Preparing Board and Partner Packs with Help from AI

Board and partner packs have a familiar pattern:

too long or too thin;
rushed together the night before; and
full of numbers that do not quite match what people see day to day.

AI will not decide your strategy. It can make it much easier to assemble management packs that tell a clear, honest story about performance, risk and opportunities.

This article looks at how firms can use AI to prepare board and partner packs more efficiently — without turning governance into a black box.

1. Decide what the pack is for

A useful pack usually serves at least three purposes:

Performance – how the firm, practice groups and key products are doing.
Risk and compliance – what is keeping COLPs, COFAs and risk partners awake.
Forward look – pipeline, investments, hiring and technology.

Before involving AI, agree a simple structure, for example:

headlines and key messages;
financial KPIs (fees, WIP, lock‑up, write‑offs);
operational metrics (matter volumes, cycle times, supervision indicators);
risk and incidents;
strategic initiatives (including AI projects);
practice area deep‑dives or case studies.

AI works best when it fills a known shape rather than generating free‑form reports.

2. Pulling data together: let AI help with the narrative, not the numbers

Core financials should come from your finance systems, not from AI. Where AI is helpful is in:

turning raw tables into narrative explanations (“litigation revenue decreased X% mainly due to…”);
spotting simple trends or anomalies to flag for discussion;
harmonising terminology across teams.

A sensible workflow is:

Finance exports agreed KPIs as spreadsheets or reports.
AI ingests those tables and drafts a commentary section with:
- key movements (up/down vs last period);
- possible drivers (based on tags or notes);
- questions for partners (“Is this drop due to Y or Z?”).
Management reviews and edits the commentary before it goes anywhere near a pack.

This keeps control of numbers with humans while using AI to avoid the blank‑page problem when writing explanations.

3. Case studies and client stories

Boards and partners respond better to stories than to spreadsheets alone. AI can help you:

identify candidate matters for case studies (new sectors, notable wins, instructing clients);
summarise key facts, strategy and outcomes from the matter file;
anonymise or generalise details where necessary for confidentiality.

For each case study, AI can draft a short note covering:

background and client context;
what the firm did (across teams where relevant);
outcome and impact;
lessons for future work (sector insight, product ideas, pricing learning).

Partners then refine tone and emphasis. The result is richer, more grounded board discussion about real work, not just revenue lines.

4. Risk, incidents and AI governance reporting

Boards increasingly expect regular updates on:

complaints and claims;
regulatory interactions;
information security issues;
AI and technology risks.

AI can support this by:

helping risk and compliance teams summarise incident logs into short, comparable entries;
structuring AI‑related incidents or lessons learned (“hallucination caught in supervision”, “client query about AI use”) into a simple format;
drafting short commentary on emerging regulatory guidance.

Again, humans decide what is material and how it is framed. AI just makes it faster to turn raw logs and notes into a coherent section of the pack.

5. Forward‑looking sections: pipeline and projects

For pipeline and strategic projects (including AI initiatives), AI can help by:

consolidating updates from multiple project leads into a single RAG‑style overview;
harmonising language about risks, dependencies and next steps;
generating short “executive summaries” for each major initiative.

For example, if each project lead submits a one‑page update in their own words, AI can:

extract key points into a standard template (status, key milestones, blockers, budget position);
highlight where several projects depend on the same team or system;
propose questions for the board (“Do we need to phase X and Y?”).

This helps partners see the whole picture without needing to read every detail.

6. Guardrails: accuracy, tone and accountability

Management information is politically and legally sensitive. Guardrails should include:

keeping all pack preparation within governed systems (case management, DMS, BI tools), not ad hoc personal accounts;
making it clear which sections were AI‑assisted, so people know where to probe;
requiring human sign‑off from finance, risk and practice heads on their areas.

Avoid the temptation to let AI “massage” bad news. Its job is to:

summarise;
structure; and
highlight;

— not to spin.

Where OrdoLux fits

OrdoLux is being designed so that matter‑level data and AI‑assisted summaries can feed naturally into partner and board reporting:

activity, time and supervision logs live with each matter, ready for aggregation;
AI can help summarise patterns (for example, AI usage, supervision trends, time capture improvements) into management narratives;
risk and incident information related to matters can be surfaced for governance reporting.

The aim is that, when you sit down to prepare the next board or partner pack, you are not starting from scattered spreadsheets and inboxes, but from joined‑up matter and performance data that AI can help you explain.

This article is general information for practitioners — not legal advice, financial advice or corporate governance guidance for any particular firm.

Looking for legal case management software?

OrdoLux is legal case management software for UK solicitors, designed to make matter management, documents, time recording, management information and AI assistance feel like one joined‑up system. Learn more on the OrdoLux website.