At a leaner firm, the productivity gains can be immediate. Selfe described using AI for research, synthesis, investment preparation, strategy and communications, allowing a small team to undertake work that previously required substantially more resources.

One example, she said, is preparing for a client conversation. An advisor may need to bring together market developments, investment commentary and a firm’s house view before discussing an issue that has unsettled a client. AI can help assemble that material more quickly, leaving the advisor with more time to interpret it and respond to the client’s concerns.

For Selfe, the ability to prepare faster does not remove the need for an experienced person to assess the information. Clients can access AI tools themselves; professional value lies partly in applying experience and judgment to the answers those tools produce.

Accountability is equally important. At Calabar, she said, AI-generated material must be traceable to source information and reviewed and approved by a human before progressing to the next step. Fluent language alone is insufficient evidence that an output is correct.

“Accountability must remain human,” she said.

Her analogy is that of an intern preparing work for a senior colleague. An advisor would review an intern’s paper before presenting it to a client, and AI-generated material warrants the same scrutiny.

The opportunity she describes is to make professionals better informed and more responsive while preserving responsibility for what reaches an investor. That leaves an important question for firms pursuing efficiency: how will they use the time AI saves to improve the advice clients receive? The report will examine that question through further interviews and survey responses.

The upcoming report will bring together survey findings and further interview insights. Professionals working in private banking and wealth management are invited to contribute their views by completing the survey.