AI and tokenisation are changing parts of financial infrastructure, not replacing financial markets wholesale. AI is being applied to tasks such as fraud detection, compliance support and cyber defence; tokenisation can represent money and assets on programmable platforms that coordinate information, transfers and settlement. Their potential efficiencies depend on legal clarity, reliable settlement assets, sound governance and connections to existing systems—and large-scale integrated adoption is not yet established.
What AI and tokenisation mean in financial infrastructure
Tokenisation represents assets or money on a programmable platform
The BIS Committee on Payments and Market Infrastructures (CPMI) describes tokenisation as generating and recording digital representations of traditional assets on a programmable platform. In financial infrastructure, the represented items can include money and securities, alongside transaction instructions and supporting information. A tokenised arrangement may cover part of an asset’s lifecycle and provide platform-based intermediation.
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The digital representation does not settle the underlying legal questions by itself. A design still needs to establish what claim the token represents, who controls custody and the authoritative record, how redemption works, and when a transfer is legally final. Regulatory responsibility and procedures for correcting errors or resolving disputes also remain matters of design.
AI is a set of tools applied to institutional work
In this context, AI is not one financial-market system. Central-bank material describes applications including transaction-network analysis for fraud detection, support for anti-money-laundering and know-your-customer work, compliance assistance, routine process automation and cyber-threat detection. These tools can support institutional decisions; they do not make those decisions automatically reliable or transfer accountability away from the institutions using them.
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How the two technologies could change market processes
Tokenised platforms could coordinate steps that are now separate
Financial transactions often involve multiple systems and intermediaries handling asset records, instructions, checks and settlement. A tokenised platform could bring some of those elements together, enabling information and asset movement to be coordinated in a more integrated process. In a design sometimes described as an atomic operation, linked actions occur together or not at all—for example, an asset transfer paired with its payment. A BIS Annual Economic Report discussion presents contingent actions of this kind as a way to reduce reversal risk in the described architecture.
That is an architectural possibility, not evidence that all markets can settle instantly or that every transaction on a tokenised platform is atomic. Actual timing and finality depend on the platform, the settlement asset, legal arrangements, operating hours and links to other systems.
AI could add monitoring and decision support
AI could operate alongside tokenised platforms by flagging unusual transaction networks, supporting compliance workflows and helping detect cyber threats or operational anomalies. More timely or connected data may help some monitoring tasks, but combining information across institutions or borders also raises questions about privacy, confidentiality, data quality and coordination. Human oversight, clear responsibility and controls on how models are used remain necessary.
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| Technology | Potential role in infrastructure | What it does not settle |
|---|---|---|
| AI | Analyze activity, flag patterns, support compliance and assist with operational or cyber monitoring. | Whether a decision is legally or institutionally accountable, or whether model outputs are correct. |
| Tokenisation | Represent money or assets on a programmable platform and coordinate some transaction information and actions. | Legal ownership, redemption, custody, finality, regulatory responsibility or safe settlement. |
| Combined designs | Could pair more integrated transaction workflows with data-driven monitoring and decision support. | Whether integrated systems are interoperable, resilient, liquid and proven at scale. |
What the evidence says about adoption and benefits
Tokenised bonds offer a bounded early indicator
A Bank for International Settlements bulletin published on 10 July 2025 reported $8 billion in tokenised bond issuance to date. In that bulletin’s comparison, tokenised bonds had lower bid-ask spreads than conventional bonds and comparable issuance costs. The finding is specific to the bulletin’s scope and date; it should not be generalized to every tokenised market or treated as proof that tokenisation caused the observed differences.
Adoption remains early
The Financial Stability Board’s 22 October 2024 report characterized tokenisation adoption as very low but apparently growing, based on limited publicly available data. It did not provide a quantified share of all financial assets. The FSB said the small scale at that time did not pose a material financial stability risk, while identifying vulnerabilities that could become more important as adoption and complexity grow.
Potential gains include less reconciliation, more coordinated settlement, improved traceability and more timely processing. These are aims and possible outcomes, not universal results: the Financial Stability Board and the BIS Financial Stability Institute have emphasized that many benefits remain unproven and that implementation involves trade-offs. The available evidence does not establish integrated AI-and-tokenisation systems operating at large scale across financial markets.
What determines whether a design is safe and useful
Legal rights, governance and finality
Start by identifying the legal claim represented by each token and which record is authoritative if platform records conflict with other records. A sound arrangement also specifies who may pause or reverse activity, how errors and disputes are handled, who is responsible for custody, and which institutions retain regulatory obligations. Programmability can execute agreed rules; it cannot substitute for clear rights and governance.
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A tokenised transaction still needs an asset in which payment settles. Central bank money, tokenised commercial bank money and stablecoins have different risk profiles and implications for payment safety and financial stability. A platform’s speed or technical design does not make these forms of money interchangeable; the settlement choice must be evaluated as part of the arrangement.
Interoperability and concentration pull in different directions
Platforms need workable connections to legacy financial systems and to other platforms if assets and instructions are to move across institutional boundaries. Fragmented networks can limit efficiency gains, while strong network effects may concentrate activity in a small number of infrastructures. These are related but distinct design pressures: connecting systems can reduce silos, yet dependencies on dominant platforms can create their own risks.
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Liquidity and market links can change
Faster or more continuous operation can alter when participants need cash or eligible collateral. The FSB has identified liquidity and maturity mismatch, leverage and interconnectedness among vulnerabilities that merit attention in tokenisation. A process that completes more quickly is not necessarily easier to fund, especially if institutions’ obligations and settlement resources do not move in step.
Operational resilience spans both technologies
Tokenised arrangements can be exposed to smart-contract errors, private-key management failures, custody weaknesses, governance failures and the consequences of immutable transactions. AI systems introduce risks around data quality, model behavior and cyber security. The relevant question is not simply whether a platform or model works in normal conditions, but who can detect, contain and recover from errors, attacks or outages.
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Evidence should be separated by maturity
Live services, controlled pilots, announced projects and forecasts are different kinds of evidence. Claims about performance or scale should specify which one they describe. The FSB’s assessment of low adoption and the BIS’s dated issuance figure are useful indicators, but neither demonstrates that all tokenised finance—or combined AI and tokenisation—is mature or broadly deployed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess a proposed system
For a bank, market operator or policymaker evaluating a specific design, these questions expose the main trade-offs:
- Rights: What exactly does the token represent, and which legal record prevails?
- Settlement: Is the settlement asset central bank money, tokenised commercial bank money or a stablecoin, and what risks follow from that choice?
- Process: Which transaction steps are genuinely coordinated or atomic, and which still depend on external systems?
- Connections: How does the system interoperate with existing infrastructure and other platforms?
- Liquidity: How do settlement timing and continuous operation affect funding, collateral and exposure to counterparties?
- Accountability: Who is responsible for AI-supported decisions, model controls, data access and human review?
- Resilience: How are cyber incidents, key or custody failures, software errors and disputed or mistaken transactions managed?
- Evidence: Is the claimed result from a live deployment, a pilot, an announced project or a projection—and what date and scope does it cover?
The practical outlook
The most defensible view is that AI and tokenisation are potential complements in the modernization of financial plumbing. Tokenisation can change how certain assets, information and settlement actions are represented and coordinated; AI can help institutions monitor activity and support operational decisions. Neither technology removes the need for trusted institutions, legal certainty, safe settlement and accountable control. Efficiency gains are plausible, but their breadth and durability depend on design choices and evidence that remains early.
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