17 Market Transformation Drivers in Cryptocurrency in 2026: From Payments to Privacy Optimization

2026 will be a pivotal year for the crypto industry. From the emergence of more efficient stablecoin deposit/withdrawal channels to the rise of intelligent AI agents, from the privacy revolution to the development of prediction markets, upcoming changes will not only impact the financial markets but also reshape the entire way humans interact with technology and value. Below are 17 insightful perspectives from leading experts in the field.

I. THE PAYMENT REVOLUTION: WHEN STABLECOIN BECOMES THE FOUNDATION OF THE INTERNET

High-Quality Link Channels: The Solution to the “Digital Dollar” Problem

Last year, the estimated stablecoin transaction volume reached $46 trillion. This number says it all: Stablecoin transactions are now over 20 times larger than PayPal, nearly three times Visa, and rapidly approaching the volume of the US automated clearinghouse network (ACH) (. Record speed: under 1 second on blockchain, fees less than a penny.

But this is only half the game. The real challenge is how to connect this “digital dollar” with the payment systems that everyday users rely on — that is, efficient deposit/withdrawal gateways.

A new generation of startups is building these solutions:

• Some encryption technology applications enable private conversion of local currencies into digital dollars
• Others integrate regional networks, using QR codes and real-time transactions
• Others develop global wallets and card issuance platforms, allowing users to spend stablecoins directly at stores

As these channels mature, new scenarios will emerge: global freelancers receive instant payments, merchants accept international payments without bank accounts, apps can send value to any user worldwide without delay. Stablecoins will then no longer be niche financial tools but will become the underlying payment infrastructure of the Internet.

) Tokenization of Assets: “Crypto-First” Thinking Instead of Physical Replication

Currently, financial institutions are racing to bring traditional assets onto the blockchain — US stocks, commodities, indices. However, a problem arises: most tokenization projects merely “copy” real-world assets without leveraging the intrinsic advantages of blockchain technology.

Synthetic derivatives — especially perpetual contracts — offer a different opportunity: they provide deeper liquidity, easier deployment, and straightforward leverage mechanisms. Emerging market stocks are ideal candidates for “perpetualization” — options markets for many stocks already show superior volume.

The essence of this trend is: instead of just “tokenizing” assets, rethink from scratch with a crypto-centric perspective. By 2026, many real-world asset tokenization solutions will truly harness blockchain’s power.

Similarly for stablecoins: they entered mainstream markets in 2025, and by 2026, the field will shift from “simple issuance models” to “innovative models.” Instead of just holding highly liquid assets like “narrow banks,” stablecoins need to create direct debt instruments on blockchain — reducing infrastructure costs, increasing accessibility. Compliance challenges remain, but developers are addressing them step by step.

Upgrading Old Banking Systems with Stablecoins

Current banking software is almost “unrecognizable” to modern developers. Since the 1960s-70s, banks were early adopters of large systems; in the 1980s-90s, second-generation banking software emerged — Temenos’ GLOBUS, Infosys’ Finacle ###. But they have aged.

Today, core ledgers still run on mainframes, written in COBOL, processing in batches rather than via APIs. Most global assets are stored in these “decades-old ledgers.”

While proven, these systems are also major barriers to innovation. Adding real-time payment features can take months or years, creating enormous technical debt.

This is where stablecoins shine. Financial institutions do not need to overhaul legacy systems. Instead, they can build new products using stablecoins, tokenized deposits, tokenized bonds — serving new customers without risking system collapse. Stablecoins offer a “low-risk path to innovation” for financial organizations.

( The Internet Will Become the “Bank” of the Future

As AI agents become widespread, many commercial transactions will be completed automatically behind the scenes. This means the way value circulates must change accordingly.

In a world where systems operate based on “intent” rather than “step-by-step commands” — for example, an agent recognizes a need, fulfills obligations, and automatically makes payments — the value must circulate with “speed and freedom comparable to current information flows.”

Blockchain, smart contracts, and new protocols are key. Currently, smart contracts can settle global payments in seconds. By 2026, protocols like x402 will enable “programmable, self-responding payments”:

• Instant payments without approval
• Developers can embed payment rules, limits, and audits without fiat integration
• Prediction markets can automatically settle when events occur — updating rates, transactions, global profit payments within seconds

When value can circulate this freely, “payment processes” will no longer be standalone operational layers but will become “network behaviors.” Banks will integrate into the Internet infrastructure. Assets will become infrastructure. The Internet will no longer just support the financial system but will become the financial system itself.

) Democratizing Asset Management Services

Traditionally, personalized portfolio management services are only for “high-value clients” — tailored advice, high costs, complex operations.

But as assets are tokenized and blockchain enables “automatic balancing at low cost,” everyone will be able to access “active portfolio management” via AI. By 2025, traditional financial institutions have increased crypto allocations in recommended portfolios to 2%-5%. By 2026, platforms focused on “asset accumulation” — fintech companies like Revolut, Robinhood — will dominate this space.

DeFi tools like Morpho Vaults can automatically allocate assets into lending markets for “optimal yields,” providing “core profit components” for portfolios. Holding idle cash in stablecoins instead of fiat, via tokenized money market funds, expands profit opportunities. Ultimately, as bonds, stocks, and private assets are tokenized, rebalancing will be automatic without bank transfers.

II. THE AGE OF AI AGENTS: FROM IDENTITY RECOGNITION TO RESEARCH

From KYC to KYA: Verifying the “New Person”

The financial service industry now has “non-human identities” — AI agents — 96 times more than human staff, but these identities are still “ghosts” — they cannot connect to banking systems due to lack of “knowing your agent” ###KYA(.

Just as humans need credit scores to borrow, agents need “cryptographic signature certificates” linked to “authorized persons,” “conditions,” and “liability.” Without solving this, merchants will continue to block agents.

The industry has built KYC infrastructure over decades; solving KYA is now just a matter of months.

) AI Becomes a Truly “Research Assistant”

By 2025, AI models will handle abstract tasks like assigning research tasks to PhD students — sometimes returning “creative and accurate” results. AI will not only detect directly but also “solve Putnam problems” ###— the hardest university math exam.

What’s fascinating is which research support functions will be most valuable. I predict AI will create a “new research paradigm” — focusing on “relational inference,” “rapid reasoning from hypotheses.” These answers may be imprecise but can point in the right direction.

Ironically, this resembles “exploiting the illusion power of models”: when sufficiently intelligent, giving AI exploratory space can generate meaningless content but also lead to breakthroughs — similar to human creativity in a “nonlinear, goal-free state.”

Achieving this requires a “new AI workflow” — multi-layered models supporting researchers in evaluating “preliminary methods,” filtering useful info. Cryptography can provide solutions for “identity recognition and fair attribution” of each model’s contribution.

( The “Invisible Tax” of Open Networks

The rise of AI agents imposes an “invisible tax” on open networks. Agents source data from “ad-supported websites” to provide utility but avoid “income supporting content creation” )—ads, subscriptions(.

To prevent open networks from collapsing, technical + economic solutions are needed, such as “next-generation sponsored content,” “micro-credential systems,” or “new funding models.”

Current AI licensing agreements are essentially “unsustainable temporary solutions” — compensating content providers is often a small fraction of the revenue they lose. Open networks need a “new economic model.”

A key breakthrough in 2026 will be shifting from “static licensing” to “real-time, usage-based payments.” This requires “micro-payment systems on blockchain + precise attribution standards” — automatically rewarding “all contributors” involved in agent task completion.

III. THE PRIVACY REVOLUTION: BUILDING AN “NO ONE WATCHES” INTERNET

) Privacy: The Competitive Edge of Blockchain

Privacy is a crucial prerequisite for “global finance on-chain,” but almost all blockchains lack this feature. In fact, “privacy protection capability” can make a chain stand out among competitors.

More importantly, privacy can “trigger a chain-locking effect” called the “privacy network effect.” Public data moves easily between chains via bridges, but “cross-chain secret transfer” is difficult: when entering or leaving “private zones,” observers of the chain, mempool, or network traffic can identify identities.

Today, many “new chains” compete with near-zero fees ###on-chain space is unified(; blockchains with privacy features can build strong “network effects.” If a “public chain” lacks a thriving ecosystem or distribution advantage, users will migrate easily; but on private chains, users hesitate to move for fear of revealing identities. Since privacy is a hard requirement in most real-world scenarios, only a few private chains can dominate.

) Real-Time, Decentralized Messaging + Anti-Censorship

As the world prepares for the “quantum computing era,” messaging apps like Apple, Signal, WhatsApp have led the way. But the problem: they rely on “private servers operated by a single organization” — vulnerable to government or corporate “shutdowns, backdoors.”

“What does quantum-resistant encryption mean if servers can be shut down?” Messaging needs “open protocols with no trusted third parties” — no private servers, no single app, open source, using “state-of-the-art encryption technology.”

In open networks, no one can revoke everyone’s messaging rights: even if an app is shut down, 500 new versions will emerge; even if a node is shut down, economic incentives from blockchain will replace it immediately. When everyone “controls messages with keys,” apps can change, but users always control their messages. This is not just “quantum-resistant” but also “ownership” and “decentralization.”

“Data as a Service”: Global Data Protection Infrastructure

Behind every model, agent, and automation system, data is essential. But most current data transmission channels lack transparency, are easily tampered with, and cannot be audited.

This may not matter much for consumer apps, but for finance, healthcare, it’s a major barrier — enterprises must protect sensitive data privacy but also need compliance, autonomy, and global interoperability.

Solution: “access control for data” — Who controls the data? How is data circulated? Who has access?

Today, if organizations want to protect data confidentiality, they rely on centralized services or custom-built systems — costly, time-consuming. We need “privacy as a service”: using new tech to set programmable access rules for raw data, client-side encryption, decentralized key management — defining who can decrypt what data, for how long, with all rules enforced on-chain. Result: data confidentiality becomes a public infrastructure of the Internet.

( From “Code is Law” to “Violations are Law”

Recently, many DeFi hacks involve protocols that have stood the test of time. This shows: security practices still mainly rely on “experience” and “case-by-case handling.”

To advance DeFi security maturity, two shifts are needed:

• From “patching vulnerabilities” to “designing for attribute guarantees”
• From “maximal protection” to “principled system protection”

Static phase )before deployment###: prove the system’s “global immutability” — that is, core rules are always followed. Many AI tools now support developers, greatly reducing manual verification.

Dynamic phase (after deployment): turn “immutable rules” into real-time protective barriers. These barriers will be encoded as “runtime assertions” — any violating transaction is automatically rejected.

Result: instead of assuming “all vulnerabilities are patched,” we use code to enforce core security properties. Nearly all hacks so far have triggered such checks; widespread deployment will prevent malicious attacks.

IV. PRACTICAL APPLICATIONS: FROM PREDICTION TO “STAKING COMMUNICATION”

Prediction Markets: Expanding Scope, Increasing Intelligence

Prediction markets are now mainstream. In 2026, they will continue to grow in scale, scope, and intelligence, but also face new challenges.

Expanding contract volume: not only “major elections, geopolitical events,” but also small-field results, complex intersection events. As new contracts generate info integrated into news ecosystems, society must balance the value of this information.

New consensus mechanisms: centralized payments remain important, but controversial cases — like “Zelensky lawsuit market” ###— reveal limitations. Oracle LLMs can assist in verifying the factuality of disputed outcomes.

AI trading agents: can gather diverse signals for short-term advantage, help understand the world, predict future trends. These agents are not just “analysts” but also help identify key factors influencing complex social events.

Relationship with opinion polls: Do prediction markets replace surveys? No. Instead, they can enhance survey quality. New tech — AI optimizes survey experience, crypto verifies respondents are real — will enable these ecosystems to grow side by side.

“Staking Media”: When News Becomes a Right

Traditional media models emphasize “objectivity,” but their flaws are obvious. The Internet empowers everyone to speak; more and more professionals, practitioners, and creators directly communicate their views to the public — their perspectives reflect “self-interest.”

Ironically: the public respects them not “despite their conflicts of interest,” but “because of their conflicts.” The new thing is not social media’s rise but “the emergence of crypto tools” — enabling everyone to make “public, verifiable commitments.”

As AI reduces content creation costs, any “identity” can generate content from any perspective — real or fake. Relying solely on statements is no longer convincing. Instead:

• Commentators: can prove “walk the talk” — betting money on their opinions
• Podcast hosts: lock tokens, prove they won’t flip or pump-and-dump
• Analysts: link predictions to “public payment markets,” creating verifiable track records

This is the embryonic form of “staking media”: this type of media not only acknowledges “conflicts of interest” but also provides evidence. Credibility comes not from “pretending to be neutral” but from “public, transparent, verifiable benefit commitments.”

Staking media does not replace other forms but complements them. It signals: no more “trust me, I am neutral,” nor “trust me unconditionally,” but “here is the risk I am willing to bear, and here is how you can verify my claims.”

V. PLATFORM TECHNOLOGIES AND DEVELOPMENT DIRECTIONS

( SNARKs: From “Blockchain-Only” to “Comprehensive”

SNARKs — cryptographic proofs verifying computation results without re-execution — have been mostly used in blockchain due to “high costs”: generating proofs can be a million times more expensive than direct computation.

But this is about to change. By 2026, zkVM costs will drop about 10,000-fold, with memory only a few hundred MB — fast enough to run on phones. The 10,000x threshold is critical because high-end GPUs can process parallel tasks roughly 10,000 times faster than laptop CPUs.

By late 2026, a single GPU could “generate proofs of CPU execution in real time,” realizing the vision: “cloud computing can be verified.” If you need to run CPU workloads on the cloud, in the future, paying a reasonable extra fee will give you “cryptographic proof of correctness” — no code changes needed.

) Trading Business: “Transit Hub” Not “Destination”

Today, almost all successful crypto companies have shifted to trading. But what if “all crypto companies become trading platforms”? What will happen in the end?

Many firms racing in the same lane not only disperse user attention but also lead to “few monopolists, most eliminated.” This means that those rushing into trading too quickly may miss the chance to build “more competitive, sustainable business models.”

Founders motivated by quick profits understand this, but “pursuing short-term market fit” has costs. This is especially true in crypto: token features and speculative incentives often tempt founders to pursue “immediate gratification” while “seeking market fit” — like a “gummy bear experiment” (testing delayed gratification).

Trading itself is not problematic — it’s an essential market function — but it should not be the “ultimate goal.” Founders focused on “core product-market fit” will ultimately be the winners.

Legal Frameworks: When “Standards” Align with “Technology”

Over the past decade, the biggest obstacle to building blockchains in the US has been “legal uncertainty.” The scope of securities law has expanded, and enforcement standards are inconsistent, forcing founders to “design for enterprise, not for networks.”

“Avoid legal risk” replaces “product strategy”; engineers give way to lawyers. The result: founders are advised to avoid transparency; token distribution becomes arbitrary; governance is superficial; token design intentionally “avoids economic value.”

Worse, projects “ignoring rules and operating in gray areas” often grow faster than “honest, compliant” builders. But today, the US government has never been closer to passing a “Crypto Market Structure Act” as it is now.

If passed in 2026, the law will encourage companies to increase transparency, establish clear standards, replacing “ad hoc enforcement” with “structured, compliant fundraising, token issuance, and decentralized governance.”

Previously, the GENIUS Act was passed, leading to a surge in stablecoin issuance. The crypto market structure law will bring even greater change — focusing on “blockchain networks.” This management approach will help blockchain networks “operate truly as a network”: open, autonomous, composable, trustworthy, and decentralized.

Conclusion: 2026 as a Turning Point

These 17 trends are interconnected — they form a big picture: the shift from “digital currency” to “Internet payment layer”; from “niche financial tools” to “public infrastructure”; from “encryption and security” to “ownership and decentralization.”

2026 will be the era where “technology meets policy,” where “innovation meets regulation,” and where “big ideas” finally become reality. The question is not “will this happen,” but “what will we build when it does.”