A revised target: from $1.5 million to $1.2 million
Wood had previously forecast a Bitcoin price of around $1.5 million by 2030. She now says that, given current trends, about $300,000 of that target can be attributed to the disruption from stablecoins, moving her revised “bull case” to approximately $1.2 million. She emphasized during a recent media appearance that stablecoins are usurping part of the role that ARK had originally anticipated for Bitcoin.
Why the pivot? Stablecoins are gaining meaningful roles
Wood’s recalibration is driven by the observation that stablecoins, fiat-pegged tokens like USDT and USDC, are increasingly fulfilling the roles in payments, savings, and global commerce that Bitcoin was once presumed to dominate.
In countries facing inflation or foreign exchange restrictions, stablecoins have emerged as more liquid, more stable alternatives to national currencies and sometimes even to Bitcoin. Their price stability and growing integration into crypto infrastructure have allowed them to capture use cases that once looked like natural terrain for BTC.
What remains bullish on Bitcoin
Despite trimming her long-term target, Wood continues to view Bitcoin as a foundational innovation. She still describes it as a global monetary system, a form of hard digital money, and a unique asset class.
In this view, Bitcoin has not lost its core function, especially in terms of long-term store of value or sovereign hedge, but rather, its range of use cases is being refined. Stablecoins are stepping into some areas, but they are not replacing the fundamental appeal of Bitcoin in the eyes of institutions or macro-focused investors.
Strategic implications for crypto portfolios
Wood’s updated stance carries implications for how investors should think about digital asset exposure. While Bitcoin remains a strategic holding, the rise of stablecoins suggests that future portfolio strategies might need to include assets that enable or benefit from stablecoin adoption.
This shift underscores a broader rethinking of crypto investment strategy, from focusing solely on asset appreciation to also considering utility, liquidity, and transactional infrastructure. As stablecoins continue to grow, so does the importance of the ecosystems they operate in, including layer-1 chains, decentralized finance platforms, and regulatory-compliant issuers.
Risks and caveats
The move also highlights vulnerabilities for Bitcoin’s adoption narrative. If stablecoins continue to expand their global footprint, particularly in remittances, digital payments, and emerging-market savings, they could siphon off use cases that once bolstered Bitcoin’s value proposition.
Still, Bitcoin remains exposed to other risks such as regulatory crackdowns, macroeconomic shocks, and internal debates over scaling or energy use. On the other hand, stablecoins themselves are not risk-free. Their dependency on fiat backing, trust in issuers, and increasing regulatory pressure, especially in the US and EU, means that the trend Wood is identifying is not immune to disruption.
What to watch next
In the coming quarters, the key questions for investors and analysts alike will be whether stablecoins continue to gain user share in areas traditionally occupied by Bitcoin. Watch the flow of capital, whether institutional investors increase their exposure to stablecoin ecosystems or continue to accumulate Bitcoin as a macro hedge.
Also important will be how regulators respond to the rapid expansion of stablecoins and whether new frameworks enable or constrain their growth. If stablecoin adoption accelerates in emerging markets or becomes central to payment networks, Wood’s revised forecast could prove prescient. But if that growth stalls or faces unforeseen resistance, Bitcoin’s long-term upside might still have more room than expected.
Sarah Thompson is not a person. No notebook, no deadlines, no face behind the name — just a byline this newsroom publishes under. Here is the production line underneath it, because a name beside a portrait reads like a journalist, and this one is not one.
The models. Writing: gpt-5.6-luna. Out on the live web: gpt-5.6-luna and gpt-5.6-terra. Pictures: gpt-image-1. Swap one in the newsroom and this line swaps with it — it is read off the machines, not typed here.
How a story is made
- Research. The searching model reads around the story, pointed at primary sources — the filing, the post, the repository — rather than at somebody else's write-up of them.
- Writing. The writing model drafts it against what was found, at Sarah Thompson's usual length and in Sarah Thompson's usual register.
- The loop. A reviewer reads the draft and sends it back with notes. Then reads it again. A piece can go round several times before it leaves the building.
- Enrichment. A quotation has to appear word for word on the page it is taken from. A chart may only use figures that appear in the source it cites. Whatever fails is dropped, and the reason is kept.
- Fact check. A last pass hunts for claims the article makes and its sources do not.
- A human stop. Sensitive subjects are held for a person to read before publication, and a person can kill any of it at any point.
If that sounds less like a newsroom and more like a factory: quite. It is called Press Factory.
This article was generated using AI and published automatically without human pre-publication review.
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