About this episode
Institutions are increasingly pointing to stablecoins, tokenization, and AI as the sectors to watch in 2026, and many are emphasizing the convergence between them. After all, AI agents can’t use cash, but they can transact with stablecoins. They can’t trade stocks, but they can trade tokenized ones. And as centralized AI computation grows more expensive and constrained, decentralized networks are stepping in to meet the demand. So, which assets will benefit the most from this convergence between AI and crypto? Today, we find out.
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Coin Bureau — Crypto And AI Will CONVERGE In 2026!!. Machine-transcribed; use the interactive transcript above to jump the player to any line.
Hello and welcome to Coin Bureau's official podcast channel. My name is Guy and if you're seeking unbiased in-depth information about Bitcoin, cryptocurrencies, Web3, and all manner of related topics, then you've come to the right place. I hope you enjoy today's episode. Institutions are increasingly pointing to stable coins, tokenization, and AI as the sectors to watch in 2026. And many are emphasizing the convergence between them. After all, AI agents can't use cash, but they can transact with stable coins. They can't trade stocks, but they can trade tokenized ones. And as centralized AI computation grows more expensive and constrained, decentralized networks are stepping in to meet the demand. So, which assets will benefit the most from this convergence between AI and crypto? Well, my name is Lewis, and today we find out. Before we begin, you need to know that I'm not a financial advisor,
and nothing in this video is financial or investment advice. It's educational content intended to explore the convergence of AI in crypto. That sounds good, then punch that like button and let's get into it. Now, over the last few years, AI has taken the world by storm, including the financial world. And one of the most exciting developments in the AI space is fully autonomous, agentic AI. These AI agents have the ability to complete basic tasks and in the context of finance, they could be used to manage money. Believe it or not, AI agents are already being used in tradfigh, especially for high frequency trading. Their ability to analyze complex data and act almost instantly with minimal human intervention has made them a core part of financial strategies worldwide. However, as exciting as AI is for tradfigh, it's not necessarily the ideal home, because legacy finance creates several bottlenecks for AI. For example, AI can't complete KYC, so it can't open a bank account. It can only operate through the accounts and wallets
set up by its human users. Simply put, tradfigh systems are built for humans and legal entities, not autonomous software. To unlock its true potential, agentic AI needs things tradfigh can't provide, access to programmable money, tradable digital assets, with instant global settlements, ample amounts of compute, and endless pool of data, and trust-minimized infrastructure. And as you've probably guessed, crypto just happens to offer all of these benefits. Through smart contracts, AI can carry out financial tasks automatically, using cryptocurrency as a frictionless method of payment. This allows AI agents to do things in crypto that were unimaginable just a few years ago. For example, agentic AI can design and execute advanced crypto trading and investment strategies. And because AI can't be influenced by fewer greed, these strategies can be executed with pinpoint precision. A more recent use case that's opened up for AI agents is micropayments,
thanks to Coinbase's X402 protocol. This means that AI agents can now pay each other, creating a fully robotic digital economy. How it'll play out remains to be seen, but it's safe to assume that this will open up entirely new avenues for profit. And if you're looking to make profits by trading crypto, then you have to check out the Coin Bureau deals page. That's where you'll find exchange sign up bonuses of up to $100,000, trading fee discounts of up to 50% and deposit cashbacks of up to 75% on the best crypto exchanges. Just hit the link in the description or scan this QR code, which will take you right to the deals page. There, you'll see all of our offers across a range of exchange partners. Then just click one of the sign up now buttons and that should take you right to the deal. These seals won't be around forever though, so take advantage of them while you can by using the link in the description below or by scanning the QR code on the screen. Now, as I mentioned earlier, AI agents are already being used in Tradify, but as you might have guessed,
they're already being used in crypto too, and not just for trading. AI agents are being used to support all kinds of business models. For example, some oversee project treasuries and there's even experimentation around Dow style agents running business models independently. AI agents are also playing an emerging role in tokenized real-world assets or RWA's, like tokenized stocks, treasuries, commodities, and even real estate. By ingesting huge amounts of real-time market data, they're able to streamline asset verification, compliance, and liquidity management. This saves time and, more importantly, money. While allowing these assets to trade on chain 24-7 without a broker, instead of being restricted by traditional market hours. Meanwhile, more and more individuals are using agentic AI to manage their crypto portfolios. Agents can continuously monitor your asset allocation and compare it to your targets. For example, if your goal is 70% BTC and 30% altcoins and altcoins suddenly rally
to exceed 30%, the AI will automatically rebalance your portfolio by selling some alts and buying BTC. This might sound like handing the keys to your crypto fortune over to a machine. And in many ways it is. Despite this, though, the trend is growing. A report from April last year found that a whopping 87% of respondents would let AI agents manage at least 10% of their portfolio and, as AI continues to improve, that number is likely to rise. However, before you rush to trust your retirement savings to an autonomous piece of code, it's important to know that AI agents are not without their risks. While they can analyze data quickly, their decisions aren't always accurate. Agents have been known to misread technical indicators and often can't distinguish normal market activity from market manipulation. This means AI can make catastrophic mistakes like repeatedly buying the dip on a crypto that's actually being rubbed. They can also over-automate trades,
which means that even small errors can quickly compound, resulting in significant losses that devastate your portfolio. Even worse, AI agents can hallucinate, acting on data that doesn't actually exist and trading as if it were real. Needless to say, this can be disastrous. But the scariest part is that it can happen before you even realize it, since AI often seems overly confident in its decisions, even when it's wrong. AI agents are also extra vulnerable to MEV attacks or MEV attacks. For those unfamiliar, a MEV attack occurs when validators use bots to reorder, copy, or sandwich your transactions for profit at your expense. Since AI trades based on predetermined logic, it's highly predictable, making it easy prey for MEV exploiters. And if that wasn't enough to consider, there's also the obvious risk of handing your private keys over to an AI agent, which, I mean, let's be honest, probably isn't the smartest idea. Not only do you risk your private keys being leaked online,
but if the AI runs into any DeFi protocols or bridges with faulty smart contracts, your funds will be left wide open. Okay, so, so far, we've seen what AI could do, and the risks involved. By this point, you may be wondering why someone would choose a crypto AI model over a mainstream one. The answer is simple, decentralization. But this isn't just a gimmick. AI may actually need decentralization to survive long-term, allow me to explain. For starters, mainstream AI models are almost entirely dependent on centralized cloud infrastructure for training and data storage. Some notable examples here include Amazon Web Service or AWS, Microsoft Azure, and Google Cloud Platform, or GCP, to name a few. The massive data sets and compute power needed to train these models are hosted in corporate data centers. Even when you interact with AI, your queries are routed through these centralized servers. Naturally, this creates reliance on a single provider
and introduces a single point of failure, which is a problem when there are, say, outages at these facilities, like we've been seeing recently. On top of that, centralized AI costs are going through the roof, due to the infrastructure requires. For perspective, analysts estimate that it costs anywhere between 10 to $50 million to build even a small-scale AI data center, with larger ones exceeding half a billion dollars. And that's just the hardware. Power, cooling, networking, and maintenance add up even more to the bill. And as AI advances and adoption grows, these costs will continue rising. And it's not just rising costs. Centralized AI models are also prone to geopolitical risk. Some countries are already restricting or banning foreign AI tools and government systems over concerns around national security. Australia's government has banned China's AI model deep seek for this very reason. Centralized models also face bottlenecks with latency and data transfer.
That's because data has to travel to central servers for processing before being sent back. This can create bandwidth constraints and can slow or even block reliable communication between endpoints. As the AI race heats up, demand for high-performance computing is pushing cloud providers to their limits. Thankfully, crypto offers a solution, decentralized physical infrastructure networks, or D-PIN. And roughly a quarter of all D-PIN projects are focused on decentralized compute. As the name suggests, decentralized compute aggregates active and idle GPUs to distribute computational tasks across a network of nodes, rather than relying on a centralized data center. This allows GPUs to work in parallel, creating a more efficient, scalable way to complete heavy-duty computational tasks. This makes decentralized compute much more cost-effective than its traditional counterparts. But it's not just decentralized compute that matters for AI.
Decentralized storage is another natural fit for the sector. Crypto also enables AI compute to be verifiable on chain, meaning anyone could confirm that the work was done correctly and on which model. And of course, many AI crypto projects have their own tokens to incentivize participation in infrastructure, data computation, compute, sharing, governance, and more. And let's be honest, lots of AI excitement also means lots of speculative trading, which always helps. But decentralized crypto AI has its limits. That's because most crypto projects focus on inference, what outputs AI can generate, rather than training. This means they prioritize responses over the underlying data used to produce them. That's simply because training large models requires enormous computational resources, which most decentralized systems can't reliably provide yet. Conversely, inference is far less demanding and can be easily distributed across a network of nodes.
And this ties into another area where crypto could help AI. And that's gathering better data. Maybe you didn't know this, but big tech firms have been known to scrape data without your consent. On top of that, AI is notoriously bad at distinguishing between what's real and what's fake. This can lead to hallucinations where models confidently generate false or misleading information. This can be caused by incomplete or biased training data, over reliance on pattern matching, and a lack of built-in fact checking. In some cases though, the data feeding AI models can be poisoned. In other words, a bad actor can alter inputs to manipulate the AI's behavior. Be that to push a particular bias or agenda. Sometimes these bad actors will plant hidden vulnerabilities called backdoors, which let them force malicious outputs through the model. In fact, a recent report found that it only takes about 250 malicious documents to corrupt an AI model regardless of its size.
Pretty insane considering how much data that these models actually consume overall. I mean, that's like a drop in the ocean. The good news though, is that crypto provides a solution because it incentivizes users to contribute quality data for AI training in a way that's hard to collect in a centralized way. That's because decentralized systems enable crowdsourcing where contributors are fairly compensated, encouraging participation from groups who otherwise might withhold their data. And because there are multiple participants and everything is on chain and publicly viewable, this means that every contribution to a data set can be tracked and verified, creating a tamper proof record of where that data came from who contributed to it and when. This also allows users to flag suspicious or low quality data. In theory, this whistleblower approach could allow crypto AI models to be trained on more reliable data sets, resulting in more accurate and less biased outputs. Another key advantage of combining AI with crypto
is enhanced privacy. Tools like zero-knowledge proofs, confidential computing, and secure inference enable AI models to process sensitive information without ever exposing the underlying information. These cryptographic proofs ensure that AI models can be trained securely while remaining compliant with privacy regulations. This makes them great for sectors like finance, healthcare, and enterprise applications. Something else to consider is quantum resistance as AI becomes increasingly vital in healthcare, finance, defense, and infrastructure. Quantum computing poses a growing threat to the cryptographic systems that secure these technologies. Developing quantum resistant cryptography is therefore essential to protect both crypto networks and AI systems. Fortunately, crypto projects are increasingly aware of this threat, and efforts to develop quantum resistant solutions are well underway. To be clear, there's still much work to be done.
But in the long run, AI models and the sensitive data they handle stand to benefit from this technology, helping safeguard their longevity. So, what does this convergence of AI and crypto mean for investors? Well, simply put, it creates massive opportunities, but it also introduces significant systemic risks while AI during strategies, such as automated trading bots, allow investors to execute complex strategies quickly the widespread use of automated AI models could amplify market volatility and potentially undermine market stability. Essentially, the increased use of AI could create a so-called monoculture where many investors rely on the same data to run AI models that act in similar ways. If left unchecked, this could trigger massive price swings in either direction. And at the same time, it goes without saying that we're lying blindly on AI bots is a risky strategy. If it wasn't already clear, AI isn't foolproof and can expose investors
to losses, scams, and even market manipulation. And we should also point out that most autonomous AI systems today aren't truly autonomous at all. That's because they're governed by rules, goals, and constraints defined by humans and require ongoing human oversight and intervention. To be fair, this intervention is a double-edged sort. On one hand, human oversight prevents AI agents from going off the rails and causing massive damage to the market. On the other hand, if humans set the parameters guiding these systems, operators could effectively manipulate them for their own personal gain. Come to think of it, this problem could be exaggerated and crypto, specifically because there's a financial incentive. There's also the question of whether AI-related tokens will truly capture the economic value of AI. To be frank, many AI cryptos are driven by hype rather than genuine utility. In some cases, projects have merely strapped AI to their branding
and introduced AI-specific tokens, even when the project could quite happily function without them. Without a clear use case, these tokens serve a little purpose outside of speculative trading, which, to all intents and purposes, makes them similar to meme coins, not exactly the most innovative concept. And this is where crypto regulation comes into play. While AI-focused cryptos are among the most exciting developments in the space, they also carry significant legal uncertainty. Beyond the concerns around data privacy and cloud computing, many AI projects have minimal KYC requirements, making them more prone to regulatory scrutiny. Thankfully, zero-knowledge proofs could be the solution for everyone involved. For instance, humans can prove they're allowed to participate in the market. AI agents can prove they were trained on ethical data sets, and institutions can prove their clients meet regulations, all without revealing sensitive personal information. And these regulatory concerns may not be an issue for much longer.
As you'll know, regulators are working hard to lay out clear rules of the road for crypto and other innovative technologies as well, including AI. Put simply, with clearer regulation, AI's role in blockchain technology will become much more clear-cut, paving the way for genuine AI innovation in the space. And with regulators taking a more positive outlook on these technologies, this innovation is expected to thrive. The SEC's proposed innovation exemption could be a game changer here, giving promising AI crypto projects a major boost. In any case, the AI crypto convergence is already showing promise. But the real question for 2026 is whether crypto becomes a core part of AI infrastructure or just a speculative play writing the AI hype? In our view, the biggest winners in the AI crypto narrative will be the projects that support critical infrastructure. So think autonomous stablecoin payment rails, tokenization platforms, decentralized compute
and data networks, privacy and verification systems, or a combination of all of the above. These projects will arguably have the most upside potential in the medium to long-term. Well, that is assuming that the impending bear market doesn't burst that bubble before it's even had a chance to inflate. Fingers crossed, though. And with saying that, that's gonna be it for me for today. But I wanna know what you think. Are you bullish on this AI crypto convergence? Are there any projects that you have your eye on? Well, just let us know in the comments below because I wanna know. And if you wanna learn about some Bitcoin miners and why they're pivoting to AI, well, you could check out that video right over here. Also, if you're wondering what other narratives that you should be watching closely for 2026, well, you could find that in this video over here. I think you're all so much for watching and I will see you again soon. It's Lewis signing off. Hello, Guy again. Before you go, if you have a moment,
please do rate and review us. It really helps the podcast grow and find new listeners. Okay, that's all for this episode. Thank you for listening and see you again soon.
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