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ING Uses AI To Give Relationship Managers More Time For Clients

Editorial Staff

22 October 2026

This article continues WealthBriefing’s interview series ahead of its forthcoming AI in Wealth Management research report, produced in partnership with , a central test of AI in wealth management is whether it frees relationship managers to spend more time with clients.

Anneka Treon (main picture), global head of private banking, wealth management and investments at ING, described an approach focused on reducing administrative friction as the business grows.

“My priority is not to cut costs,” she said. Instead, the aim is to make relationship managers more effective as demand for their services expands.

Four agents for everyday work
ING’s internally developed Commercial Assistance Suite brings together four agents covering KYC, investment expertise, sales coaching and meeting preparation. ING says it intends to make the suite available to relationship managers in the Netherlands and Belgium by the end of 2026.

Treon said the KYC agent reported average savings of 45 minutes of RM time during legal-entity onboarding.

The investment expert helps bankers review portfolio performance and relevant news, with a conversational function making the investment office’s views easier to access.

Sales coaching, still undergoing further piloting, examines patterns in successful relationship managers’ conversations and uses those insights to provide feedback to colleagues.

Controlling information and advice
The investment expert also provides a testing ground for functionality that might eventually reach clients. For now, ING is building experience internally while addressing governance and client-protection questions.

This supports what Treon called ING’s “head to heart” approach: using digital processes to create space for conversations about clients’ goals and concerns.

Treon sees opportunities for conversational AI to make investment guidance more accessible but cautioned: “We are not there yet.”

Wider industry
ING’s experience highlights a question for the wider industry: how should AI progress be measured? Making an agent available is a starting point. Consistent use, time released for clients and sustained benefits as deployment expands will provide more meaningful evidence.