AI Agents in Financial Services: From Pilot to Production

This is the decade where AI moves from experiment to operating model. McKinsey puts the long term productivity prize from gen AI at $4.4 trillion. PwC's 2025 Digital Trends in Operations Survey shows 57% of operations leaders have already embedded AI into selected functions. Yet only 1% of executives say their organisation has reached AI maturity.

The gap between deployed and delivering is the gap this room is built to close.

For FinServ, the case for AI agents is proven in the contact centre and the back office. The challenge now is industrialising it. Scaling across functions without fragmenting the technology stack or the data estate. Holding the cost case as volume grows. Lifting customer outcomes (CSAT, retention, complaint volumes) at the same time. And doing all of it under FCA expectations on consumer duty, vulnerability handling and explainability, with the security posture and auditability that lets governance keep pace with delivery.

That is a cross functional problem. Operations owns the P&L impact, technology owns the platforms that make scale possible, and security and risk own the controls that make it defensible. This briefing is built for the leadership team being asked to deliver all of it together.

Who it's for

• COOs and Operations Transformation leaders accountable for cost to serve, productivity and capacity
• Heads of Contact Centre and Customer Operations modernising the front line
  Operating model, change and process transformation leaders
• Operational Risk leaders who own the controls that make scale possible
• CIO and CX peers welcome alongside the operations leadership team

Zoom will run a live FinServ AI agent through a controlled customer workflow from start to finish. Triage, secure authentication, payment, and a compliant summary with full audit trail. Then we open the floor for the room to stress test it with the edge cases your own programmes are hitting today.

The point is to make the operating model decisions visible. Where the agent earns its ROI. Where it lifts the customer experience. Where humans stay in the loop. And what defensible governance looks like when you are running at scale rather than running a pilot.

What you'll leave with

• A practical framework for sizing AI agent ROI across the operations P&L: cost to serve, deflection, AHT, FTE capacity released, CSAT and retention impact
• A reference operating model for moving AI agents from pilot into production without fragmenting tooling, talent or controls
• A clear view of the customer journey moments where AI agents deliver the biggest operational and experience uplift, and the moments to keep human led
• The guardrails, auditability, consumer duty checkpoints and human in the loop controls that keep automated workflows defensible at scale
• Tactics for accelerating sign off across Ops, CX, Risk and Compliance so projects move in weeks rather than quarters
• Real examples from FinServ operations teams already capturing the upside