Bitwise Asset Management Chief Investment Officer Matt Hougan has outlined a bold outlook suggesting that blockchain and distributed ledger technology (DLT) transaction activity could expand by as much as 100 times in the years ahead.
In a recent investment note examining common investor missteps, Hougan argued that market participants are significantly undervaluing the scale of future on-chain activity, driven primarily by the expanding tokenization of traditional assets and the emergence of autonomous artificial intelligence agents.
Hougan emphasized that many investors currently size blockchain platforms based on existing cryptocurrency trading volumes and payment flows.
This approach, he suggested, fails to account for fundamental structural shifts underway.
One catalyst is the migration of conventional financial instruments—such as equities, bonds, and other real-world assets—onto blockchain networks.
Once these assets become tokenized, they gain the ability to trade continuously around the clock rather than being limited to conventional market hours.
Traditional US equity markets, for example, operate roughly 33 hours per week during standard weekday sessions.
Tokenized versions of those same stocks could instead remain available for trading 24 hours a day, every day of the year—equating to 168 hours weekly.
This alone represents a fivefold expansion in available trading time, which Hougan believes would naturally support higher overall transaction counts even without other factors.
Layered on top of continuous trading is the expected role of AI agents.
These software systems are designed to independently monitor portfolios, analyze market conditions, and execute trades on behalf of users without requiring constant human intervention.
Hougan posed the question of how much more frequently such agents might transact compared to human traders—potentially two times, ten times, or far higher.
Combining extended market hours with machine-driven activity, he wrote, makes a tenfold increase in stock transaction volumes appear readily achievable, while increases of 50 times or even 100 times remain plausible.
The implications extend beyond equities.
Similar dynamics could apply to payments and other forms of financial activity, where AI-driven “agentic” processes might generate substantially greater volumes than today’s human-centric systems.
Because many blockchain networks derive revenue from transaction fees or related activity metrics, a surge of this magnitude could translate into meaningfully higher protocol earnings, even if per-transaction fees compress amid rising scale.
Hougan’s broader note also addressed related investor errors, including underestimating the addressable market for crypto applications as tokenization brings trillions in traditional assets on-chain, and overestimating the competitive advantage of traditional finance incumbents relative to established crypto-native platforms.
These points highlight a gap between current perceptions and the potential reality of blockchain’s role in future markets.
While Hougan acknowledged that expanded trading windows alone may not produce proportional volume growth, the combination of tokenization and AI automation positions blockchain networks for substantially elevated activity levels. Investors who continue extrapolating solely from present-day figures, he suggested, risk missing the opportunity created by this evolving landscape.