Chat-based tool embedded in Advisor Gateway aims to cut friction and free up time for clients
A new AI-powered assistant embedded directly into advisors' daily technology platform is designed to speed up how they find information and complete routine tasks, freeing up more time for client work.
Wells Fargo has launched AI Teammate, a chat-based capability built into Advisor Gateway, the firm's central technology platform for financial advisors, client associates and support teams across its Wealth & Investment Management (WIM) division.
The tool lets users ask questions in plain language, pull answers quickly and act on them without switching between multiple systems.
In its first phase, AI Teammate is focused on helping teams search and summarize material from WFA's core resource centre. That includes locating answers through plain-language search, condensing product, process and workflow information, guiding users through workflows with clear next steps, and consolidating scattered resources into a single access point.
The rollout will extend to financial advisors across all WIM advisor channels, including independent advisors operating under Wells Fargo Advisors Financial Network, known as FiNet.
Sol Gindi, head of the WIM Client Relationship Group and Wells Fargo Advisors, framed the launch as part of a wider AI strategy at the firm.
"We are making significant investments in AI and technology to empower advisors, grow client relationships, and gain market share," Gindi said. "AI Teammate builds on the foundation of Advisor Gateway and represents an important step in our broader vision for AI. We have a pipeline of additional AI tools in development that are all geared to helping our people focus on clients, deepen relationships, and deliver everything Wells Fargo has to offer more effectively."
Wells Fargo said future versions of the tool will go further, helping advisors spot new opportunities, prepare for client meetings using personalized insights, and prioritize actions that build relationships and grow their practices.
Workflow integration
Andre Mansour, head of WIM AI, said the goal is to place AI at points advisors already touch during their working day rather than as a separate destination.
"By embedding AI into natural workflow entry points, we can help our teams work more efficiently and make better use of the insights available to them," Mansour said.
Eve Varner, head of the WIM Chief Product Office, said the launch builds on prior work to simplify how advisors interact with the firm's systems.
"AI Teammate advances the progress we've made in delivering a more seamless and intuitive advisor experience," Varner said. "It's about making the tools advisors use every day more connected, more useful, and ultimately more effective in helping them serve clients."
Wider industry pattern
The launch fits a pattern playing out elsewhere in wealth management, where firms are applying AI to cut down time spent on preparation and research rather than replacing advisor judgment.
Manulife Wealth & Asset Management has rolled out three AI tools of its own across its Canadian and US businesses, covering compliance queries, advisor outreach and meeting preparation.
A tool built for Manulife John Hancock Retirement has generated close to 2,000 opportunities and roughly 390 closed deals since March 2025, while cutting time spent on pre-meeting research by 80% and lifting lead recommendations fivefold, according to the company. A separate compliance tool for Manulife Wealth advisors has logged nearly 980 users and more than 5,400 conversations, with 42% of advisors reporting time savings of up to 15 minutes per inquiry.
At Guardian Capital, portfolio manager Adam Cilio has used machine learning models in the firm's i3 investment process since 2017, pairing them more recently with large language models that digest qualitative research. Cilio has said the combination allows his team to focus human oversight on portfolio construction and risk management while AI handles data-heavy analysis.
Across these cases, the common thread is using AI to compress research and administrative work so advisors and portfolio managers can spend more time on judgment calls and client relationships, rather than handing decision-making to the technology itself.
