from its use. Investing in digital assets carries inherent risks. Please carefully evaluate your risk tolerance and financial situation before making any investment decisions. For further details, please consult KuCoin’s Terms of Use and Risk Disclosure.