AI and Bitcoin: How Artificial Intelligence Is Shaping Bitcoin's Price — Expert Interview

When OpenAI launched ChatGPT in November 2022, few could have predicted that this moment would become a turning point not only for the technology industry, but also for global financial markets. A little over three years have passed since that day — and today, in March 2026, we are witnessing a remarkable picture: the price of Bitcoin, the dynamics of Nvidia stock and the pace of artificial intelligence development have become so closely linked that analysts are seriously talking about a "new technology supercycle" in which AI and cryptocurrencies reinforce each other. Bitcoin, which was worth around $16,000 in November 2022, reached a historic high of $126,000 by October 2025, after which it corrected to the current $66,000. Nvidia, which grew more than 800% during the same period, became the first company in the world with a capitalization of $5 trillion. The correlation between these two assets in 2024 reached 0.88 — an indicator that means virtually synchronous movement.

Michael Levin — leading AI developer at Stanford University, head of a research group on machine learning applications in financial modeling within the Stanford AI Lab. Author of dozens of scientific publications on predictive models, neural network architectures and their application to non-stationary time series, including cryptocurrency markets. Levin's laboratory was among the first to investigate the impact of generative AI development on macroeconomic indicators.

Alexander Mercer — analyst at iTrusty.io, where he leads the column "AI × Crypto: Data-Driven Insights". Mercer specializes in quantitative analysis of the intersection of technology trends and cryptocurrency markets. His weekly analytical reviews are read by over 200,000 subscribers.

Format of our meeting: a dialogue. Michael Levin asks questions from the position of a scientist-developer who sees AI from the inside. Alexander Mercer answers from the position of an analyst who sees how technology trends are reflected in financial markets. Our conversation lasted over two hours and covered everything: from the mathematics of correlations to the physics of data centers, from the macroeconomics of monetary policy to the philosophy of digital assets. Before you is the complete transcript of this dialogue.

Part I. Correlation: when numbers speak for themselves

Michael Levin: Alexander, let's start with the most obvious thing. On the charts, Bitcoin and Nvidia shares — the main beneficiary of the AI boom — look almost like mirror images of each other. How statistically significant is this correlation?

Alexander Mercer: This is an excellent question to start with, because it's easy to fall into two extremes here: either to claim that "everything is connected," or to dismiss it with "correlation is not causation." The truth, as usual, is more interesting than either extreme.

Let's look at the specific numbers. By March 2024, the 90-day correlation coefficient between Bitcoin price and Nvidia stock reached 0.86. This is TradingView data, which is easy to verify. The 52-week correlation in the same period was 0.88 — the highest since January 2023. For context: a value above 0.80 in financial analytics is considered "strong correlation." This means that in 80+ % of cases, when Nvidia rose, Bitcoin also rose, and vice versa.

But that's not all. In November 2025, when Nvidia published a quarterly report showing 62% year-over-year sales growth to $57 billion, the total capitalization of the crypto market jumped 4% within an hour of publication. This is not just correlation on daily charts — this is a real-time reaction, which speaks to a direct causal relationship in the perception of market participants.

Michael Levin: But couldn't both assets just be reacting to the same external factor — for example, to general "appetite for risk" in the markets?

Alexander Mercer: Absolutely right, and this is the most important caveat. In statistics, there is the concept of "spurious correlation" — when two phenomena correlate not because one causes the other, but because both depend on a third factor. And indeed, part of the correlation between Bitcoin and Nvidia is explained by the overall macroeconomic background: Fed policy, appetite for risky assets, dynamics of the S&P 500 index.

As of early March 2026, the 30-day correlation of Bitcoin with the S&P 500 index is 0.55. This is a significant figure that confirms: Bitcoin is now trading as a risky technology asset, not as "digital gold," as it is often positioned. When S&P 500 falls — Bitcoin falls with it. When the technology sector grows on a wave of AI optimism — Bitcoin grows too.

But here's what's interesting: if we remove the "Bitcoin — Nvidia correlation" from the general market background, the connection still remains statistically significant. I conducted this analysis in our laboratory, and the residual correlation after controlling for S&P 500 is approximately 0.35–0.40. This means that about a third of the connection between Bitcoin and the AI sector — is something specific, not explainable simply by general market sentiment.

Michael Levin: And what, in your opinion, stands behind this "specific" third?

Alexander Mercer: I identify five separate channels through which artificial intelligence development affects Bitcoin price. Some of them are obvious, some — not at all. Let's break down each one in detail, because true understanding lies in the details.

Part II. Channel One: AI as a "concentrated economic stimulus"

Michael Levin: You often use this term — "concentrated stimulus." What do you mean?

Alexander Mercer: Look at what happened over the past three years. The world's largest corporations — Meta, Amazon, Alphabet, Microsoft — invested unprecedented sums in AI infrastructure. In 2024, the combined capital expenditures of these four companies on AI were about $230 billion. In 2025, this figure grew to $320 billion. And according to forecasts for the next three years, cumulative investments in AI infrastructure will reach $500 billion.

Nvidia became the first company in the world with a valuation exceeding $5 trillion, showing growth of more than 800% over two years. Investors who invested $1,000 in Nvidia ten years ago today have a portfolio worth $270,000. This is a return of 27,000%.

Michael Levin: And how does this relate to Bitcoin?

Alexander Mercer: Directly. Bitcoin has been trading for several years as a "high-beta technology asset." When the technology sector grows on a wave of artificial intelligence optimism, Bitcoin gets a powerful tailwind. Money flows into risky assets, appetite for innovation grows, and Bitcoin — as a symbol of technological revolution — attracts part of this flow.

Think about it: OpenAI signed a contract with Oracle for $300 billion. Nvidia invests $100 billion in OpenAI. OpenAI spends tens of billions on AMD chips. This is a closed investment cycle that generates a colossal flow of liquidity. And part of this liquidity inevitably flows into the crypto market — because for many investors, Bitcoin and AI stocks are in the same "basket of risky technology bets."

Moreover, we're not just talking about abstract money flows. Specific people who made fortunes on AI startups and Nvidia stock are diversifying some of their profits into Bitcoin. We see this in blockchain analytics data: wallets associated with Silicon Valley venture funds are regularly topped up with large BTC amounts after AI company funding rounds.

Michael Levin: But doesn't this mechanism work in reverse as well? When the AI sector falls, does Bitcoin suffer too?

Alexander Mercer: Exactly. And we saw this very recently. When Nvidia stock fell 12% over concerns about AI market growth slowdown, Bitcoin briefly fell below $90,000. And the current Bitcoin correction from $126,000 to $66,000 is partly explained by the market's general cooling toward risky assets, including the AI sector.

This is a two-way connection. Bitcoin benefits from AI optimism, but also suffers from AI pessimism. And it's this symmetry that makes the correlation so persistent.

Part III. Channel Two: Macroeconomics — from AI to loose monetary policy and back to Bitcoin

Michael Levin: You mentioned the NYDIG research that came out just last week. What's the gist of it?

Alexander Mercer: This is perhaps the most intellectually interesting channel of connection between artificial intelligence and Bitcoin. Greg Cipolaro, head of the research department at NYDIG — one of the largest institutional crypto companies — published an analytical note describing how AI could become a hidden macroeconomic catalyst for Bitcoin price growth.

Cipolaro's thesis is built on classical macroeconomic logic. AI is a general-purpose technology, comparable in scale of impact to electricity and the Internet. Widespread adoption of such a technology inevitably reshapes the labor market. Some professions disappear, others emerge, but the transition period can be painful: rising unemployment, social tensions, slower consumer demand.

And here's where the chain kicks in: if AI causes significant disruptions in the labor market, central banks will be forced to respond. How? By cutting rates. Expanding stimulus programs. Printing money, if you will. And loose monetary policy is historically one of the most powerful drivers of Bitcoin price growth.

Michael Levin: Can you illustrate this with a historical example?

Alexander Mercer: Of course. The most vivid precedent is the 2020 pandemic. When COVID-19 paralyzed the world economy, central banks flooded the markets with liquidity: the Fed lowered rates to zero and launched a quantitative easing program. Result: the M2 money supply in the US grew 40% over two years. And what happened to Bitcoin? It grew from $10,000 to $69,000 — almost seven times over.

According to NYDIG estimates, if AI delivers disinflation through productivity gains (more efficient supply chains, lower costs) and unemployment remains below 4.5%, the Fed could make two to three rate cuts by the end of 2026. And institutional flows into Bitcoin ETFs, which are already averaging $1.5 billion per week, could accelerate even further in such a scenario.

Michael Levin: But isn't the opposite scenario possible?

Alexander Mercer: Absolutely. And Cipolaro honestly discusses this. If the AI boom boosts productivity so much that the economy overheats, real returns rise, and the Fed is forced to tighten policy — Bitcoin will face serious headwinds. Higher rates make risk-free assets (like Treasury bonds) more attractive, and capital flows out of risky assets, including cryptocurrencies.

But there's also a third, most likely scenario, which NYDIG describes as "positive for Bitcoin in any outcome." If AI generates labor market turbulence or financial market volatility that triggers fiscal expansion and monetary easing — the liquidity impulse is likely to favor Bitcoin. That is, even negative consequences of AI for the economy could prove positive for Bitcoin price — through the monetary policy channel.

As NYDIG analysts aptly put it: "AI doesn't compete with Bitcoin — it complements it." And from a macroeconomic perspective, this is truly the case.

Michael Levin: What about the energy aspect? AI data centers consume a colossal amount of electricity. Won't this lead to higher electricity prices, which would hurt Bitcoin miners?

Alexander Mercer: This is one of the most interesting intersections, and it deserves a separate conversation. Let's move on to the third channel — infrastructure.

Part IV. Channel Three: the great hashrate pivot — how Bitcoin miners became AI infrastructure

Michael Levin: Tell me more about the transformation of the mining industry. What exactly is happening?

Alexander Mercer: What's happening is what analysts call the "Great Hashrate Pivot." This is a tectonic shift in the Bitcoin mining industry that began after the 2024 halving and is rapidly accelerating.

The essence is as follows. In April 2024, Bitcoin's fourth halving occurred — the block reward was reduced from 6.25 to 3.125 BTC. Mining profitability dropped sharply. At the same time, electricity costs continued to rise, and network difficulty reached record levels. Many mining companies found themselves on the brink of profitability.

And then artificial intelligence came knocking on their door. Or rather — AI companies that desperately needed one resource: computing power connected to powerful electricity sources. And Bitcoin miners had exactly that — gigawatts of power capacity, cooling systems, land parcels and long-term contracts with energy grids.

Michael Levin: How large is this pivot in numbers?

Alexander Mercer: The numbers are impressive. By October 2025, Bitcoin miners had signed contracts with technology and cloud companies for a total of $65 billion. AI contracts generate three times more revenue per megawatt compared to traditional mining. This is data from CoinShares — one of the largest analytics agencies in the crypto industry.

Michael Levin: Why do AI companies come specifically to miners rather than building their own data centers?

Alexander Mercer: Because time is money. Building a new AI data center from scratch takes three to six years. This includes obtaining permits, laying energy infrastructure, connecting to the grid, building the facility and installing equipment. And a mining facility already has everything needed: strong power connection, cooling systems, physical infrastructure. Its conversion to AI can be done much faster.

A telling example is CleanSpark. It won a contract from Microsoft itself to build an AI data center in Wyoming. Why? Because CleanSpark offered to deploy a 100-megawatt facility in six months. Microsoft, with its colossal resources, couldn't offer that kind of speed from scratch.

CleanSpark CEO Matt Schultz explained this clearly: "Bitcoin miners are uniquely positioned because we know how to quickly build and launch data centers. The main constraint now is access to electricity. And we have it."

Michael Levin: How exactly does the hybrid "mining + AI" model work?

Alexander Mercer: This is perhaps the most elegant aspect of the entire story. Bitcoin mining is uniquely flexible workload. Mining rigs can be switched on and off instantly, with no consequences. AI data centers, on the other hand, require uninterrupted operation — 99.99999% uptime.

In the hybrid model, AI computing acts as a "baseload" — it runs 24/7 and provides stable income. Bitcoin mining acts as "flexible load": it turns on when electricity is in surplus (at night, during strong winds or on sunny days) and turns off when the network is overloaded or electricity prices are high.

MARA Holdings is actively developing this concept. Its head, Fred Thiel, presented at the AIM Summit in London with a presentation describing Bitcoin mining as the "missing link" for AI's energy needs. According to him, electrical grids have enough capacity for all AI needs right now — the problem is that AI loads are inflexible. Mining solves this problem, acting as a buffer.

Moreover, miners earn money by helping power grids. In Texas, CleanSpark shut down its facilities during Hurricane Helen and redirected the energy to the grid — electricity in the hospital was restored within an hour as utilities fixed the infrastructure.

Michael Levin: What effect does this transformation have on Bitcoin price?

Alexander Mercer: A dual one. First, mining companies get stable additional income from AI contracts, which reduces selling pressure on the market. Miners are among the largest natural Bitcoin sellers: they need to sell mined BTC to pay for electricity and equipment. When part of these expenses is covered by AI revenue, selling pressure decreases, supporting the price.

Second, the market revalues miner stocks. Analysts start viewing them not as "derivative from Bitcoin price," but as infrastructure companies at the intersection of two largest technology trends. This attracts institutional capital, which indirectly supports the entire crypto sector.

Data confirms: despite the AI pivot, publicly traded miners increased computing capacity in the first nine months of 2025 more than in the same period of 2024. They're not leaving Bitcoin — they're diversifying, becoming more resilient businesses.

Part V. Channel Four: AI Tokens and the "Tide Effect"

Michael Levin: A whole segment of "AI tokens" has appeared in the crypto market. How do they affect Bitcoin?

Alexander Mercer: This is the fourth channel of connection, and it works through a mechanism I call the "tide effect." When the tide rises, it lifts all boats — both small and large.

Over the past two years, a powerful "AI × Crypto" narrative has formed in the cryptocurrency world. Tokens of projects at the intersection of artificial intelligence and blockchain — such as RNDR (Render Network), FET (Fetch.ai), TAO (Bittensor), AGIX (SingularityNET) — regularly demonstrate outperforming dynamics.

In May 2024, for example, RNDR grew 40% in a single week — this was the largest gain among the top 100 cryptocurrencies. Other AI tokens — AGIX, TAO, FET — grew 17-23% over the same period, significantly outpacing the broader market. Bitcoin grew "only" 1.7% that same week, but it did grow.

In 2025, AI crypto projects attracted more than 1 billion dollars in investments — a significant increase compared to the previous year. This money enters the crypto ecosystem and begins to circulate: some goes into AI tokens, some into infrastructure (Ethereum, Solana), and inevitably some flows into Bitcoin as the anchor asset of the entire market.

Michael Levin: Can you explain the mechanism of "spillover" in more detail?

Alexander Mercer: Of course. Imagine a fund that wants to invest in the intersection of AI and blockchain. It buys RNDR, FET, TAO. But to manage risk, it also holds part of its portfolio in Bitcoin — as the most liquid and established crypto asset. This is standard portfolio management practice.

Additionally, retail investors, seeing AI token growth, enter the crypto market for the first time. Their "entry point" often starts with Bitcoin — as the most recognizable crypto asset. They buy BTC, then redistribute part of it into AI tokens.

The analytics platform DYOR tracks "narrative indices" — which topics attract the most capital. In 2024-2025, "decentralized AI" and "DePIN" (decentralized physical infrastructure) consistently ranked in the top 3 hottest narratives. Hitesh Malvia, founder of DYOR, stated directly: "AI tokens will continue their cyclical rallies because they directly correlate with AI development happening around us."

Thus, the AI narrative doesn't just exist within the crypto market — it acts as a pump, injecting fresh capital into the ecosystem from outside. And Bitcoin, as the largest "boat" in this sea, rises with the tide.

Part VI. Channel Five: AI Inside the Market — How Algorithms Shape Bitcoin's Price

Michael Levin: You mentioned that AI not only correlates with the Bitcoin market but actively shapes it from within. What do you mean?

Alexander Mercer: This is the fifth and perhaps least obvious channel of connection. Artificial intelligence has become more than just an external factor for the crypto market — it has become its internal driving force.

The market for AI trading bots for cryptocurrencies is valued at 47.4 billion dollars in 2025 and is projected to grow to 200 billion by 2035. This is a colossal market growing at 14% per year. More than 60% of institutional investors in cryptocurrencies are already using or exploring AI trading systems. Traders using AI bots demonstrate 20-40% more stable results compared to manual trading.

Michael Levin: How effective are AI strategies for Bitcoin trading?

Alexander Mercer: The data speaks to striking effectiveness. A study published in 2025 in the peer-reviewed journal Frontiers in Artificial Intelligence showed that a Bitcoin trading strategy built by ChatGPT based on a neural network ensemble achieved cumulative returns of 1640% for the period from January 2018 to January 2024.

Another study from Finance Research Letters recorded a 944.85% return for a ChatGPT strategy that integrated technical analysis, macroeconomic indicators, and social media sentiment analysis. AI's key advantage is the ability to process unstructured data: Twitter posts, Reddit comments, news headlines — and extract trading signals from them.

Michael Levin: But if everyone uses similar AI strategies, doesn't that create a herd effect?

Alexander Mercer: This is one of the key risks, and I'm glad you brought it up. When many AI bots analyze the same data and generate similar signals, what's called "herding behavior" emerges. All bots simultaneously decide to buy — and the price soars. All simultaneously decide to sell — and the market crashes.

We've seen this in action. 2025 Nasdaq research confirms: AI bots systematically outperform human traders by 15-25% during periods of high volatility, but in doing so amplify the swings themselves. AI makes the Bitcoin market more efficient during calm periods and more volatile during stress periods.

An interesting competition took place on the decentralized exchange Hyperliquid in late 2025: the largest language models — GPT-5, DeepSeek, and Gemini Pro — traded autonomously. The result was unexpected: general-purpose LLMs only marginally outperformed the market. But specialized AI agents, optimized for specific metrics (Sharpe Ratio, maximum drawdown), showed significantly better results. The conclusion: the future belongs not to ChatGPT as a trader, but to specialized AI models developed specifically for financial markets.

The market is already moving in this direction. WEEX launched the world's first AI trading hackathon with a prize pool of 880,000 dollars and a Bentley automobile for the winner. Such events show how seriously the industry takes AI trading. This is no longer an experiment — it's mainstream.

Part VII. The Energy Paradox: Competition That Became Symbiosis

Michael Levin: Let's talk about energy in more detail. AI and Bitcoin — the two largest electricity consumers in the digital world. Is this competition or cooperation?

Alexander Mercer: Great question, and the answer has evolved over the past two years. In 2023, when the AI boom was just beginning, many believed AI and Bitcoin were competitors for limited energy resources. But by 2026, it became clear that symbiosis was forming.

Let's look at the scale. Data centers in 2024 consumed approximately 415 terawatt-hours of electricity — roughly twice as much as all Bitcoin mining. In the US alone, data center consumption reached 183 TWh, or 4.4% of national demand. By 2030, an eightfold increase in AI electricity demand is expected.

Michael Levin: And how do they solve this problem jointly?

Alexander Mercer: Through the model I described above: hybrid facilities where AI is the baseload and mining is flexible. But there are other aspects too.

First — shared innovations in cooling. Both AI and mining generate enormous amounts of heat. Liquid cooling and immersion cooling technologies developed for one sector are applied to the other. MARA Holdings is developing custom high-density mining installations with immersion cooling that can operate side by side with AI servers.

Second — joint investment in renewable energy. Major cloud providers — AWS, Google Cloud, Microsoft Azure — have announced long-term plans to achieve zero emissions. They are experimenting with energy storage, AI-managed cooling systems, and local generation from renewable sources. Bitcoin miners, in turn, have long placed facilities near sources of cheap "stranded" energy — energy that would otherwise be lost without a consumer. Their experience is valuable to the AI sector.

Third — AI optimizes mining itself. Data centers conducting cryptocurrency operations often use AI tools to manage energy distribution, forecast heating, and schedule loads for periods when renewable energy is available in excess. This creates a closed loop of mutual optimization.

Fourth — regulatory advantage. Bitcoin mining has often been criticized for energy consumption, and in some regions (New York, British Columbia) moratoria have been introduced. AI, by contrast, is perceived as a "public good." Converting mining facilities into AI data centers improves the industry's reputation and mitigates regulatory risks.

Part VIII. Chronology: How AI and Bitcoin Moved in Sync

Michael Levin: Can you walk us through the key moments where AI events directly coincided with Bitcoin price movements?

Alexander Mercer: Gladly. Let's walk through the chronology — it's very revealing.

November 2022. OpenAI launches ChatGPT. In the same period, Bitcoin and Nvidia stock reach bottom after a prolonged decline. BTC trades around 16,000 dollars, Nvidia around 11 dollars per share (adjusted for splits). This is the "zero point" of a new supercycle.

January-March 2023. ChatGPT gains 100 million users in two months — a record for any application in history. The scale of the AI revolution begins to sink in. Nvidia begins its rally. Bitcoin slowly recovers, surpassing the 25,000 dollar mark.

May 2023. Nvidia publishes a quarterly report that shocks the market: data center revenue exceeded all forecasts. Shares soar. Bitcoin rises in parallel amid general technology optimism.

End of 2023 — beginning of 2024. Microsoft invests 10 billion dollars in OpenAI. Google releases Gemini. The AI race reaches a new level. Bitcoin surpasses 40,000, then 50,000 dollars. In January 2024, the SEC approves the first spot Bitcoin ETFs. Institutional capital floods into the market. The BTC/NVDA correlation reaches a record 0.88.

March 2024. Bitcoin exceeds its previous all-time high for the first time, reaching 73,000 dollars. Nvidia is now worth over 2 trillion. AI tokens (RNDR, FET, TAO) show triple-digit gains for the quarter.

April 2024. Bitcoin's fourth halving. Block reward falls to 3.125 BTC. Massive pivot of miners to AI infrastructure begins.

Mid-2024 — summer 2025. Parallel growth continues. Bitcoin rises to 100,000, then to record 126,000 dollars by October 2025. Nvidia surpasses 5 trillion in market cap. AI investments hit all-time highs.

October 2025 — March 2026. Correction. Bitcoin falls from 126,000 to 66,000 amid geopolitical instability, trade wars, and general risk appetite cooling. Five consecutive "red" monthly candles. AI stocks also correct, though less sharply.

March 2026. NYDIG publishes research on the AI-Bitcoin connection through monetary policy. BTC/S&P 500 correlation — 0.55. The market awaits the Fed's decision. Miners continue diversification. Bitcoin trades around 66-68 thousand.

Michael Levin: This chronology shows that the connection — is not just correlation over a single time period, but a stable pattern?

Alexander Mercer: Exactly. Every major AI trigger — whether a new product launch, an Nvidia report, a major AI investment — was accompanied by a reaction in the crypto market. Not always immediate, not always proportional, but consistently repeating. For a scientist, that's far more convincing than one pretty aligned chart.

Part IX. Risks: When the Connection Works Against Bitcoin

Michael Levin: Let's talk about risks. If the AI boom turns out to be a bubble, what will happen to Bitcoin?

Alexander Mercer: This is a question every sensible investor should ask. And the answer is not encouraging for bulls.

Some serious analysts are already drawing parallels between the current AI boom and the dot-com crash in 2000. Investment fund GMO warns that the AI boom may be a "bubble within a bubble." Trader and educator Adam Khu reminds us that during the 2000–2002 dot-com crash, Warren Buffett's Berkshire Hathaway grew by 80% because Buffett completely avoided the technology sector. Today, Buffett holds neither Nvidia shares nor Bitcoin, and sits on a record cash cushion of 350 billion dollars.

If the AI bubble bursts, Bitcoin — as a high-beta risky asset — may suffer more than AI stocks themselves. Khu warns: "When the AI/crypto/quantum computing bubble bursts, overvalued and unprofitable assets in these sectors will fall 50–80%."

Michael Levin: What specific scenarios could trigger this?

Alexander Mercer: The first scenario is "AI disappointment." If it turns out that the return on investment in AI is significantly lower than expectations, the market could sharply reassess the entire technology sector. 320 billion dollars invested in AI infrastructure in 2025 — that's a colossal sum. If these investments fail to begin generating proportionate returns, an "AI winter 2.0" could occur.

The second scenario is regulatory shock. If governments begin strictly regulating AI (restrictions on model training, bans on autonomous systems, taxes on AI computing), it will slow sector growth and negatively impact all related assets, including Bitcoin.

The third scenario is an energy crisis. If the growth in electricity consumption by AI data centers leads to power grid overload and a sharp spike in electricity prices, both AI companies and Bitcoin miners will suffer. This risk is particularly relevant given that certain regions have already exhausted available capacity.

The fourth is monetary policy tightening. If the Fed raises rates (for example, in response to inflation caused by rising energy costs), all risky assets will face pressure.

Michael Levin: How can an investor protect against these risks?

Alexander Mercer: Three rules. First — diversification. Don't put all your eggs in one narrative, however compelling it seems. Second — time horizon. Short-term correlation can be deceiving; long-term fundamental factors matter more. Third — critical thinking. When everyone around you is convinced that "AI + Bitcoin = infinite growth," it's time to question the premises.

Part X. A Look into the Future: Three Scenarios for 2026–2030

Michael Levin: Let's look into the future. How do you think the relationship between AI and Bitcoin will develop in the coming years?

Alexander Mercer: I see three possible scenarios. Let's call them "Symbiosis," "Decoupling," and "Bubble."

First scenario: "Symbiosis" (probability 45%). AI continues strong growth, investments pay off, productivity rises. Central banks pursue accommodative policy in response to labor market transformation. Bitcoin miners successfully diversify, providing infrastructure for both AI and blockchain. Bitcoin reaches new highs, fueled by liquidity, institutional interest, and its role as "digital gold" in a world of expanding money supply. Bitcoin price by 2028–2030 — in the range of 200,000–350,000 dollars.

Second scenario: "Decoupling" (probability 35%). The AI market matures, volatility declines. Bitcoin finds its own drivers: regulatory clarity, payment infrastructure development, status as a strategic reserve. Correlation with the AI sector decreases from 0.88 to 0.30–0.40. Bitcoin begins trading more as "digital gold" and less as a "technology asset." Price stabilizes in the range of 100,000–180,000.

Third scenario: "Bubble" (probability 20%). The AI boom fails to meet expectations. Mass disappointment. Major tech companies write down billions in investments. The AI stock market loses 50–70%. Bitcoin, as a related asset, falls 60–80% from peak values, returning to levels of 25,000–40,000.

Michael Levin: Which scenario do you find most likely?

Alexander Mercer: If I had to place one bet, I'd bet on "Symbiosis" with elements of "Decoupling." It seems to me that in 2026–2027, the correlation between AI and Bitcoin will remain high, but starting in 2028–2030 it will begin to weaken as both markets "mature." AI will become a common tool, and Bitcoin — a recognized asset class. They won't need to "drag" each other along anymore.

But the "Bubble" scenario shouldn't be dismissed. History teaches us that every major technology cycle — railroads, radio, the internet — was accompanied by a bubble and a correction. There's no reason to think AI will be an exception. The question is only when and how deep the correction will be.

Part XI. What This All Means for the Average Investor

Michael Levin: To summarize: what should an ordinary person interested in both AI and Bitcoin take away from this conversation?

Alexander Mercer: First and foremost: the link between artificial intelligence and Bitcoin price is real and multifaceted. It's not a random coincidence of charts. It works through five specific channels: general market sentiment, monetary policy, physical infrastructure, AI-crypto projects, and AI trading.

Second: this link is two-way. Bitcoin gains from AI optimism but also loses from AI pessimism. Anyone investing in Bitcoin should monitor the AI market — and vice versa.

Third: don't confuse correlation with guarantee. The fact that Bitcoin and AI rose together for three years doesn't mean they'll rise together forever. Markets change, narratives change, fundamental factors change.

Fourth: diversification is your best friend. If you believe in AI, you don't necessarily have to express it through Bitcoin. If you believe in Bitcoin, you don't necessarily have to tie that belief to AI's success. Having exposure in both directions is wise, but putting all eggs in one basket is reckless.

Fifth: monitor macroeconomics. Fed decisions on rates, money supply dynamics M2, labor market indicators — all of this now is directly linked to both AI and Bitcoin. Understanding macro context gives you an edge over those who only look at charts.

And sixth, most importantly: we're living in a unique time. Two technological revolutions — AI and decentralized finance — are happening simultaneously and reinforcing each other. Regardless of how markets behave in the coming months, the long-term fundamental factors — growing computing needs, fixed Bitcoin supply, transformation of the financial system — remain in force.

Michael Levin: Alexander, thank you for such a deep and thorough interview. One last question: what would you say to someone who is only now considering investing in Bitcoin against the backdrop of the AI boom?

Alexander Mercer: I would say: don't invest in Bitcoin "because of AI." Invest — or don't invest — based on your own analysis of fundamental factors, understanding of risks, and your personal financial situation. AI is one of many factors affecting Bitcoin's price. Important, but not the only one.

Study the subject. Read research. Understand the technology. Grasp what's behind the numbers. And never invest more than you're willing to lose. This rule applies to Bitcoin, AI stocks, and any other asset.

The world is changing faster than ever before. Artificial intelligence is restructuring the economy. Bitcoin offers an alternative to the traditional financial system. The link between them is one of the most interesting economic phenomena of our time. And it seems to me that we're only at the very beginning of this story.

Part XII. Practical Section: Which Metrics to Watch

Michael Levin: For those of our readers who want to independently track the link between AI and Bitcoin — what metrics and indicators would you recommend?

Alexander Mercer: Excellent practical question. Here's my list of metrics that I personally track weekly and recommend to everyone seriously studying this topic.

First — BTC/NVDA correlation. You can track this for free on TradingView. Look at 90-day and 52-week coefficients. A value above 0.70 indicates the link is active. Below 0.30 — the link has weakened, Bitcoin is trading on its own logic.

Second — Nvidia quarterly earnings. Each Nvidia report is a mini-event for the crypto market. Follow the revenue from the Data Center segment — it reflects actual demand for AI computing. If revenue exceeds forecasts — expect a positive crypto market reaction within 24–48 hours.

Third — flows into Bitcoin ETFs. Data on daily inflows and outflows from spot Bitcoin ETFs (available, for example, on SoSoValue and CoinGlass websites) are a direct indicator of institutional interest. Sustained inflows — bullish signal. Outflows — bearish.

Fourth — Fed rate decisions and M2 money supply dynamics. This is the macroeconomic backdrop against which the entire AI × Bitcoin story unfolds. Policy easing — positive for both. Tightening — negative. Fed data is publicly available.

Fifth — Big Tech capital expenditures on AI. Each quarter, the largest tech companies report their CAPEX. If combined AI infrastructure spending continues to grow — the "AI stimulus" for the economy persists. If it starts declining — that's a warning signal.

Sixth — AI token activity. The DYOR platform tracks "narrative indices" of the crypto market. If the "Decentralized AI" or "DePIN" category is in the top-3 for capital inflows — the AI narrative in crypto is strong. If it drops out of the top-10 — interest is fading.

Seventh — miner contracts with AI companies. Reports from CoinShares and analytical notes from Bernstein track how many megawatts and dollars miners redirect to AI. Growth in these metrics is a fundamental bullish factor for the sustainability of the mining ecosystem.

Eighth — Bitcoin network hash rate and difficulty. Despite diversification into AI, if hash rate continues to grow — mining remains profitable and the network is healthy. Sustained hash rate growth alongside AI expansion — the best possible scenario.

Michael Levin: Is there a single "AI-Bitcoin connection index"?

Alexander Mercer: Not yet, but I'm confident such an index will appear by 2027. At iTrusty.io, we're working on a composite indicator that combines BTC/NVDA correlation, ETF flows, Big Tech CAPEX, and AI token activity into a single metric. For now it's in beta testing, but early results look promising — the index adequately predicted the October 2025 correction two weeks before it began.

Editor's Afterword

Our conversation with Michael Levin and Alexander Mercer lasted over two hours and, frankly, could have continued for that long again. The link between artificial intelligence and Bitcoin is a topic that accumulates new data literally every week. The NYDIG research published a few days before our meeting only confirmed: the academic and professional community is taking this link increasingly seriously.

The key conclusions from the interview can be reduced to five theses. The correlation between Bitcoin and the AI sector is statistically significant and partially persists even after controlling for common market factors. AI affects Bitcoin's price through five channels: market sentiment, monetary policy, infrastructure, AI tokens, and algorithmic trading. Bitcoin miners are transforming into AI infrastructure, creating a physical "bridge" between the two technologies. AI trading bots already manage a market worth 47 billion dollars and systematically outperform human traders. The connection carries risks: if the AI boom turns out to be a bubble, Bitcoin could suffer significantly.

For those who want to delve deeper into the topic, we recommend the original NYDIG research "Bitcoin in the Age of AI," available at nydig.com, as well as scientific publications referenced by our experts: research from Frontiers in Artificial Intelligence and Finance Research Letters on AI strategy returns in the crypto market. Scientific papers from Michael Levin's lab are available on the Stanford University website.

You can follow Alexander Mercer's analysis on iTrusty.io, where he runs the "AI × Crypto: Data-Driven Insights" column.

This material is informational and analytical in nature. It is not an investment recommendation. The cryptocurrency market is associated with high risks. Conduct your own research and consult with a financial specialist before making investment decisions.