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Reading: AI-Driven Deflation Could Push Bitcoin to $11 Million by 2036, Says Strive Strategist
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AI-Driven Deflation Could Push Bitcoin to $11 Million by 2036, Says Strive Strategist

Last updated: March 3, 2026 2:46 pm
Published: March 3, 2026
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AI-Driven Deflation Could Push Bitcoin to $11 Million by 2036, Says Strive Strategist
AI-Driven Deflation Could Push Bitcoin to $11 Million by 2036, Says Strive Strategist


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A new forecast from Strive suggests that artificial intelligence could play a surprising role in sending Bitcoin to unprecedented heights over the next decade.

Joe Burnett, Vice President of Bitcoin Strategy at Strive Asset Management, believes AI-driven deflation may force central banks to keep expanding the money supply — a dynamic that could push Bitcoin to $11 million per coin by the first quarter of 2036.

Burnett’s base case assumes that Bitcoin will grow to represent roughly 12% of global financial assets by 2036. Today, Bitcoin accounts for about 0.2%. To reach that target, Bitcoin’s total market capitalization would need to climb to approximately $230 trillion — more than 176 times its current size.

At a current price of around $66,950, this projection implies a compound annual growth rate (CAGR) of roughly 53% over the next decade. While aggressive, this wouldn’t be entirely unprecedented. Bitcoin posted an average CAGR of about 60% between 2015 and 2024, although maintaining that pace becomes increasingly difficult as market capitalization expands.

Nic Puckrin, co-founder and lead market analyst at Coin Bureau, noted that such a forecast would effectively position Bitcoin as a dominant global reserve asset. It would also mean Bitcoin’s valuation becomes significantly larger than the current US M2 money supply, far exceeds the size of today’s US equity market, and approaches double the value of global GDP.

How AI Deflation and Monetary Expansion Could Fuel Bitcoin’s Rise

Burnett’s thesis centers on what he calls an “AI deflation engine.” As artificial intelligence improves productivity and reduces operational costs across industries, prices for goods and services could steadily decline. While that sounds positive on the surface, sustained deflation poses serious challenges in a debt-based fiat system.

In such a system, wages and asset prices may fall during deflationary periods, but debt obligations — including mortgages, corporate loans, and sovereign debt — remain fixed in nominal terms. This imbalance can strain credit markets and increase the risk of financial instability.

To counteract that pressure, Burnett argues, central banks and fiscal authorities may be forced to inject additional liquidity into the economy to prevent a deflationary spiral. Over time, this could lead to structurally loose monetary policy and a persistent expansion of the money supply relative to scarce assets like Bitcoin.

As more liquidity enters the system, investors may increasingly seek hard, supply-capped assets as a hedge against currency debasement. With its fixed supply of 21 million coins, Bitcoin stands out as a prime candidate.

Burnett also highlights the rise of “digital credit” models as another potential catalyst. Companies such as Strategy — currently the largest corporate holder of Bitcoin — are using public securities backed by substantial Bitcoin reserves to raise capital. These structures provide investors with dollar-denominated income while enabling companies to accumulate more Bitcoin.

According to Burnett, this could create a feedback loop: growing global demand for yield fuels digital credit expansion, which in turn increases Bitcoin accumulation. Over time, this dynamic may form the foundation of a new credit system built on verifiably scarce digital money.

Despite the bold outlook, Burnett’s $11 million target remains significantly higher than most other bullish projections. For example, ARK Invest has previously outlined a 2030 bull-case price target of $1.5 million for Bitcoin, with a bear-case scenario closer to $300,000.


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TAGGED:AI-driven deflationBitcoinBitcoin 2036 forecastBTC price prediction
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