17 Key Possibilities That Will Reshape the Crypto Industry in 2026

The cryptocurrency industry is preparing for the next year, during which stablecoins, artificial intelligence, and decentralization mechanisms will undergo profound changes. Below is an in-depth analysis of new trends across the sector and their potential future impact.

Payment and Financial Infrastructure Certification

Last year, transactions worth 46 trillion dollars were conducted via stablecoins, equivalent to 20 times PayPal and 3 times Visa. But the main current issue is how to connect stablecoins with the daily financial system.

New generation startups are trying to fill this gap. They are linking stablecoins with neighboring payment networks and local currencies. Some companies are simplifying the process of replacing local accounts with digital dollars, others are providing real-time payments through bank intermediaries, and yet others are building decentralized payment platforms.

The development of these cash flow channels is transforming stablecoins into a core part of the payment infrastructure. Workers will be able to receive cross-border wages, traders will conduct global trades without bank accounts, and programmable payments will settle in seconds.

RWA and the Crypto-Native Asset Model

Traditional assets are beginning to be tokenized on the chain, but most are only tokenized in form, avoiding real crypto-native value. Perpetual contracts provide deeper liquidity among synthetic products and offer simplified leverage mechanisms.

A new type of tokenization model will emerge. Stablecoins will become the main flow in 2025-2026, with more stablecoins being “native issued,” not just tokenized.

However, the historical problem remains: like shell banks, stablecoins hold strictly liquid assets, which cannot support a decentralized economy in the long run. The new model involves entering through debt assets: they should start on-chain, not off-chain, then be tokenized. This reduces credit management costs and expands global access.

Digital Reorganization of Bank Accounts and Settlements

The automation of bank system schedules dates back to the 1960s-70s. Mainframes written in COBOL still handle many global assets, hindering innovation.

Stablecoins and tokenized assets have enabled institutions to create new products without rewriting old systems. This provides a quick path for innovation.

Artificial Intelligence Agents and the “Know Your Agent” (KYA) Standards

In the agent economy, the main limitation is gradually shifting from intellectual level to identification. In financial systems, the number of “non-human identifications” exceeds human ones by 96 times, yet they are still not transparent identifications.

The essential requirement: KYA - know your agent. Agents require (AI systems) cryptographic proofs, linking the agent to an authorized subject, operational constraints, and responsibilities. Until this mechanism is complete, traders will block agents at the firewall level.

Current KYC infrastructure must resolve the KYA issue within a few months.

Artificial Intelligence Changing Research

Mathematicians have begun using AI models in research. Models that were incomprehensible in January started independently finding new and correct answers by November, even solving Putnam math competition problems.

This created a “multi-agent within agent” research model: one model evaluates ideas, others extract real values. It is used in writing articles, patent searches, art creation, and security analysis.

But this system requires good interoperability between models and precise compensation for each model’s contribution. Cryptography can help solve these two problems.

Hidden Taxation on Open Networks

The growth of AI agents is loading hidden taxes onto open networks. AI agents gather data from ad-based websites and create user convenience, but they bypass revenue streams that support content creators, such as (advertising and subscriptions) systems.

New sponsorship schemes, attribution systems, or innovative financing models are needed. Current AI licensing protocols do not fully address the problem.

Next year’s main change: shifting from static permission to real-time, usage-based compensation mechanisms. Through blockchain-based micro-payments and precise consistency standards, we will automatically reward each subject that successfully completes a task, all on-chain.

Privacy - Shell Main Controller

Privacy is crucial for the global financial chain, but many current blockchains lack it. Privacy increases the exit costs between chains and creates a “network effect lock-in.”

Moving from open to private chains is easy, but bridging secrets is very difficult. During transfer between private and open chains, monitored blockchains can identify individuals. This creates a winner-takes-all situation: since privacy is vital in most real applications, a few private chains could control the entire crypto market.

Quantum-Resistant, Decentralized Messaging

As the world prepares for the quantum era, major communication protocols (iMessage, Signal, WhatsApp) are advancing cryptography. But the problem: all apps rely on servers controlled by a single organization, which can be shut down by governments or compelled to hand over sensitive data.

A smart solution: “trust me” is replaced with “you don’t need to trust me.” Communication does not require a trusted intermediary. Messaging protocols need open standards. If the network is decentralized, shutting down a single app will produce 500 new versions the next day.

If people own their data via private keys, everything changes. This is not only quantum-resistant protection but also about ownership and decentralization.

Privacy - Service as a Product

Behind every model, agent, and automated process, data is stored. But today, most data pipelines are not transparent, mutable, and difficult to audit. Many fields, such as (finance, medicine), require privacy protection.

In the “privacy as a service” model: rules for access to programmable native data, encryption on the client side, and decentralized key management allow precise control over who, under what conditions, during what time, can decrypt which data.

With verifiable data systems, privacy becomes a core part of internet infrastructure, not just a patch at the application layer.

Transition from “Code Law” to “Rules Law”

Recent DeFi hacking incidents have shown that security is still based on individual cases and experience. As maturity progresses, DeFi security should move from pattern-based design to the level of formal verification, from “best practices” to “principled” approaches.

Static deployment: testing, auditing, formal verification systematically check global invariants. AI proof tools simplify writing technical specifications and invariant hypotheses.

In the dynamic, post-deployment phase: runtime monitoring and enforcement turn invariants into dynamic barriers. Each transaction is verified as a runtime assertion.

As a result: “code law” becomes “rules law.” New attack methods must also meet security requirements; otherwise, other attacks become insignificant or very difficult.

Forecast Markets - Larger, Broader, Smarter

Forecast markets are becoming mainstream, integrating with stablecoins and AI. More contracts are being registered: key elections, geopolitical events, complex cross-events—all in real-time coefficients.

This new data transforms forecast markets into part of the news ecosystem, but raises questions: how to evaluate data value, how to optimize design to make it more transparent and auditable?

New consensus methods are needed to verify contract authenticity. Centralized platforms’ arbitration has been important but revealed limitations in contentious cases. New decentralized governance mechanisms and large language model oracles will help determine the truth.

Creation of “Betting Media”

The traditional media model has shown cracks in objectivity. The internet has given everyone a voice. But the problem: AI generates endless content cheaply, allowing anyone to claim anything from any perspective.

Tokenized assets, programmable lock-ups, forecast markets, and on-chain history create a foundation for trust. Commentators can prove they risked their opinion and money simultaneously.

This is “betting media”: media that not only accepts the idea of “interest” but also proves it. Credibility depends not on neutrality but on how much risk you are willing to take.

Verifiable Cloud Computing - SNARKs and zkVM Revolution

For years, SNARKs (cryptographic proof technology) was limited in blockchain, with very high costs. But by 2026, zkVM prover costs will drop ten thousand times, memory usage will be a few hundred megabytes, making it feasible to run on phones.

Ten thousand times is not critical because GPU parallel throughput is ten thousand times higher than a laptop CPU. By the end of 2026, a single GPU will be able to prove real-time CPU computations.

This opens the door to verifiable cloud computing. If you run computations in the cloud, you can obtain a cheap cryptographic proof of correctness, without changing your code.

Balancing Financial Stability and Network Building

Today, almost every advanced crypto company is moving into trading. But if every company becomes a trader, most participants will lose. This issue is especially urgent as founders seek rapid product-market fit around tokens and speculation.

But it’s not the end of trading, it’s the end of the fat. Founders focusing on product-market fit in the “product” part may ultimately lose.

Legal-Technical Alignment and Blockchain Potential

Over the past decade, the biggest obstacle to building in the US was legal uncertainty. Securities laws were misused, forcing founders into compliance for regular companies.

Over time, companies shifted from product strategy to reducing legal risks. This interpreted transparency, made token issuance voluntary, and governance only for guidance. Token design avoided explicit economic value.

But the crypto industry’s regulation is closer than ever. Once rules are adopted, for example, (stablecoin law), transparency will be encouraged, clear standards established, and explicit pathways for financing and decentralization created.

Once the GENIUS law is passed, stablecoins showed explosive growth. Legislation around the crypto market structure will bring further significant changes—these are all related to the network ecosystem. Regulation will enable blockchains to operate as true networks—open, autonomous, composable, and decentralized.

Next year, the importance of these 17 sectors will increase, accelerating the industry’s steps toward becoming the core infrastructure of the digital economy.