AI agents were deployed at the Toronto trade fair.

(Image caption) The Toronto Technology Conference brings together participants in AI, Web3 and digital assets, with the industry focus shifting towards more actionable intelligent business systems.

From July 21st to 22nd, the Blockchain Futurist Conference will appear in GFM's coverage for the fourth time. In the past three articles, we've accompanied this conference through its place in the industry landscape, the unfolding of the Web3 ecosystem, and how it's gradually weaving a network of international collaboration. This time, as a strategic media partner of the conference, GFM wants to discuss a more pressing question: where will the Web3 and RWA market go as artificial intelligence begins to touch payments, transactions, identity, data, and asset management?

This year's AI Futurist Conference is no longer just a side event, but rather a crucial part of the entire agenda. Over two days, autonomous intelligent agents, AI business, data ownership, robotics, virtual reality, financial institutions, digital assets, and quantum blockchain took turns on stage. While the topics seemed separate, they were all converging in the same direction: AI handles understanding and execution, Web3 provides a toolkit for identity, wallets, contracts, and settlement, and RWA gradually integrates real-world assets and returns into this system.

The first to feel the pressure of this change may not be technology companies. Businesses need to rethink their transaction processes, investors face unfamiliar asset entry points, financial institutions need to redesign authorization and risk control rules, and even ordinary users have to stop and think about how much data and control they have given up.

AI agents are getting closer to control of funds.

The Agentic Day Summit and the Agentic Commerce Bootcamp are two of the most noteworthy events on this year's agenda.

Agentic AI refers to artificial intelligence systems with a certain degree of autonomous execution capability. It can break down a goal into a series of tasks, invoke tools, compare conditions, make choices, and complete the task within its authorized scope. Once such a system is connected to digital wallets, smart contracts, and stablecoins, it gains the ability to participate in payments, procurement, investment, and asset management.

In e-commerce scenarios, AI agents can help users find products, compare prices, negotiate terms, and complete payments. Once it enters the RWA (Real Estate Investment and Property) market, its actions will become more complex: analyzing real estate income rights, private credit, accounts receivable, energy projects, or infrastructure assets, and personally executing subscriptions, exits, or asset allocations based on yield, term, collateral arrangements, and risk conditions.

On the other hand, this convenience comes with an unavoidable question: how much money can this agent actually use?

Investors need to figure out whether the agent only provides advice or can actually place orders on their behalf; whether there are restrictions on the amount, term, and asset type; whether the agent will stop and wait for confirmation when encountering high-risk operations; and whether the responsibility for any errors should fall on the platform, the developer, the user, or the asset manager.

Without clear answers to these questions, AI agents will find it difficult to truly enter regulated asset markets. They will remain in an awkward position—technically capable of taking action, but institutionally no one is willing to hand them the keys.

Identity and authorization will become the core of the system.

The main stage of the conference will discuss trust, data, and ownership in the era of autonomous AI. This is especially important for RWA, because every RWA product ultimately revolves around legal rights, asset control, and liability.

Traditional financial systems are accustomed to clearly defining roles such as account holder, order giver, and liability in case of problems. With the addition of AI agents, a new executor emerges in the transaction chain. It may represent an individual or a company; it may strictly adhere to the rules or make its own decisions in complex situations.

Future RWA platforms need to clearly distinguish between the three roles: asset owner, licensor, and executive agent. If the permissions of these three roles are blurred, it will become impossible to investigate unauthorized operations, data misuse, erroneous transactions, and to hold anyone accountable.

Decentralized identities and verifiable credentials might offer some answers. Platforms could assign verifiable permissions to AI agents: limiting transaction amounts, restricting asset types, setting validity periods, and requiring human approval for significant transactions. The authorization process, operation records, and revocation procedures should also be fully documented for future auditing and accountability.

For investors, these system designs are more important than how smart the model is. A reliable system should allow users to clearly see what the agent can do, and should also allow users to stop or revoke permissions at any time.

(Image caption) After real estate, trade assets and other entity rights are connected to the blockchain, legal ownership, data verification and liquidity arrangements become the foundation of RWA's value.

Data quality determines whether AI's judgments are valuable.

AI's judgment is ultimately developed through data. The underlying value of RWA products is mostly buried off-chain, and it's difficult to piece together a reliable picture based solely on token prices and on-chain transaction records.

The value of a real estate project lies in its rental income, vacancy rate, maintenance expenses, taxes, insurance, mortgages, and management condition. The value of private credit lies in the borrower's cash flow, collateral, repayment history, and contractual terms. Energy and infrastructure projects also require continuous monitoring of operational efficiency, cash flow, and contract fulfillment.

If AI only reads on-chain prices, it can easily mistake fluctuations in liquidity for changes in the asset's intrinsic value. Truly meaningful analysis requires a continuous influx of reliable off-chain data.

Who provides the data, how often it is updated, whether it has been verified by a third party, and how erroneous data is corrected—the answers to these questions directly determine the reliability of the AI's output. If the RWA platform cannot answer these questions, even the most powerful model can only make guesses based on incomplete data.

Data ownership should not be taken lightly either. While users authorizing AI to access their wallets, investment portfolios, spending records, and identity information can lead to more accurate services, the platform's use of this data must be clearly defined in its rules. Whether the data will be used to train models, provided to third parties, or completely deleted after authorization is revoked—these should all be unambiguous clauses in the user agreement. Convenience should not come at the cost of relinquishing control of data.

The RWA market is growing a layer of intelligent services.

Many RWA platforms are currently focusing their efforts on the fundamentals: asset issuance, legal structure, token design, and on-chain circulation. The addition of AI may allow for the growth of a new layer of services on top of this foundation.

This layer can handle asset screening, risk comparison, cash flow forecasting, compliance review, portfolio management, and investor education. Institutional investors can handle a large number of non-standardized assets more efficiently, and ordinary investors also have the opportunity to access research tools that were previously only available to professional institutions.

Risks don't disappear just because information is compressed. An asset document that is dozens of pages long can be condensed into a few paragraphs by AI, but the content that truly determines the investment outcome is often hidden in the details such as redemption conditions, order of repayment, management fees, related-party transactions, and default handling clauses.

Mature AI-powered financial services cannot simply provide conclusions; they must also present the basis for those conclusions. Users should be able to access specific contracts, data sources, and risk clauses. Every automated operation should also leave complete authorization and audit records. This will ultimately become the standard for measuring the true reliability of an RWA platform.

(Image caption) AI agents are beginning to participate in asset analysis, risk assessment, and transaction execution. Investors need to understand the boundaries of their authorization and their responsibility mechanisms.

Virtual reality is changing the way due diligence is done.

This year's conference also featured robots and immersive virtual reality experiences. While these may seem more like demonstrations, they could subtly change RWA's due diligence methods.

Real estate, hotels, mining, energy facilities, agricultural projects, and artworks have traditionally relied primarily on on-site inspections, photographs, videos, and written reports for verification. Virtual reality can provide a more complete remote viewing environment, and robots and sensing devices can continuously collect operational data.

The utilization rate of logistics warehouses, the operational efficiency of energy equipment, and the production status of agricultural projects can all be continuously recorded and then processed and analyzed by AI. If this data is independently verified and linked to on-chain equity, investors will have much more confidence in their understanding of the underlying assets.

However, the more realistic the visuals, the more cautious you need to be. Data can be embellished, and scenes can be meticulously designed. Immersive technology only has true investment value when coupled with legal disclosure, independent verification, and continuous monitoring; otherwise, it's merely a more sophisticated presentation.

What financial institutions care about most is controllability and accountability.

The conference established a "House of Intelligence," bringing together finance, artificial intelligence, Web3, and digital assets in the same discussion space. This demonstrates that financial institutions' focus on these technologies has progressed to the point of practical deployment.

Financial institutions are willing to use AI to improve risk management and data processing efficiency, and they also value the cost improvements brought by tokenized assets, stablecoins, and on-chain settlement. However, they find it difficult to swallow a system with ambiguous permissions, unclear data sources, and untraceable responsibility.

For institutions to enter the RWA market, they need comprehensive legal rights, asset custody, identity verification, transaction restrictions, and auditing mechanisms. AI agents must have clearly defined authorization boundaries, and on-chain transactions must align with real-world legal systems.

Such requirements will push the RWA market further towards a crossroads. Some platforms will continue to serve native crypto users, using speed, liquidity, and openness as selling points; others will build stricter identity, custody, disclosure, and risk control systems to attract banks, funds, and corporate clients. The latter path is slower, but it is closer to the conditions truly needed for large-scale capital.

Quantum security is beginning to enter the realm of long-term assets.

The conference also introduced the concepts of quantum blockchain and official wallets, demonstrating that AI, blockchain, and quantum technologies have been placed within the same security framework for discussion.

Quantum computing has not yet entered the everyday financial market on a large scale, but its potential impact on cryptographic systems is already worth considering for long-term asset projects. Blockchain relies on cryptography to protect private keys and transaction security. Once the existing algorithm is broken in the future, asset migration, key updates, and protocol upgrades will turn from theoretical problems into real-world troubles.

RWA products typically have long terms. Real estate, infrastructure, and private lending often extend for years, so platforms can't just focus on the immediate security environment. Whether smart contracts can be upgraded, who has the authority to initiate upgrades, and how assets will be migrated—these questions will eventually appear on institutional investors' due diligence lists. Quantum technology is still somewhat forward-looking, but for long-term assets, it's necessary to allow for adjustments in advance.

(Image caption) The Toronto AI Futurists Conference witnesses the convergence of artificial intelligence, industry, and the global innovation ecosystem.

What can ordinary investors gain from all of this?

The most noticeable change for ordinary users after the integration of AI and RWA is the improved efficiency of information processing. AI can help read white papers, contracts, and asset reports, outlining the yield, term, fees, and main risks step by step.

This could lower the barriers to entry for services. Research, monitoring, and asset allocation tools that were previously only affordable for large institutions may gradually become available in the digital wallets and trading platforms of ordinary people.

Cross-border asset allocation will also be much more convenient. AI agents, combined with stablecoins and on-chain settlement, can save some operational steps, but tax, securities, and identity regulations still stand in place. Investors cannot ignore their legal responsibilities just because the process has become simpler.

One more thing worth mentioning: users may gradually relinquish their independent judgment. After AI reads information, selects products, and completes transactions for users, model biases, platform profit calculations, and erroneous data may all be hidden behind a seemingly simple interface. Trustworthy AI financial services should always leave users with a loophole—the right to human confirmation, revocation of authorization, review of supporting documentation, and the right to stop the transaction at any time; none of these should be lacking.

Why GFM continues to follow this conference

The Blockchain Futurist Conference has been held for several years, and the 2026 edition clearly focuses on AI agents, data rights, financial institutions, digital assets, and real-world applications. This arrangement indicates that the Web3 industry is facing stricter regulatory requirements.

As a strategic media partner, GFM's focus on this conference goes beyond just the event's scale and guest list. The real significance behind the four consecutive reports lies in documenting how industry language is gradually changing and identifying which concepts are truly entering the business and asset markets, rather than remaining on the conference floor.

One of the most noteworthy changes this year is that AI is beginning to move closer to transaction rights and asset control. Web3 provides programmable identities, wallets, and settlement tools, and RWA is bringing these capabilities into the world of real estate, credit, energy, and other physical assets.

The competition that follows will focus on several more institutional issues: whether asset owners can retain control, the reliability of data, whether the actions of agents can be tracked, and whether responsibilities can be clearly defined.

AI can improve efficiency, but it can also amplify errors and conflicts of interest. The truly noteworthy aspect of this conference is that it has brought these unanswered questions to the forefront for industry, institutions, and investors.