AI and distributed ledger technology: coincidence or convergence?

Over the past few years, two powerful trends have reshaped financial services in parallel. And though they’ve often been discussed separately, it’s increasingly impossible to ignore them together.

Artificial intelligence has moved from experimentation to everyday commodity at remarkable speed. What was once specialised is now widely accessible, and we’re seeing AI becoming more embedded into tools, products and workflows.

The way money moves has evolved just as dramatically. Payments that once took days now settle in seconds. Customers expect value to move instantly, invisibly, and across borders and platforms without friction. 

These shifts have transformed both decision-making and execution. What they have not yet done is fundamentally change how the two interact. But that’s beginning to change.

Individually, AI and distributed ledger technology (DLT) represent a significant transformation, while together they raise a more provocative question: are we witnessing two separate technology trends maturing at the same time, or the early stages of a deeper merging that will redefine financial infrastructure itself? In short, are we seeing coincidence – or convergence?

Decision versus execution  

These two technologies are often framed as part of the same innovation wave, though in reality they solve very different problems:

• AI transforms the speed and quality of decision-making.
• DLT transforms the speed, certainty and programmability of value.

Individually, both are powerful, but the real shift happens when they begin to reinforce each other.

However, there is still a gap between deciding and doing. Insights can be generated faster than systems can act on them, or transactions can be executed faster than meaningful decisions are made. When that gap closes, the implications are far more significant than incremental efficiency, and will enable entirely new operating models for financial services.

The rise of agentic finance

What’s changed recently is the rise of AI agents. These systems don’t just analyse information – they can monitor data, make decisions and trigger actions across multiple systems.

At the same time, DLT infrastructure means those actions can be taken automatically through smart contracts – essentially pre-defined digital agreements that run themselves when certain conditions are met, such as moving funds, transferring assets or releasing collateral.

Bring the two together, and you get something new: decisions that don’t just sit as insight, but are carried through into execution end-to-end.

From transactions to orchestration

When AI and DLT converge, finance shifts from discrete transactions to continuous orchestration. Some of the emerging use cases illustrate this clearly:

• Autonomous homebuying: AI agents coordinate buyers, lenders and legal processes, while tokenised contracts synchronise funds, agreements and completion, compressing a months-long process into something far faster and more certain. 
• Hyper-personalised investing: AI continuously designs and optimises portfolios at an individual level, while DLT embeds execution, rebalancing and reporting directly into smart contracts. 
• Real-time risk and margining: DLT enables automated collateral flows, while AI interprets signals and identifies genuine risk events, improving both speed and resilience. 
• Autonomous wealth transfer: AI-enabled 'living wills' adapt over time, with DLT infrastructure ensuring secure, automatic execution when required. 

The financial infrastructure gap

There is, however, a fundamental constraint in that today’s financial infrastructure is not designed for this model. It’s built around account-based money, human-led decisions, and sequential, system-by-system processing.

By contrast, AI agents are continuous, multi-step and cross-system, and DLT is programmable, interoperable and multi-instrument. This creates a structural mismatch. As AI capability accelerates, the infrastructure it runs on must evolve in parallel. Without that evolution, we risk increasing speed and complexity without improving outcomes.

Evolving from bank accounts to digital wallets

This shift also changes the interface. For decades, the bank account has been the centre of financial life, storing money and enabling transactions. In a DLT, AI-enabled world, that model begins to give way to digital wallets.

These are fundamentally different to a bank account, and can:

• hold multiple forms of value – including DLT assets
• integrate identity, permissions and contracts
• enable secure delegation to AI agents
• act as a unified interface across financial systems.

Increasingly, wallets become not just a container for value, but a control layer where individuals define what agents can see, decide and do. This is critical, because it brings us to the most important challenge of all. Trust.