BrightPath grew from 8 to 32 people in four years. Staff already used AI daily, but every adviser had invented their own method, client data was going into tools without checks, and nothing was measured. The problem wasn't "no AI"; it was ungoverned AI: risk without leverage.
Not software. The small set of standards, configured tools and rules that make good AI use the default. Built on the firm's existing stack (M365, Claude Team, ChatGPT Team), configuration, not new purchases.
A firm-standard Statement-of-Advice first draft from structured inputs, removing the blank-page and boilerplate cost while making the adviser's best-interests review stronger. The AI never issues advice; a licensed adviser verifies every figure and signs.
Triage and drafting of routine client email in the firm's voice, with an explicit "possible advice → escalate" path so an advice question never gets a casual AI answer. A human sends every message.
Modelled under stated assumptions (see the before/after model). The brief's success bar is ≥20% cycle-time improvement, both pilots clear it.
The ≥20% result depends only on per-item drafting/handle time, the most directly measurable input, so it's robust to the volume and dollar assumptions, which scale value, not the percentage. Dollar figures are an indicative value of reclaimed time, not cash savings.
Because this is financial advice, the human-review gate is designed to be unavoidable, not optional. Client-identifying data is kept out of tools via a placeholder de-identification habit; only business-tier tools with training disabled are approved; and a short, signed acceptable-use framework maps to Australian obligations (best-interests duty, ASIC RG 175, Privacy Act 1988 / APPs) at a practitioner level. AI drafts · a licensed human decides
.docx)