AI Agent Summit 2026 in Singapore brought AI-agent infrastructure, machine payments and tokenized real-world assets into the same discussion, with organizers reporting more than 1,500 online registrations and over 500 in-person attendees. Hosted by Noos and co-hosted by Techub News, the event focused on the practical systems needed for software agents to move beyond answering prompts and begin carrying out tasks across decentralized networks.
The summit’s agenda placed particular emphasis on settlement: how autonomous software could pay for computing, access services, manage wallets or interact with tokenized assets without relying on a person to approve every step. That remains one of the harder commercial and technical questions facing AI-agent projects, especially where an automated system is permitted to control funds or trigger transactions.
Noos presented itself as a decentralized computing and economic settlement network designed to connect AI skills, agents and globally distributed computing resources. The organization said its network includes more than 4,000 distributed computing nodes globally and a catalog containing more than 10,000 AI Skills, a term generally used for specialized functions that agents can call upon to complete particular jobs.
B.AI introduced as strategic settlement partner
B.AI was introduced at the opening of the event as a strategic partner focused on what it described as a smart global settlement layer. The platform was presented as combining stablecoin payments, Web3 wallet integration and request-based routing across AI models.
That proposed combination addresses a growing design challenge for AI-agent applications. A task-performing agent may need to select a model, purchase computing resources, pay for data or services, and deliver a result. Each of those steps can involve different providers and payment systems. A settlement layer would seek to connect those actions through a programmable transaction flow.
The model also raises questions that the industry has yet to resolve consistently: who sets a spending limit for an agent, who is accountable if a transaction is executed incorrectly, and what protections apply when an agent interacts with third-party tools or tokenized assets. Those questions appeared repeatedly in the summit’s panel program.
The event included keynote speakers identified as Leclerc, Varghese, Jack, Kevin, Nicole and Wilson. Their presentations covered decentralized infrastructure, digital identity and domain-name assets, project development, robotics combined with AI, and developer-oriented key management.
Key management services are particularly relevant to autonomous systems because they determine how private keys — the credentials used to authorize blockchain transactions — are stored and accessed. Giving software agents transaction authority without exposing keys or enabling uncontrolled transfers remains a central security requirement for agent-led financial activity.
Panels examine autonomous execution and tokenized assets
The first panel, moderated by Ye and featuring David, Leclerc, Chan and Zhao, examined the transition from chat-based assistants to agents able to execute multistep tasks. Speakers discussed technical limits on autonomous operation and the design of token incentives for agents that can hold assets or generate revenue.
The difference is operational rather than cosmetic. A conversational assistant can provide an answer or recommendation, while an agent may be designed to take action after interpreting an instruction: compare options, call external software tools, send a payment request or complete a workflow. Each added capability increases the value of automation but also expands the potential impact of mistakes, faulty instructions and compromised permissions.
Token incentives were discussed in that context as a way to reward network participants who provide computing capacity, validation or specialized services. Designing those systems is difficult. Rewards need to encourage useful work and reliable infrastructure without creating incentives for artificial activity, weak verification or concentration among a small group of operators.
The second panel, moderated by Stella and featuring Brian, Benjamin and Cai, turned to real-world assets, or RWAs. The discussion moved beyond the process of placing records of assets on a blockchain and toward the harder task of ensuring that an on-chain token has a trusted connection to the asset it represents.
That distinction is crucial for any agent-led RWA system. A token can be transferred automatically on a blockchain, but the underlying asset may involve legal ownership, custody arrangements, valuation, payment obligations or regulatory restrictions. Automated execution could make such transactions faster, but it would also require clear rules for failures, disputes and responsibility.
Panelists also considered the barriers to scaling AI-agent-led RWA operations, including technology readiness, regulatory treatment and market trust. These issues limit how far automation can go in asset markets, particularly where transactions have legal consequences outside the blockchain environment.
Infrastructure takes priority over token speculation
The summit’s strongest theme was less about a single AI token or product than the infrastructure that would allow agents to operate economically: computing networks, identity systems, key controls, wallet connections and settlement mechanisms.
Noos listed B.AI, Pawa Robotics, Fortune, Unikey, BTSE, AI PET, Savior of Health and DN.com as strategic partners. The range of named organizations reflected the event’s attempt to connect AI-agent development with robotics, digital identity, payments and Web3 services rather than treating those areas as separate markets.
A networking session followed the panels, allowing attendees to continue discussions on decentralized infrastructure and tokenized assets. The event’s program suggested that the next phase of AI-agent development will be judged less by an agent’s ability to produce fluent responses and more by whether it can complete useful tasks securely, pay for the resources it consumes, and operate within enforceable limits.
Explore how tokenized RWA assets and AI-driven finance are reshaping settlement, trading, and automated execution across global markets.
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