The market cycle spanning 2024 to 2026 has consolidated a structural correlation between digital property and the event of synthetic intelligence. Inside that framework, two analysts with institutional backgrounds —Tom Lee, co-founder of Fundstrat, and Jordi Visser, former Chief Funding Officer of Weiss Multi-Technique Advisors— have articulated impartial positions that converge on the identical conclusion: Ethereum is the best-positioned infrastructure to soak up worth generated by autonomous brokers and automatic settlement processes. Each approaches, regardless of departing from distinct analytical frameworks, share a quantifiable core that’s now decisive for any allocation thesis in digital property.
Tom Lee’s studying: gasoline demand, tokenization, and deflationary strain
Lee’s thesis rests on observable community circulate metrics and provide dynamics. His start line is that synthetic intelligence brokers —methods that execute transactions, pay for companies, and handle collateral autonomously— want a programmable settlement forex with no sovereign counterparty danger and steady availability.
ETH fulfills that position due to its twin perform: it’s the gasoline token required to execute any operation on the Ethereum Digital Machine and, concurrently, an asset that may be locked as collateral in staking and decentralized finance protocols.
The rise in non-human exercise on the principle community and on knowledge availability layers that choose Ethereum generates a rise in base price burning via the EIP-1559 mechanism. Lee has projected in a number of analyses that the mixture of a lowered issuance price after The Merge and sustained transactional quantity pushed by AI brokers can flip ETH right into a internet deflationary asset for extended durations. This isn’t a projection based mostly on speculative assumptions, however on the elasticity of block house demand when algorithmic actors working 24 hours a day intervene.
The second vector Lee incorporates is the tokenization of real-world property accelerated by synthetic intelligence. Cash market funds, company bonds, personal credit score rights, and property titles have begun to be represented as tokens on Ethereum and on second-layer options. Synthetic intelligence automates the origination, fractionalization, and restructuring of these devices, decreasing operational prices and multiplying issuance and settlement occasions.
Each good contract deployed, each redemption of a yield token, and each collateral reallocation requires gasoline. The full tokenized worth locked grows, and with it the structural demand for ETH as a computational useful resource and as a reserve asset within the treasuries of issuing protocols.
Added to that is the expectation of institutional flows via spot Ethereum exchange-traded funds (ETFs), authorised in the US in 2024. Lee has identified that the AI narrative gives a valuation anchor that transcends earlier speculative cycles, as a result of it hyperlinks community utility to a macro pattern of enterprise productiveness.
In that scheme, demand for regulated publicity to ETH interprets into shopping for strain on the underlying asset, which is in flip withdrawn from circulation for staking or as collateral in decentralized derivatives markets, intensifying the impact on liquid provide.
Jordi Visser and the “AI Flippening”: settlement, id, and the displacement of belief
Jordi Visser has formulated a thesis of crypto asset market capitalization reordering that he calls the “AI Flippening.” The central argument holds that synthetic intelligence will trigger a shift within the worth hierarchy between Bitcoin and Ethereum as a result of the autonomous agent financial system calls for a programmable settlement layer that Bitcoin can’t present with out modifying its base structure.
Visser buildings his reasoning on three pillars. The primary is the settlement of funds in stablecoins. Greater than 60% of the availability of fiat-backed stablecoins resides on Ethereum and its rollups. AI brokers will settle exchanges of digital items, API entry, parametric insurance coverage, and subscription funds largely in stablecoins, however each operation requires ETH because the gasoline unit.
The amount of automated funds anticipated by the tip of the last decade turns that technical friction right into a everlasting demand vector. Visser factors out that this circulate doesn’t rely on market cycles, however on the growth of computing infrastructure and multimodal language fashions that generate transactions on behalf of customers or firms.
The second pillar is verifiable id and repute for non-human brokers. The operation of autonomous financial brokers requires cryptographic authentication mechanisms, on-chain repute accumulation, and permission administration that don’t rely on a central entity. Ethereum, via account abstraction requirements (ERC-4337), the Ethereum Title Service (ENS), and verifiable credential codecs, gives a decentralized id layer that can be utilized by software program brokers with out human intervention.
The third pillar is a displacement of institutional belief towards verifiable code. In an setting the place synthetic intelligence automates treasury capabilities, mortgage origination, and capital allocation, individuals will demand clear and real-time auditable execution guidelines. Sensible contracts on Ethereum permit verifying compliance with situations with out counting on intermediaries that may modify insurance policies unilaterally.
Visser argues that this neutrality differential will trigger a gradual migration of worth from devices that rely on sovereign jurisdictions towards decentralized protocols ruled by open-source code. The bottom asset backing that infrastructure is ETH, which capabilities because the reserve asset of an algorithmic settlement financial system.
Convergence factors and empirical proof gathered via 2026
Each analysts agree that AI brokers will use public and permissionless networks, discarding enterprise options with managed validators. Unified liquidity, token requirements (ERC-20, ERC-721, ERC-4626), and lending and cash market protocols already deployed with years of safety historical past make Ethereum the one platform able to absorbing demand with out extreme fragmentation.
On-chain knowledge collected from early 2025 to mid-2026 assist a number of of those assumptions. The proportion of gasoline consumed by addresses related to autonomous agent frameworks (comparable to ELIZA, GAME, ubc, and others) rose from lower than 0.5% in January 2025 to exceed 6% of whole gasoline on Ethereum mainnet and sure rollups in June 2026, based on Dune Analytics dashboards and Nansen experiences.
This progress doesn’t come from a single protocol, however from a fragmented ecosystem of brokers executing mortgage settlement transactions, yield place rebalancing, prediction market arbitrage, and knowledge verification for decentralized oracles.
ETH burning metrics correlated with peaks in agent exercise present that days with increased gasoline consumption by these methods coincide with will increase within the internet damaging issuance price. The Dencun improve (2024) and the introduction of blobs for knowledge availability lowered execution prices on L2s, permitting AI brokers to function with transaction prices low sufficient to justify automated enterprise fashions.
The amount enhance on execution layers interprets into increased settlement frequency towards the settlement layer, the place ETH is burned as a part of the batch inclusion course of.
In parallel, real-world asset (RWA) tokenization data monitored by rwa.xyz and The Block point out that the entire worth of economic devices represented on Ethereum and its L2 extensions exceeded 22 billion {dollars} within the second quarter of 2026, a rise of almost 300% because the starting of 2025.
The participation of asset managers comparable to BlackRock, Franklin Templeton, and WisdomTree in issuing tokenized funds has been publicly documented and leverages present good contract infrastructure, decreasing settlement occasions and permitting automated composition with DeFi protocols.
The algorithmic administration of those funds by autonomous treasury brokers provides a further layer of predictable gasoline demand.
The ETH/BTC correlation has proven a related behavioral shift. Between 2022 and 2024, actions of that pair depended nearly solely on macro flows and danger urge for food throughout the crypto ecosystem.
Beginning in 2025, the introduction of ETH ETFs in the US and the rise of AI and tokenization narratives have generated episodes the place the pair appreciates coinciding with bulletins of advances in synthetic intelligence fashions or favorable stablecoin regulation, even in periods the place Bitcoin trades sideways.
Whereas causality is complicated to isolate, 90-day rolling correlation knowledge between the AI fairness index (BOTZ, AIQ) and the ETH/BTC pair have moved from ranges near 0.2 to surpassing 0.6 in some stretches of 2026, a price that analysis groups from FalconX and Kaiko have begun to watch as a part of the post-halving correlation regime.
Implications for valuation and danger allocation
The convergence of those two theses just isn’t restricted to a story train. If gasoline consumption by autonomous brokers maintains the noticed progress price and asset tokenization reaches the volumes projected by market infrastructure analysts, community price income may turn into a variable impartial of the crypto asset worth cycle.
Valuation fashions based mostly on income multiples, comparable to the connection between community worth and annualized charges (NVT adjusted), permit projecting valuation ranges that differ from purely financial approaches utilized to Bitcoin.
The dangers to this thesis lie within the technical execution of the scalability roadmap, competitors from various chains with parallel execution architectures and differentiated price fashions, and the chance that agent frameworks migrate a part of their settlement exercise to layer-3 options or to execution environments that don’t inherit Ethereum’s safety. Thus far, community results, liquidity depth, and token standardization have acted as efficient entry boundaries, however monitoring the market share of TVL and energetic builders stays needed.
The funding case posed by Lee and Visser doesn’t relaxation on imprecise expectations of mass adoption, however on metrics of non-human financial exercise already underway. Ethereum’s capability to perform as monetary infrastructure for autonomous brokers introduces a requirement vector that didn’t exist in earlier cycles and that will modify the availability dynamics and institutional notion of the asset within the coming years.
In that context, the dialogue about whether or not Ethereum can surpass Bitcoin in market capitalization ceases to be tribal hypothesis and turns into a testable speculation with on-chain exercise knowledge, stablecoin progress, and the growth of volumes settled by algorithmic brokers.
