Davos marks a maturing phase for AI in financial services

At the World Economic Forum in Davos, a notable shift in tone emerged from discussions on artificial intelligence in banking and FinTech.

AI in financial services

Rather than racing to deploy the newest models, industry leaders emphasised discipline, resilience and trust.

AI is no longer treated as a speculative advantage but as critical infrastructure that must be governed with care.

The consensus was clear: in financial services, credibility now matters more than speed.

From Disruption to Interdependence

The long-framed battle between banks and FinTechs is giving way to a more nuanced reality.

Institutions increasingly compete and collaborate at the same time, sharing data, platforms and customer journeys while vying for relevance.

Executives described this relationship as structurally interdependent rather than adversarial. Banks bring scale, balance sheets and regulatory credibility; FinTechs contribute agility and product innovation.

Neither side can deliver meaningful transformation alone.

This interdependence is most visible in payments, wallets and digital commerce, where customer interfaces are often controlled by technology platforms while banks remain essential to settlement, compliance and risk management.

Trust as the True Network Effect

Trust repeatedly surfaced as the defining competitive advantage.

While digital platforms can scale quickly, confidence in the safe handling of money, identity and data remains decisive.

Payments and commerce only function when users believe systems are secure, transparent and accountable.

In this sense, trust operates as a network effect more powerful than user numbers or processing volume.

Executives argued that AI amplifies this dynamic.

Poorly governed models, opaque decisioning or unexplainable outcomes risk eroding confidence far faster than they generate efficiency gains.

AI Adoption Without Illusion

Banks acknowledged the productivity benefits already delivered by machine learning, from fraud detection to compliance automation.

However, caution dominates the next phase. Generative and agentic AI tools are being tested internally but rolled out carefully in customer-facing contexts.

The risk of errors, hallucinations or unintended bias remains too high for uncontrolled deployment in regulated environments.

This restraint reflects a broader recalibration: AI is seen as transformative, but only if embedded within robust operational and governance frameworks.

Branches, Platforms and Human Relevance

Despite years of digital investment, physical branches and human interaction remain strategically relevant.

Rather than disappearing, branches are being re-engineered as multi-channel hubs, supporting in-person service alongside chat and call-centre interactions.

AI-powered agent tools enhance productivity, but they complement rather than replace human judgement, particularly for complex financial decisions.

The message from Davos was pragmatic: efficiency gains do not eliminate the need for trust built through personal engagement.

Regulators as Infrastructure Builders

Perhaps the most significant signal came from regulators.

Central banks are moving beyond rule-making toward actively building digital infrastructure, from instant payments to AI governance frameworks.

This approach aims to prevent risk from migrating outside oversight while enabling innovation.

The emerging model treats operational resilience alongside capital and liquidity as a core supervisory concern.

In an AI-driven financial system, stability depends not just on regulation, but on shared standards, interoperable infrastructure and sustained trust.