Bitcoin’s future in an AI-driven world may depend less on code and more on central banks.
In a new note, Greg Cipolaro, global head of research at financial services and infrastructure firm NYDIG, argued that artificial intelligence will affect bitcoin primarily through macroeconomic channels and its impact on the labor market.
The key variables are growth, employment, real interest rates and liquidity. Bitcoin, he writes, lies downstream of those forces.
If automation reduces jobs and wages, consumer demand could weaken and, in a severe case, falling incomes would affect debt payments and pressure asset prices.
Those fears appear to be well founded. Just this week, Jack Dorsey’s fintech company Block revealed that it was shrinking to its pre-pandemic size, cutting staff by about 40%. Dorsey cited AI-enabled efficiency for job cuts, something theorized in Citrini’s AI doom research that spooked the market this week.
In such a scenario, authorities could respond with lower rates or fiscal spending to stabilize the economy. That wave of liquidity could support bitcoin, which has often tracked changes in the global money supply.
A different outcome would seem less friendly to the cryptocurrency. If AI boosts productivity and economic growth without major job losses, real yields could rise and central banks could maintain tight policies.
Higher real rates have historically weighed on bitcoin by increasing the opportunity cost of holding it and making risk assets less attractive.
Change in demand
The anxiety around AI echoes past moments of turmoil in human society.
The steam engine displaced manual labor in factories and farms. Then electrification rewired entire industries. Later, computers and the Internet automated administrative work and reshaped retail, media, and finance.
Each wave sparked fears of permanent job loss. In the early 20th century, factory mechanization led to labor unrest as machines replaced skilled craftsmen. In the 1980s and 1990s, personal computers eliminated typist pools and administrative staff. More recently, e-commerce has helped hollow out the role of traditional retail.
However, aggregate demand did not collapse. Productivity increased. New industries absorbed displaced workers, even if the transition proved uneven and painful. Today, we have industries that were unthinkable before the advent of the Internet. Think about cloud computing.
Cipolaro argued that AI may follow a similar pattern. As a general-purpose technology, it requires companies to redesign workflows and invest in complementary tools. Over time, this process tends to expand productive capacity rather than reduce it.
“The implication is not that disruption will be painless, but that the equilibrium response to new technology has historically been integration, not obsolescence,” Cipolaro wrote. “Society’s response to AI will likely follow the same pattern.”
For bitcoin, that distinction is important. If AI ultimately drives long-term growth, the structural context could differ from the short-term shocks that often drive liquidity injections.
Meanwhile, adoption may also increase thanks to agent payments, which would essentially make software pay other pieces of software without human involvement. One of the early visions of Bitcoin focused on machine-to-machine payments, and AI may be the tool needed to make them a reality.
Still, there are currently no incentives for widespread implementation. Credit cards combine rewards and short-term credit, features that stablecoins have not yet matched, Cipolaro noted.
Ultimately, while the rise of AI poses new challenges, what matters is the human response to the disruption it brings. If AI triggers a deflationary shock and forces the money printer back on, or fuels a productivity boom that lifts real returns, bitcoin will reflect that.
