Australian crypto exchange Swyftx says AI-enabled microbusinesses and freelancer work could meaningfully expand stablecoin usage over the next decade, particularly for cross-border payments that are often too slow or too expensive for traditional rails.

In a second-quarter industry report, Swyftx projected that the global gig and freelance payments market could grow to $2.1 trillion by 2033, with AI-native workers contributing $775 billion of that total. In its base-case scenario, Swyftx estimated that $262 billion of payments from the AI-native cohort could be settled using stablecoins, assuming an adoption rate of roughly 33%.

Key takeaways

• Swyftx forecasts gig and freelance payments could reach $2.1T by 2033, with AI-native workers accounting for $775B.
• Under a base-case adoption assumption (about 33%), Swyftx projects $262B of AI-native payment volume could be settled in stablecoins.
• Swyftx argues small firms (fewer than five employees) are moving quickly toward AI adoption, potentially expanding the addressable remittance-like use case for stablecoins.
• The exchange links stablecoin demand to fee savings and faster settlement compared with conventional cross-border payment systems.
• Swyftx estimates related “institutional settlement” services could generate up to $1.3B in revenue by 2033 if certain cost assumptions hold.

Why Swyftx thinks AI microbusinesses will push stablecoin volume

Swyftx’s thesis centers on a convergence: accelerating adoption of AI tools among smaller businesses and workers, alongside persistent friction in international payments. According to Pav Hundal, lead market analyst at Swyftx, the trend isn’t just about technology—stablecoin uptake depends on whether the incentives and operational conditions make it worthwhile.

“Adoption doesn’t happen just because the technology exists. It happens when the economics are compelling, and the rules are clear. For stablecoins, both of those conditions are now falling into place.”

The report frames stablecoins as a direct beneficiary of payment utility demand. Swyftx notes that stablecoin market capitalization has doubled over the past two years and that stablecoins reached a record $1.79 trillion in volume in June, citing this as evidence that use cases are expanding beyond speculation.

Small firms, solo founders, and cross-border invoices

A key part of Swyftx’s argument is that the “center of gravity” for AI adoption may be shifting. The exchange says the smallest firms—those with fewer than five employees—are among the fastest-moving participants in adopting AI. In its view, this shift has helped create a new class of solo entrepreneurs who can operate like microbusinesses while serving global clients.

Swyftx estimates solo workers number between six and 10 million today, with a projection that they could reach 17 million over the next decade. It argues these workers frequently invoice across borders and typically deal with payment sizes and timing patterns that are not well optimized by conventional banking and payment infrastructure.

Because these solo founders are likely to be particularly sensitive to remittance and transaction fees, Hundal described the market as “potentially chunky” for stablecoins—suggesting that small savings per transfer could compound into substantial aggregate demand.

Swyftx also suggests that if its stablecoin settlement projections materialize, the benefits may not stop at end users. It says the “institutional settlement layer” beneath these payments—over-the-counter liquidity, custody, and yield services for platforms routing payments—could capture a new revenue stream. In its scenario, that revenue opportunity could reach as much as $1.3 billion by 2033, contingent on the assumption that total transaction, liquidity, and custody costs sum to 0.5%.

Speed and cost: stablecoins versus traditional cross-border payments

Swyftx contrasts stablecoin transfers with what it describes as the shortcomings of traditional cross-border rails: high fees, settlement processes that can take multiple days, and limited availability in more than 50 countries.

To illustrate potential savings, Swyftx points to stablecoin transfers using Ethereum layer-2 networks. It claims such transfers can reduce fees by 80% to 90%, and it cites an example in which the average freelancer could save about 86% per year in transfer fees. The implication for investors and builders is straightforward: stablecoin adoption tends to be strongest where it meaningfully improves the cost-benefit equation of moving money internationally—especially for frequent or recurring small-to-mid size payments.

Separately, the report references the “agentic AI payment” narrative as another driver of stablecoin volume. The reasoning, as Swyftx frames it, is that AI agents will not have direct access to bank accounts, so they will likely rely on crypto-based rails to execute payments. While the report does not provide quantified forecasts specifically tied to autonomous agent payments, it treats the payments workflow gap as a structural reason stablecoins may be used more often.

What to watch as the stablecoin use case evolves

For readers tracking where stablecoin demand could go next, Swyftx’s projections highlight two variables to monitor: how quickly smaller businesses and solo operators translate AI adoption into real payment workflows, and whether the economics of stablecoin settlement—fees, liquidity, custody, and routing—continue improving enough to sustain wider usage. The next question is not only whether AI becomes more common, but whether stablecoin infrastructure can meet the operational needs at scale.

SBI is reportedly preparing to launch a lending product offering a 3% annual yield on its JPYSC stablecoin, adding a yield feature weeks after introducing Japan’s first trust bank-backed yen stablecoin.

According to a Monday report by Nikkei, the Japanese financial group could introduce the service as early as this month through its crypto exchange, SBI VC Trade. The product is expected to lock users’ JPYSC holdings for three months while paying a fixed annual yield of 3%.

The reported lending service follows the recent launch of JPYSC, a yen-backed stablecoin issued by SBI Shinsei Trust Bank under Japan’s trust bank framework. SBI previously said the stablecoin was built to lower transaction costs, support large block transactions, and serve both retail and corporate users.

SBI adds yield feature to JPYSC

Announced in February by SBI Holdings and Startale Group, JPYSC operates under Japan’s Type III electronic payment instrument framework and is fully backed 1:1 by the Japanese yen. The stablecoin is designed for cross-border payments, treasury management, and tokenised asset settlement, while SBI VC Trade acts as its primary distribution platform.

At launch, SBI said the stablecoin was developed for institutional-grade performance and to connect traditional banking systems with blockchain networks. The companies also said financial institutions and large corporations had expressed interest before the rollout.

The reported lending product adds another service around JPYSC as SBI continues to expand its regulated digital asset business. On July 7, SBI became the sole investor in Gauntlet’s $125 million Series C funding round, invested another $76 million as the sole backer of institutional crypto marketplace EDX Markets, and completed the acquisition of Japanese crypto exchange Bitbank for nearly $289 million.

EDX said the new funding will support trading, clearing, settlement, product development, and international expansion, while SBI described the investment as part of its digital asset strategy.

Elsewhere in Japan, interest in stablecoins has continued to spread across both financial institutions and commercial businesses.

A separate Monday Nikkei report said convenience store operator Lawson has started a trial allowing customers to make payments with the JPYC stablecoin at one of its stores. JPYC is recognised as Japan’s first legally approved yen-backed stablecoin.

Japan’s three largest banking groups, MUFG, SMBC, and Mizuho, also announced last month that they plan to begin live commercial transactions using a jointly issued stablecoin during fiscal year 2026, adding another regulated payment project to the country’s expanding stablecoin sector.

Turkish prosecutors have accused 504 people of operating an alleged money laundering network that moved nearly 40 billion Turkish liras through shell companies, jewellery stores, payment providers and cryptocurrency transactions.

According to a 1,548-page indictment prepared by the Istanbul Chief Public Prosecutor’s Office, the suspects allegedly used shell companies, bank accounts, foreign exchange offices, point-of-sale terminals and crypto transfers to disguise proceeds generated from illegal betting operations.

Prosecutors alleged the network established a web of front companies that allowed betting revenues to enter the financial system before being routed through a proprietary digital accounting platform known as “M80.” The indictment stated that the system handled the movement and tracking of the group’s financial operations.

Investigators further alleged that part of the proceeds was converted into cryptocurrencies before being transferred abroad. The indictment also accused members of the network of attracting victims into fraudulent investment schemes by promising unusually high returns.

Turkish prosecutors are seeking prison sentences of up to 34.5 years for alleged ringleader Türker Ak and up to 31 years for alleged network manager Murat Dönmezoğlu.

Turkish authorities have increased their attention on crypto-related investigations. Last year in August, Ethereum core developer Federico Carrone, known online as Fede’s Intern, was detained for about 24 hours after the Turkish Ministry of Internal Affairs accused him of helping others misuse the Ethereum network. 

Carrone denied any involvement in illegal activity, saying his work focused on academic research into privacy tools, and he was later released before returning to Europe.

Taken together, the recent investigations show regulators in several jurisdictions continuing to examine how cryptocurrencies are used in financial crime, with enforcement increasingly targeting laundering networks, cross-border fund movements and digital asset transactions linked to alleged criminal activity.

Crypto laundering remains under scrutiny

The case adds to a series of recent enforcement actions across the globe in which authorities have identified cryptocurrencies as one method used to move or conceal illicit funds rather than the underlying source of criminal activity.

Earlier this year, the People’s Bank of China said virtual currency laundering would remain one of its enforcement priorities as part of its next anti-money laundering strategy. Chinese authorities said criminal groups increasingly combine virtual currencies with cross-border fund transfers, underground banking networks and nominee accounts to make transactions harder to trace.

Ireland has also identified crypto assets as a “very significant” money laundering and terrorism financing risk in its latest National Risk Assessment. The country’s Department of Finance said it plans to introduce industry standards governing crypto-related sources of funds by the second half of 2027 while strengthening anti-money laundering controls across the financial sector.

Australia-based crypto exchange Swyftx says the next wave of stablecoin usage may come from the people and businesses already pushing against the limits of traditional payments: gig workers, freelancers, and AI-enabled solo operators. In a second-quarter industry report, the exchange links the expanding gig economy—particularly cross-border freelance work—to a potential jump in stablecoin settlement.

The report models a global gig and freelance payments market that could grow to $2.1 trillion by 2033, with AI-native workers representing a $775 billion portion of that total. Under Swyftx’s base-case assumptions, about $262 billion of that AI-native payment volume could be settled using stablecoins, implying adoption of roughly 33% for the modeled cohort.

Key takeaways

• Swyftx projects gig and freelance payments could reach $2.1 trillion by 2033, with AI-native workers accounting for $775 billion.
• In its base case, Swyftx estimates $262 billion of AI-native payment volume could be settled in stablecoins at an assumed ~33% adoption rate.
• The exchange points to solo entrepreneurs and small businesses as among the fastest-moving in AI adoption, creating a new customer segment sensitive to fees.
• Swyftx cites stablecoin transaction volumes rising to a record $1.79 trillion in June, reinforcing the idea that payment utility demand is real.
• It argues stablecoins can outperform cross-border rails on cost and speed, particularly for frequent, cross-border invoices.

Why gig work and AI-native labor are central to stablecoin demand

Swyftx’s thesis starts with who is paying and how often. The exchange argues that the smallest employers—firms with fewer than five employees—are adopting AI at a faster pace than larger organizations. That shift, it says, contributes to a rise in solo entrepreneurs who operate across borders and invoice frequently.

Because these workers often face payment amounts and settlement rhythms that standard banking and payment infrastructure are not optimized for, Swyftx frames stablecoins as a natural fit. It estimates there are currently about 6 million to 10 million solo workers globally, projecting growth to 17 million over the next decade.

Lead market analyst Pav Hundal told Cointelegraph that the appeal of stablecoins is increasingly tied to economics rather than just technology. “Adoption doesn’t happen just because the technology exists. It happens when the economics are compelling, and the rules are clear,” Hundal said, adding that both conditions are “falling into place.”

Stablecoin volumes are already signaling payment utility

The exchange’s predictions build on recent usage trends. Swyftx notes stablecoins have doubled in market capitalization over the past two years and reached a record $1.79 trillion in volume in June—figures Swyftx presents as evidence of growing payment demand.

The report also emphasizes that stablecoin activity is not only about end users; it can extend to the “settlement layer beneath” the payment routes. Swyftx suggests that if its modeled scenario develops, the infrastructure supporting settlements—such as over-the-counter liquidity, custody, and yield services used by platforms—could capture a new revenue stream.

In that framework, Swyftx estimates this could reach as much as $1.3 billion by 2033, assuming total transaction, liquidity, and custody costs of 0.5% across the relevant payments.

For context, earlier coverage from Cointelegraph highlighted the June record by noting stablecoin transaction volume at $1.79 trillion and linking it to broader payment-oriented narratives. Stablecoin transaction volume hits record $1.79T in June

Lower fees, faster settlement, and a more global customer base

In Swyftx’s account, traditional cross-border payment rails tend to impose three frictions that matter most to frequent freelancers: high fees, multi-day settlement windows, and uneven availability across jurisdictions. The exchange also asserts that many rails exclude users in more than 50 countries, which can limit the addressable freelance base.

To illustrate the potential advantage, Swyftx points to stablecoin transfers using Ethereum layer-2 networks as an example of how costs and time can improve. It claims such transfers can cut fees by 80% to 90%, saying an average freelancer could save about 86% per year in transfer fees under the cited example.

The report also ties the stablecoin payments outlook to the broader “agentic AI” narrative. Swyftx argues that AI agents—unlike human users—cannot easily obtain bank accounts. As a result, it says they will likely rely on crypto-based assets to execute payments.

That point aligns with earlier Cointelegraph reporting on the idea that autonomous AI agents with crypto access could become a meaningful payments driver. Autonomous AI agents with crypto access could become unstoppable

What investors should watch next

Swyftx’s projections are directionally clear—stablecoins may benefit as AI-native work increases and small operators demand cheaper, faster international settlement. The key uncertainty is adoption: the exchange’s base case assumes roughly one-third adoption of stablecoins within its modeled AI-native payment cohort by 2033. Traders and builders should watch whether stablecoin use keeps rising in real payment flows at the same pace suggested by recent volume records, and whether regulatory and on-ramps/off-ramps continue to make the “economics and rules” Hundal references more consistent across jurisdictions.

Fundstrat co-founder and BitMine chairman Tom Lee has told investors to watch the Ethereum-to-Bitcoin ratio for signs of a broader crypto recovery. 

In a July 13 post before his WebX 2026 appearance in Tokyo, Lee called ETH/BTC a “signal of a revival of crypto.” His statement reflects his market view rather than a guaranteed trading signal. WebX listed Lee for a keynote from 11:25 a.m. to 11:55 a.m. on the CRYL Stage.

The ratio shows how much Bitcoin one Ether can buy. A rising reading means Ethereum is gaining against Bitcoin, while a falling reading means Bitcoin is leading. ETH/BTC recently climbed toward 0.02858 after rebounding from an early June low near 0.026. 

Live prices later placed the ratio near 0.0282, showing that the pair remained close to its recent resistance area. Ether traded around $1,800 while Bitcoin changed hands near $63,700 at the time of checking.

ETH/BTC tests resistance after June recovery

The pair has formed higher lows since early June, but it still faces a ceiling around 0.0286. Traders have watched that level because several recovery attempts stalled there. A clean move above it could extend Ethereum’s relative rebound. Another rejection could return attention to support around 0.027 and the June floor near 0.026.

The wider trend remains mixed. ETH/BTC was still lower over the previous three months despite its July recovery. As crypto.news previously reported, Ether had fallen harder than Bitcoin through much of 2026, pushing the ratio toward multi-year lows. 

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Stronger Bitcoin ETF demand, weaker Ethereum fund flows and competition from other networks contributed to that gap. A stronger ratio would mark a change from that pattern, not a confirmed long-term reversal.

Bitcoin dominance and altcoin measures shift

Lee’s call also comes as Bitcoin’s share of the total crypto market has eased from recent highs. CoinGecko placed Bitcoin dominance near 56.2%, while other trackers showed readings that varied by methodology. A falling dominance rate can show that capital is moving toward Ether and other digital assets, although stablecoin values and different market baskets can change the result.

The Altcoin Season Index has also improved, with one reading near 58. That remains below the common 75 threshold used to define a full altcoin season. The rise shows that more large altcoins have started to outperform Bitcoin, but it does not confirm a market-wide shift. Several smaller tokens still trade well below their 2025 peaks. The measure tracks top assets over 90 days and excludes stablecoins and asset-backed tokens.

ETF demand and BitMine buying remain in focus

Fund flows give Ethereum a second test. As crypto.news reported, U.S. spot Ethereum ETFs returned to daily net inflows in early July after weeks of pressure. The funds took in about $14.9 million on July 1, led by BlackRock’s ETHA. 

One positive day did not erase the June outflows, so traders still need a steadier run of demand. Ethereum’s staking rate has also crossed 33%, reducing liquid supply available for sale.

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Corporate buying has added another source of support. BitMine said its Ethereum treasury reached 5.74 million ETH, equal to about 4.8% of supply. 

Lee has linked Ethereum’s outlook to stablecoin growth, tokenized assets and clearer U.S. rules. Those claims remain forward-looking. For now, ETH/BTC needs to hold its recovery and break resistance before Lee’s “revival” view gains stronger market confirmation.

China has proposed a series of judicial and procedural reforms to strengthen investigations, evidence handling and asset recovery in virtual currency money laundering cases, as prosecutors seek to close gaps in the country’s criminal enforcement framework.

According to an article published in the People’s Procuratorate Daily, China’s current legal framework faces three major obstacles when prosecuting virtual currency money laundering cases, including difficulties in determining criminal liability, collecting evidence, and recovering illicit assets.

The article, written by prosecutors from the Yuhu District People’s Procuratorate in Xiangtan, Hunan, and a law professor from Xiangtan University, said virtual currencies have improved transaction efficiency, but their decentralised structure, anonymity and cross-border nature have also made them increasingly attractive for laundering criminal proceeds.

Although China has established an anti-money laundering framework, the authors said inconsistencies between the revised Anti-Money Laundering Law and the Criminal Law have created enforcement challenges. While the updated AML law no longer limits predicate offences, Article 191 of the Criminal Law still applies only to seven specified upstream crimes, leaving many virtual currency laundering cases involving other offences to be prosecuted under the offence of concealing or disguising criminal proceeds instead.

The article warned that this has increasingly turned the latter offence into a catch-all provision and argued that judicial authorities should place more emphasis on identifying standalone laundering conduct during investigations.

Prosecutors call for stronger investigations and evidence rules

To address those issues, the authors proposed that China’s highest judicial authorities issue dedicated case-handling guidelines, publish additional guiding cases, and expand training in blockchain analysis technologies for investigators and prosecutors.

Investigators should also adopt a mandatory “dual investigation” approach by examining both the underlying offence and related laundering activity, the article said. It recommended preparing virtual currency fund flow reports during investigations and requiring prosecutors to assess whether separate money laundering charges should accompany predicate offences, including under China’s self-laundering provisions where appropriate.

The proposal also called on prosecutors to intervene earlier in complex investigations, examine the purpose behind fund transfers rather than relying solely on the type of upstream offence, and strengthen supervision when cases that qualify as money laundering are instead filed under other criminal provisions.

Evidence collection remains another major challenge because criminals increasingly use mixers, privacy coins, decentralised exchanges and cross-chain transfers to split and move funds across multiple jurisdictions, the authors said. Encrypted communications, destroyed data and limited cross-border cooperation further complicate investigations, while linking blockchain wallet addresses to real-world identities remains technically demanding.

To address those issues, the article proposed recognising publicly verifiable blockchain transaction records as self-authenticating electronic evidence when their hash values remain consistent. Blockchain analytics reports obtained from compliant analysis firms should also be accepted as evidence, subject to judicial review of the tools, methods and conclusions used in producing those reports.

The authors also suggested allowing courts to infer criminal intent under certain circumstances, including when suspects use mixers or privacy-focused cryptocurrencies to conceal transactions, rapidly dispose of large cryptocurrency holdings through abnormal trading methods or conduct frequent high-value transactions using anonymous wallets that cannot reasonably be linked to their identities.

Rather than requiring investigators to trace every transfer from origin to destination, the article argued that courts should be permitted to rely on indirect and circumstantial evidence where individual pieces of evidence corroborate each other and establish a complete chain of proof.

Authors propose national asset recovery framework

Asset recovery has presented another obstacle because China prohibits cryptocurrency circulation while authorities often lack compliant channels to dispose of seized virtual assets, the article said. The authors added that inconsistent procedures governing private key management, asset valuation and liquidation have created risks during criminal enforcement.

To resolve those issues, they proposed establishing a national mechanism to standardise the seizure, custody, valuation and disposal of confiscated virtual currencies. 

A centralised custody platform could manage seized assets, while disposal could take place through compliant channels such as designated auctions or negotiated transfers. They also recommended creating an expert committee to develop judicial valuation standards using blockchain data and pricing from major international exchanges.

Cross-border cooperation should also be strengthened through bilateral or multilateral judicial assistance agreements covering virtual currency crime, the authors said. 

They further proposed developing a blockchain-based judicial cooperation network that would allow participating jurisdictions to verify suspicious wallet addresses, asset freeze orders and other enforcement information while respecting national data sovereignty.

The recommendations build on China’s recent push to tighten oversight of crypto-related financial crime. In June, the People’s Bank of China said virtual currency laundering would remain an enforcement priority during the country’s next five-year anti-money laundering strategy, while noting that organised criminal groups increasingly rely on cryptocurrencies, underground banks and cross-border fund transfers to conceal illicit proceeds. 

The central bank also said authorities would continue strengthening international cooperation on investigations, intelligence sharing and asset recovery in cases involving cross-border financial crime.

Decentralized Autonomous Organizations (DAOs) were created to replace centralized decision-making with transparent, community-driven governance. Token holders can vote on proposals, allocate treasury funds, and shape the future of a protocol without relying on a single authority. While this model has transformed organizational governance, it also faces significant challenges: low voter participation, governance fatigue, information overload, and complex proposal evaluation.

Artificial intelligence (AI) is emerging as a powerful solution to these issues. Rather than replacing human governance, AI has the potential to enhance DAO operations by making governance more efficient, informed, and accessible. The combination of AI and blockchain could define the next generation of decentralized organizations.

The Current Challenges of DAO Governance

Many DAOs struggle with active participation. Thousands of token holders may technically have voting rights, but only a small percentage regularly engage in governance. Several factors contribute to this problem:

• Governance proposals are often highly technical.
• Reviewing multiple proposals requires significant time and expertise.
• Large token holders can dominate voting outcomes.
• Community members experience governance fatigue from constant voting.

As DAOs continue to grow, these inefficiencies become increasingly difficult to manage.

How AI Can Improve DAO Governance

1. Intelligent Proposal Summaries

AI can analyze lengthy governance proposals and generate concise, easy-to-understand summaries. This allows more community members to quickly understand the purpose, potential benefits, risks, and financial implications of each proposal before voting.

Instead of reading dozens of pages of technical documentation, users receive clear insights within minutes.

2. Data-Driven Governance Analysis

AI can process massive amounts of blockchain and ecosystem data to provide objective analysis.

For example, AI can evaluate:

• Treasury health
• Historical voting patterns
• Market conditions
• User activity
• Protocol revenue
• Smart contract usage

These insights help voters make decisions based on data rather than speculation or social media narratives.

3. Detecting Governance Risks

Machine learning models can identify unusual voting behavior that may indicate governance attacks or manipulation.

Examples include:

• Sudden accumulation of voting power
• Coordinated voting campaigns
• Suspicious wallet activity
• Flash-loan governance exploits

Early detection allows DAOs to respond before governance integrity is compromised.

4. Personalized Governance Assistants

AI-powered governance assistants could act as personal research tools for DAO members.

Users might ask:

• “How will this proposal affect protocol revenue?”
• “What similar proposals have been passed before?”
• “What are the risks if this proposal fails?”

The AI provides instant answers backed by blockchain data, making governance more accessible for both beginners and experienced participants.

5. Treasury Optimization

Managing multi-million-dollar DAO treasuries requires careful planning.

AI can assist by:

• Forecasting cash flow
• Modeling market scenarios
• Evaluating investment opportunities
• Recommending diversification strategies
• Monitoring treasury risk exposure

Importantly, AI should offer recommendations—not make final financial decisions. Human oversight remains essential.

AI Delegates and Autonomous Governance

One emerging concept is the AI governance delegate.

Instead of manually reviewing every proposal, token holders could assign their voting power to AI agents configured according to their preferences.

For example:

• Conservative investors prioritize treasury preservation.
• Builders prioritize developer funding.
• DeFi users favor liquidity incentives.
• Environmental advocates support sustainable initiatives.

The AI would analyze proposals and vote according to the delegated strategy while remaining transparent and accountable.

This could dramatically increase governance participation without removing community control.

Potential Risks

Despite its promise, AI introduces new governance challenges.

Bias in AI Models

AI systems are only as good as the data they are trained on. Biased or incomplete datasets may produce flawed recommendations.

Lack of Transparency

If AI recommendations are generated through opaque models, community members may struggle to understand why certain conclusions were reached.

Explainable AI will be critical for maintaining trust.

Centralization Risks

If a single AI provider becomes the primary governance assistant across multiple DAOs, decision-making could unintentionally become centralized.

Open-source AI models and decentralized AI infrastructure may help reduce this risk.

Over-Reliance on Automation

Governance is not purely mathematical. Community values, long-term vision, and ethical considerations require human judgment.

AI should augment—not replace—the collective wisdom of DAO participants.

The Future of AI-Powered DAOs

As AI agents become more capable, they may handle many operational tasks within DAOs, including:

• Drafting governance proposals
• Monitoring protocol performance
• Managing community discussions
• Identifying ecosystem opportunities
• Tracking treasury performance
• Simulating governance outcomes before votes occur

Meanwhile, blockchain ensures transparency, immutability, and verifiable execution of governance decisions.

This partnership between AI and decentralized infrastructure could create organizations that are faster, more efficient, and more resilient than traditional institutions.

Finale

AI-powered DAO governance represents a natural evolution of decentralized organizations. By simplifying proposal analysis, detecting governance threats, optimizing treasury management, and improving voter participation, AI can address many of the limitations that DAOs face today.

However, successful implementation will require transparency, accountability, and strong community oversight. The future of decentralized governance is unlikely to be fully automated—it will be a collaboration between human intelligence and artificial intelligence.

As Web3 continues to mature, DAOs that successfully integrate AI while preserving decentralization may become the blueprint for how digital organizations operate in the years ahead.

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Digital assets posted a third consecutive quarter of losses in Q2 2026, the longest losing streak since the 2022 bear market, as institutional capital rotated into AI equities and Bitcoin ETFs recorded their largest quarterly outflow since launch. Our report examines what drove the divergence, where structural adoption continued regardless, and what Q3 signals to watch.

Digital assets posted a third consecutive quarter of losses in Q2 2026, the longest losing streak since the 2022 bear market, as institutional capital rotated into AI equities and Bitcoin ETFs recorded their largest quarterly outflow since launch. Our report examines what drove the divergence, where structural adoption continued regardless, and what Q3 signals to watch.

Bitcoin price traded near $62,800 on Monday after slipping about 1.5% over 24 hours, according to crypto.news market data. 

The move kept the largest crypto above the $60,000 support area, even as the latest U.S.-Iran strikes triggered sharper moves across oil, stocks, bonds and gold. Ether traded near $1,779, XRP stood around $1.08 and Solana changed hands near $76.40. 

Crypto prices weakened, but they avoided the steep losses seen in several Asian equity markets. Bitcoin’s limited reaction contrasted with its sharp selloffs during earlier rounds of conflict this year.

Brent crude climbed more than 4% to about $79.31 a barrel as traders assessed threats to shipping through the Strait of Hormuz. Gold fell about 1.5% toward $4,060 as higher Treasury yields reduced demand for assets that pay no interest. 

Japan’s Nikkei dropped 2.2%, while South Korea’s KOSPI lost 7.6%. The two-year U.S. Treasury yield reached its highest level since early 2025 as markets raised expectations for tighter Federal Reserve policy.

U.S.-Iran attacks revive oil and inflation concerns

The latest market moves followed another exchange of attacks between the United States and Iran. U.S. Central Command said its forces struck dozens of Iranian military sites after Iran attacked a container ship near the Strait of Hormuz. 

Iran again claimed control over the waterway, while U.S. officials said the route remained open. Those statements remain disputed, and shipping data showed traffic through the strait stayed limited.

The route carried about one-fifth of global oil and liquefied natural gas flows before the war, making any disruption important for energy prices. Higher oil can raise transport and production costs, which may keep inflation elevated. 

Minutes from the Federal Reserve’s June meeting showed that a few officials saw a case for raising rates, although they supported holding the target range at 3.5% to 3.75%. Officials also listed Middle East conflict and energy prices among the risks that could keep inflation high.

Bitcoin ETF inflows provide support after eight weak weeks

U.S. spot Bitcoin ETFs recorded $197 million in net inflows from July 6 through July 10, ending eight straight weeks of withdrawals, according to SoSoValue data. The reversal followed $527 million in outflows during the shortened week ending July 2. 

Source: SoSoValue

BlackRock’s IBIT led the latest weekly inflows with about $292 million, while Grayscale’s smaller Bitcoin trust added roughly $95 million. GBTC recorded about $108 million in withdrawals, leaving demand uneven across individual funds.

As crypto.news previously reported, Bitcoin ETF selling had removed a key source of demand during the June decline. The return to weekly inflows supports the recovery from the $58,000 to $60,000 area, but the total remains modest compared with the money withdrawn during the previous eight weeks. 

Bitcoin also failed to hold above $65,000 after several tests, showing that fund inflows have not yet produced a clear breakout.

Bitcoin indicators improve but $65,000 remains key

Bitcoin’s recent structure remains sideways to slightly positive after the late-June bottom. The price has stayed above the main support zone near $60,000, while sellers continue to defend the area around $65,000. 

The relative strength index stands near 47, close to its moving average and below the neutral 50 level. That reading shows that buying pressure has improved from oversold conditions but has not taken control of the market.

The moving average convergence divergence indicator also shows an early recovery. Its histogram remains positive, and the MACD line sits above the signal line. Both lines remain below zero, which means the wider trend has not turned firmly positive. 

A daily close above $65,000 would improve the technical setup and open the way toward higher resistance. A fall below $60,000 would weaken the recovery and return attention to the June lows.

In addition, Crypto analyst Crypto Patel said exchange-to-exchange Bitcoin flows fell 91% in 30 days, from 1,800 BTC on June 14 to 166 BTC on July 12. He linked the decline to European users moving away from Binance after the exchange lost access to regulated services in the European Union under MiCA. 

He called the move “the Bitcoin signal almost everyone missed,” but the flow figures and the claimed direct link have not received independent confirmation.

Binance suspended several services for European Union users on July 1 after failing to secure a MiCA license before the deadline. The exchange kept withdrawals available and said it planned to seek authorization in another member state. 

Patel said flows above 800 to 1,000 BTC could show that European liquidity had settled on new venues. For now, Bitcoin remains inside its recent range while traders watch ETF demand, exchange liquidity, oil prices and the next Federal Reserve decision.