AI Meeting Intelligence for Advisory Firms_

Advisory firms use AI to transcribe client meetings in real time, identify speakers, extract key decisions and action items, generate structured summaries and client file notes, and track actions to completion, ensuring that the firm’s most valuable asset (the content of client conversations) is captured, searchable, and actionable rather than existing only in the notes one person happened to take. Every meeting produces a structured record within minutes of ending.

Why meeting content is lost in advisory firms

Advisory firms live in meetings. Client discovery sessions, project check-ins, board presentations, internal strategy discussions, and stakeholder interviews. Each meeting contains decisions, commitments, insights, and action items. In aggregate, the content of these meetings represents the firm’s understanding of each client’s business.

The problem is capture. Most advisory professionals take notes during meetings, but those notes are partial, subjective, and unstandardised. The note-taker writes down what they consider important, which may differ from what another attendee considers important. Action items are recorded inconsistently. Client statements that seem minor during the meeting but become significant later are not captured.

After the meeting, the notes (if they exist) live in the note-taker’s personal files, in an email summary to the team, or occasionally in a formal file note. Finding what a client said about a specific topic six months ago requires remembering which meeting it was, who attended, and where the notes were saved.

The loss has real consequences. Action items are forgotten. Client preferences expressed in one meeting are contradicted in the next because the team does not have the record. New team members joining an engagement have no way to understand the history of client conversations. When a key team member leaves the firm, their meeting notes leave with them.

For firms where meetings are billable, there is also a commercial issue. Writing up meeting notes after the meeting takes 15-30 minutes per meeting. For a partner with 4-6 meetings per day, that is 1-3 hours of administrative time. Much of it does not get done, which means the record is incomplete.

How AI meeting intelligence works

Meeting capture

The system joins meetings via integration with video conferencing platforms (Teams, Zoom, Google Meet) or records in-person meetings via a mobile application or room microphone. The audio is processed in real time.

Transcription: the audio is converted to text with speaker identification. Each participant’s contributions are labelled, so the transcript reads as a dialogue rather than a monologue. Transcription accuracy exceeds 95% for standard English, with industry-specific terminology improving accuracy further when configured.

Speaker diarisation: the system distinguishes between speakers even when they talk over each other. Initial speaker labels (“Speaker 1,” “Speaker 2”) are replaced with names once the system learns voice profiles, or when the meeting participants are identified from the calendar invite.

For sensitive meetings where recording is not appropriate, the system can work from manual notes entered after the meeting, applying structure and extraction to the adviser’s written input.

Structured extraction

From the transcript, the system extracts structured data:

Decisions: statements where the participants agreed to a course of action. “We’ll go with Option B” is identified as a decision, tagged with who made it and when.

Action items: commitments to do something. “I’ll send you the revised model by Friday” becomes an action item with owner (the speaker), description (send revised model), and deadline (Friday). Each action is tagged for tracking.

Questions raised: questions asked during the meeting that were or were not answered. Unanswered questions are flagged for follow-up.

Key statements: significant client statements that may inform the engagement. A client mentioning “our board is concerned about the timeline” or “we’re also talking to [competitor firm]” is flagged as a key statement.

Numerical commitments: budgets, targets, deadlines, and other numerical references are extracted and tracked. If the client commits to a £500k budget or a Q3 launch date, this is captured as a trackable commitment.

Risk indicators: mentions of risk, concern, worry, or problem are flagged. The system does not assess the risk; it ensures it is recorded so the team can address it.

Meeting summary generation

Within minutes of the meeting ending, the system generates:

Executive summary: 3-5 sentences capturing the meeting’s purpose, key discussion points, and outcomes. Written for someone who was not in the meeting.

Detailed summary: a structured document covering each topic discussed, what was said by each party, the conclusions reached, and the next steps. This is the equivalent of a thorough file note, produced automatically.

Action item list: every action identified, with owner, description, and deadline. This list feeds into the firm’s task management system.

Client file note: formatted per the firm’s standard for client file documentation. Includes: date, attendees, topics covered, decisions made, actions arising, and follow-up required. The adviser reviews, edits if necessary, and approves. The approved note is saved to the client file in the firm’s document management system.

Action tracking

Actions extracted from meetings enter the firm’s task management workflow:

• Each action is assigned to the identified owner
• Deadlines are set from the meeting discussion
• Reminders trigger before deadlines
• Overdue actions escalate to the engagement manager
• At the start of each subsequent meeting, unresolved actions from previous meetings are surfaced in the agenda

This tracking ensures that commitments made in meetings are honoured. The common advisory failure mode (“we discussed this three meetings ago and it still has not been done”) is addressed by persistent tracking.

Searchable meeting library

Every transcript and summary is stored in a searchable library:

• Search by keyword across all meetings with a client, or across all clients
• Filter by date range, attendees, meeting type, or engagement
• Find specific statements by a specific person
• Track how a topic has evolved across multiple meetings
• Identify patterns (the same concern raised in multiple meetings may indicate a systemic issue)

This library becomes institutional memory. When a new team member joins an engagement, they can read the meeting summaries and transcripts to understand the client relationship history. When a client references a previous conversation, the team can find exactly what was said.

Pre-meeting preparation

Before each meeting, the system generates a preparation brief:

• Outstanding actions from previous meetings with this client
• Key points from the last meeting
• Topics that were deferred or left unresolved
• Any relevant developments since the last meeting (from the client dashboard if deployed, or from news monitoring)

The adviser enters the meeting prepared rather than relying on memory.

Results from deployment

Advisory firms using meeting intelligence typically see:

• File note completion rates increase from 40-60% to 95%+ (because notes are generated automatically)
• Action item completion rates improve 30-40% (because tracking is persistent)
• Client satisfaction increases because the firm remembers and follows through on commitments
• New team members ramp up faster because meeting history is accessible
• Partner administrative time drops 1-2 hours per day (no manual note-writing)
• The firm builds a searchable knowledge base that grows with every meeting

UK-hosted infrastructure. Audio and transcripts encrypted. Configurable retention policies. GDPR-compliant processing.

Typical timeline: 4-6 weeks. Typical investment: £12-20k / $15-25k.