How to Choose a Board Management Platform Built for LLM Integration

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Board technology is changing quickly. Portals and apps that once focused on uploading PDFs now promise AI summaries, natural language search, and draft minutes powered by large language models (LLMs). For directors and corporate secretaries, the real question is not whether AI matters. It is how to select a board management platform built for LLM integration without increasing risk.

Below is a practical guide to evaluating a board management platform to choose when LLMs are part of the roadmap.

1. Get the foundations right before you look at LLMs

Any serious platform must still meet the classic board tech requirements. If the basics are weak, sophisticated AI features will only multiply the risk. At a minimum, look for:

  • Security and privacy

    • Strong encryption in transit and at rest.

    • Multi-factor authentication and granular role-based permissions.

    • Clear data residency options and a tested incident response plan.

  • Governance workflows

    • Meeting scheduling, agenda building, pack compilation and distribution.

    • E-signatures, resolutions, voting, and action tracking in one place.

  • Usability for busy directors

    • Simple interfaces on web and mobile.

    • Offline access and easy annotation.

    • Clear navigation between agendas, packs, and archives.

Only when these are in place does it make sense to talk about LLMs.

2. Understand what “LLM integration” actually means

Vendors use “AI” and “LLM integration” in different ways. Some offer basic text summarisation. Others embed LLMs more deeply into the workflow.

A credible LLM-enabled platform should support practical use cases such as:

  • One-click summaries of long reports and board packs.

  • Draft minutes and action logs for human review.

  • Natural language search across past minutes, packs, and policies.

  • Agenda and calendar suggestions based on past cycles and regulatory needs.

Ask vendors to show these features with realistic board documents, not just marketing copy.

3. Look at AI risk frameworks, not just features

LLMs introduce new categories of risk: data leakage, bias, hallucination, and regulatory exposure. Governance bodies around the world are issuing guidance on how to manage these risks.

For example, the NIST AI Risk Management Framework sets out four core functions — Govern, Map, Measure, and Manage — to help organisations embed trustworthy AI with clear accountability and controls. (NIST)

The EU’s AI Act is creating the first comprehensive legal regime for AI in a major market, using a risk-based approach and stricter rules for high-risk systems. (Digital Strategy)

When you assess a board management platform, ask how its AI design and processes align with these kinds of frameworks. A strong vendor should be able to explain:

  • How they identify and manage AI risk.

  • Who inside their organisation owns AI governance.

  • How they adapt to emerging regulation such as the AI Act.

4. Ask precise questions about LLM architecture and data use

LLM “magic” is not enough. You need clarity on how the platform actually works:

Data boundaries

  • Are your board documents stored and processed in a dedicated tenant?

  • Are prompts and outputs ever used to train models outside your organisation?

  • Can the vendor guarantee full data separation if you leave the service?

Model hosting

  • Which LLMs are used and where are they hosted (region, cloud)?

  • Can the platform support private or regional models if required by regulation?

Access control and logging

  • Does the LLM respect the same permissions as the rest of the platform?

  • Is there a detailed log of who triggered which AI action, on what document, and when?

If the vendor cannot answer these questions clearly, treat that as a warning sign.

5. Check alignment with board-level AI governance guidance

LLMs in board platforms are not just an IT issue. They are part of the board’s own AI governance responsibilities.

Board-focused guidance from institutes and regulators consistently stresses:

  • The need for board-level oversight of AI strategy and risk.

  • Clarity on roles and accountability between board and management.

  • Investment in board capability and literacy on AI. (Institute of Directors)

Choose a platform whose approach to AI makes it easier to meet these expectations. That means:

  • Clear labelling where content has been AI-assisted.

  • Built-in options to limit or switch off AI features for certain entities or committees.

  • Support for internal audit and compliance testing of AI features.

6. Test LLM features in real board scenarios

Instead of relying on a checklist alone, build a short pilot around real use cases:

  • Upload redacted board and committee packs and compare AI summaries with human-written executive overviews.

  • Use LLM-powered search to answer questions on a long-running topic such as cyber risk or capital allocation, and check whether the results are accurate and complete.

  • Generate draft minutes from sample notes or transcripts, then measure how much editing is needed before they are fit for the record.

The goal is not perfection. It is to see whether the platform saves time without losing nuance or missing critical detail.

7. Think about people and process, not just technology

Even the best LLM-enabled platform will fail if the organisation’s policies and habits do not change. Before you roll out new features:

  • Update your board technology or information policy to cover AI use.

  • Define which use cases are “assist only” (for example, summaries and draft minutes) and which areas should remain fully human.

  • Provide short training sessions for directors and governance staff on how LLM features work and how to challenge outputs.

Good practice guides on AI governance encourage boards to combine technology choices with clear principles on ethics, risk, and accountability. (cgi.org.uk)

8. Bringing it together: what a good choice looks like

A strong board management platform to choose for LLM integration will:

  • Meet high standards for security, usability, and core governance workflows.

  • Offer targeted LLM features that address real board pain points.

  • Provide clear, documented answers on data handling, model hosting, and risk management.

  • Align with recognised AI governance frameworks and emerging regulation.

  • Help the board demonstrate that human judgement, not automation, remains in charge.

If you evaluate vendors through this lens, LLM integration becomes less of a buzzword and more of a practical asset. The platform you select will not just manage documents. It will help your board see the right information at the right time, in a way that is consistent with the organisation’s values, risk appetite, and legal duties.

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