UBS saves U.S. advisors an estimated 10,000 hours a month with AI client-meeting prep

UBS advisors serve high net worth and ultrahigh net worth clients, and they need to know what is going on with each client and where the opportunities are before a client meeting. Finding answers to questions about branch guidelines and procedures was labor intensive, with advisor teams calling an internal call center. Advisors also could not keep up with everything UBS research produced, so a client question could mean reading an article, working out the firm's view and then going back to the client.

UBS built STAAT Insights, an AI-driven engine that serves advisors insights and opportunities across 400 scenarios and sends an automatic client briefing before each meeting. It was built by studying how the best advisors serve clients and codifying that process in a set of AI models. UBS also gave all employees Microsoft Copilot, built a chatbot on its branch guidelines and procedures so advisors get answers right away, and introduced a meeting-scheduling agent that lets an advisor share availability with a client in one click. The firm says a human needs to stay in the loop and advisors need to cite where information came from.

UBS Chief Data and Analytics Officer Joe Cordeira conservatively estimates that advisors in the United States save 10,000 hours a month by using AI to prepare for client meetings. He says 80% of advisors actively use STAAT Insights, Copilot usage is over 85%, and the knowledge-base chatbot gets about 20,000 prompts a month from advisors. He also says an AI meeting summary versus keying notes into the CRM could save 20 to 30 minutes per client meeting.

• Study how the best advisors serve clients and codify that process in AI models so every advisor benefits.
• Send advisors a briefing before each client meeting that shows what is going on with the client and where the opportunities are.
• Keep a human in the loop and have advisors cite where AI-generated information came from.