Tiger Research has released a long-range report looking at what crypto could become by 2036, asking what happens if blockchain still has not fully changed the world in 2026. Instead of building the piece around protocol design or market structure alone, the report uses four ordinary-life scenarios to map out possible changes in money, investing, blockchain infrastructure, and online media economics.
The article was written by Tiger Research and translated by TechFlow. Its core claim is simple: the future it describes is not framed as fantasy, but as an extension of technical shifts already underway.
Judy and the slow handover from local currency to stablecoins
The first story is set in 2036 at a currency exchange counter in the fictional country of Zutopia. Judy, who has worked in the business for 34 years, pulls out a bill counter and starts sorting local banknotes called Bucks. Her reaction is immediate: “People still use Bucks?”
In Tiger Research’s scenario, Bucks still exists in legal terms, but not in practical monetary life. Inflation has eroded its value day by day, and dollar stablecoins have become the default for everyday use. Judy looks back to 2002, when she was 22 and lived through a sovereign default. Banks shut their doors. People could not withdraw lifetime savings. Her father told the family they had to exchange their wages into dollars as soon as they were paid. Waiting even one day meant watching Bucks visibly lose value. People checked black-market dollar rates more often than newspaper headlines. Official exchange rates were largely unusable, monthly FX allowances were capped by the government, and nobody knew when dollar deposits might be frozen.
By the mid-2020s, younger customers were asking Judy a different question: “Can I exchange into USDT?” At first, only a limited group used stablecoins this way, mainly freelancers and exporters receiving overseas payments. They no longer had to rely on banks or stand in line. With a phone, they could move from Bucks into stablecoins and back again when needed.
Judy did not initially think this would replace her job. Older people still wanted cash, and many businesses still needed the local currency. Then the line at the counter started thinning. Younger customers disappeared first, then middle-aged ones. By 2030, payday lines were gone too. Once companies no longer had a reason to hold Bucks, they started paying salaries directly in stablecoins. Bucks was reduced to a functional role for taxes and utility bills.
The report marks 2033 as the turning point. That year, the tax authority changed course and posted a short notice online: USDC and USDT would be accepted as alternative forms of tax payment. Bucks still existed, yet the state itself had publicly signaled that it preferred receiving someone else’s money.
In 2034, the finance ministry followed. Government bonds issued in Bucks repeatedly failed to attract buyers, and the ministry ultimately sold new debt denominated in dollar stablecoins. Civil servant wages moved in the same direction. By 2035, some local governments had begun paying half of public-sector salaries in stablecoins because workers paid only in Bucks were the first and hardest hit by inflation.
Tiger Research uses Judy’s story to show a gradual transfer of monetary functions. Printing money, collecting taxes, and paying wages were once core powers of the state. In this version of 2036, those functions are steadily pulled toward stablecoin rails.
The report ties that scenario to present-day numbers. As of May 2026, it says, stablecoins had a combined market capitalization of about $320 billion and annual transaction volume of $2.8 trillion. For comparison, the U.S. wholesale payment network processes more than $2 trillion in a single day, meaning stablecoins’ yearly volume was only about three weeks of that system’s throughput. Tiger Research also says that after excluding wash trading and fake activity, less than 6% of stablecoin use was tied to actual payments, while 88% circulated inside exchanges for trading and collateral loops.
For the report, the key question is not whether 6% is large enough. It is where that 6% is happening. Stablecoins may have been most visible in New York and Silicon Valley discussions, but the people who urgently need them are in countries where local currency loses value every day, not in places where credit cards and bank accounts already work well enough.
Lia and markets that never close
The second story moves to Singapore in 2036. It is 2 p.m. local time when Lia receives a limit-order alert for NVIDIA on her phone. New York equities are not even open at that hour, yet the NVIDIA chart on her screen is still moving. She buys immediately. On the same display sit U.S. Treasuries, real estate investment trusts, and data-center infrastructure funds, all tradable through one interface.
That is the world Tiger Research is trying to picture: not just stock trading, but trading in nearly every form of value. Lia sums it up with a line the report returns to: “Investing never stops, no matter where you are.”
The report traces part of that shift back to 2021, when 9-year-old Lia watched U.S. retail traders push GameStop shares sharply higher. In that moment, participation itself became central, at times outweighing the asset’s conventional valuation. The organizing layer was not a traditional brokerage house, but an online community.
Tiger Research then cites two data sets from 2025. A World Economic Forum survey across 13 countries found that 30% of Gen Z respondents started investing once they became adults, versus 9% for Generation X and 6% for baby boomers. In the same survey, 86% of Gen Z had learned how to invest before entering the workforce, compared with 47% for boomers.
A separate Coinbase survey from the fourth quarter of 2025 found that 73% of younger respondents said it was difficult to build wealth through traditional channels, higher than the 57% recorded for older generations. The report reads those figures as evidence that investing is already treated as routine by younger cohorts, and that their appetite is not limited to a narrow menu of assets.
Tiger Research pushes the timeline forward again to June 2025, when tokens backed 1:1 by major U.S. equities such as Apple, Tesla, and NVIDIA began flowing into decentralized exchanges. The report says those products came without nationality restrictions and without strict KYC gates. If a user had a wallet address, they could gain exposure to U.S. stocks, with leverage described as effectively unlimited.
Inside the story, Lia logs onto a borderless trading platform called Lemming Brothers and buys a tokenized product linked to a South Korean real estate index. Ten minutes later, her phone vibrates with a liquidation notice. She swipes it away and moves on.
That detail matters because the report is not only describing faster trading. It is describing a different market environment entirely. In Lia’s world, each category of value can be broken down, packaged, and made tradable around the clock. Alerts arrive nonstop. The market becomes part of the ambient noise of life. Her parents, by contrast, are still dollar-cost averaging into “safe assets” through regulated exchanges.
Do-hyun and the collapse of chain sprawl
The third story takes place in Pangyo Techno Valley in 2036. Infrastructure engineer Do-hyun scrolls through a dashboard of blockchain networks and stops. “Ten years ago you had to keep scrolling,” he says. “Now there are fewer than ten.”
He began his career in 2024, which Tiger Research describes as the peak period for Layer 2 rollup proliferation. Anyone could stitch together a framework and stack, launch a chain under a new name, and call it infrastructure. Do-hyun’s employer joined that buildout and deployed validator nodes.
The chain he remembers is called Allchain. In June 2024, driven by airdrop expectations, its total value locked reached $2.2 billion. He still remembers the team celebrating in a meeting room and saying, “At this rate, aren’t we the next Ethereum?”
The feeling did not last. Once the token listed and airdrop rewards were exhausted, both price and usage fell sharply. Tiger Research says projects and users that had arrived for incentives left as soon as Allchain stopped paying, and 97% of deposits disappeared within a year.
The report treats that outcome as representative, not exceptional. Many independent networks that appeared during the same cycle followed a similar path. Incentives pulled in developers and users, but once funding dried up, ecosystems hollowed out almost immediately, leaving silent infrastructure behind.
Cost was part of the problem. Running an independent chain came with heavy fixed infrastructure expenses, and those costs were too large for a single project to carry for long. As maintenance burdens climbed, one Allchain after another shut down and vanished.
Only a small number survived. Tiger Research writes that hundreds of chains once presented as world-changing projects ended up fighting over a market-share remnant only slightly above 10%, then faded out.
Looking back at views common around 2026, Do-hyun says many people confused the number of chains with scalability itself. The report argues the opposite: fragmentation damaged user experience and raised security costs. What users actually wanted was not hundreds of intricate, disconnected networks, but a small set of very large infrastructure layers with durable liquidity and better speed.
He closes the dashboard, picks up his bag, and goes home. The gesture is small, but it closes a larger point in the report. If the list of active chains is much shorter by 2036, crypto’s next phase may come from consolidation rather than endless multiplication.
Jae-hoon and the shift from ad impressions to machine payments
The fourth story is set in Sangam-dong in 2036. Jae-hoon, who works at a media startup, spots a banner ad in the lower right corner of another platform and laughs. “There are still companies sticking banner ads on screens and waiting for readers.”
Tiger Research uses that moment to frame a broader transition in web economics. By its account, banner advertising is no longer the default revenue model in 2036. A platform may keep setting monthly traffic records and still fail to earn meaningful ad revenue because the model itself has lost its footing.
When Jae-hoon entered the media business in the early 2020s, the logic was clear. Write strong articles, bring in readers, sell banners to advertisers. The daily question in newsroom meetings was direct: “How many page views did we get today?”
The break begins in the late 2020s. By 2029, the report says, more than half of global web traffic no longer comes from humans but from AI agents and bots. They scrape articles and summarize them in a second, but they do not look at banner ads.
Media companies initially blocked bots, as many others did, because server costs surged too fast to ignore. That response created another problem. Once a publisher fell outside AI search and recommendation systems, the brand started to disappear. The industry was pushed into a hard choice: block bots and lose traffic, or let them in and earn nothing.
The question spreading through offices was blunt: “Who are we selling content to now?” Tiger Research’s answer is not ad inventory. It is pricing the content itself.
The report puts the technical trigger in May 2025, when Coinbase launched the x402 standard. That standard revived HTTP 402, the long-neglected “payment required” response code. By 2029, the focus was still on building rails such as Know Your Agent, or KYA, verification and settlement infrastructure. The real inflection point came in 2030, when one media company started selling data directly to AI systems through x402. Once that model was validated, other media and data companies adopted it quickly.
At first, the sums looked too small to matter. A single call might only generate a few dozen Korean won. Yet when those calls stacked into hundreds of thousands or even millions per day, the income became meaningful and, in the report’s telling, exceeded what banner ads had delivered in the past.
Jae-hoon puts it this way: “We don’t need to worry about what advertisers think anymore. Machines pay full price, and the company runs on that.” The old web model, which monetized human attention through ads, gradually winds down. In its place comes a machine economy where AI agents transact for content through APIs.
At the end of the story, Jae-hoon shuts his dashboard and picks up a cup of coffee. He no longer checks how many people visited. He checks how many AI agents paid that day. The next morning, hundreds of thousands of agents will be back at the server door, and the payment log will still be growing.
Disclosures and usage terms attached to the report
Tiger Research closes the piece with a standard disclaimer. It says the report was prepared using materials believed to be reliable, but offers no express or implied warranty on accuracy, completeness, or fitness for purpose, and accepts no liability for losses resulting from use of the report or its contents. Its conclusions, recommendations, estimates, forecasts, targets, views, and opinions may change at any time and may differ from the views of other people or organizations.
The document also says it is for reference only and should not be treated as legal, business, investment, or tax advice. Any mention of securities or digital assets is for illustrative purposes and does not constitute investment advice or an offer to provide investment advisory services. The material is not directed at investors or prospective investors.
Under its usage terms, Tiger Research says fair use of its reports is allowed as long as that use does not damage the commercial value of the material. If the report is cited, the user must clearly identify Tiger Research as the source and include the Tiger Research logo. If the material is to be reorganized and republished, separate consultation is required. Unauthorized use may lead to legal action.