Large organisations are achieving limited benefits from AI projects. Yet, their appetite to invest more is undiminished. Rob Lunn, Product Manager at Fnality, a regulated wholesale payment system that settles transactions on-chain, argues that this paradox is not just a general business problem. In financial services, where unit cost discipline and regulatory compliance define survival, it is a structural risk that leadership teams have not yet priced in.

Rob makes the case that AI and blockchain are not competing technologies; they serve fundamentally different parts of the payment chain, and confusing the two is one of the more expensive mistakes a payments organisation can make.

The conversation maps the payment process from instruction receipt through to settlement and reconciliation, and locates precisely where each technology delivers value. Blockchain, through atomic settlement, removes counterparty risk at the point where absolute certainty is required: payment occurs if and only if the corresponding asset transfer happens. AI delivers its greatest value at the start and end of that chain, reading unstructured invoice / payment instruction data, extracting meaning from vendor records, and supporting liquidity forecasting and reconciliation. Where existing automation already achieves very high straight-through processing rates, agentic AI faces two barriers Rob identifies as equally significant: the legal framework for autonomous transaction signing, and enterprise and consumer trust.

Highlights from the conversation:

• The paradox Rob names: large organisations report a low success rate with AI projects today, yet investment appetite, based on industry surveys and events including London Tech Week, is off the scale.

• Atomic settlement explained: blockchain links payment and asset transfer so that one cannot occur without the other, removing the settlement risk that became systemic during the Lehman Brothers collapse.

• Settlement risk is one of the factors determining how much capital banks must hold under global regulations, making its reduction a direct financial benefit, not just an operational one.

• Rob's leadership framework: be highly selective in AI use cases; focus on a small number of well-defined projects; assess total cost of ownership against customer outcome, regulatory obligation, and long-term capability building.

• The talent pipeline argument: eliminating junior roles before organisations build the technical and domain knowledge those roles develop leaves the future management layer without the skills to run AI-dependent operations safely.

For leaders in financial services asking where AI and blockchain actually earn their place, and what the cost of getting that wrong looks like, this conversation provides an unusually precise answer.

Chapters

00:00 Fnality and Blockchain in Payments

03:23 Blockchain's Role in Mitigating Settlement Risk

08:31 Synergies Between AI and Blockchain Technologies

11:07 Limitations of AI in Payment Processes

14:52 Regulatory Challenges in Financial Technologies

17:23 Impact of AI and Blockchain on Leadership in Payments

21:12 Long-term Challenges in the Payments Industry

23:21 Preparing for AI and Blockchain Integration