Enterprise AI
Meeting intelligence
Also known as: AI notetaker, meeting assistant, conversation intelligence
Meeting intelligence is software that records, transcribes and analyses meetings to produce summaries, action items and searchable insight across conversations. It usually joins calls as a bot or runs inside the conferencing platform, then applies language models to the transcript. In sales settings it is often called conversation intelligence and is used to coach reps and track deal risk.
What it is
A meeting intelligence tool captures the call, produces a transcript with speaker labels, then generates notes, follow ups and topic tagging. Many products push summaries into a CRM or project tool, and let users search across every recorded conversation. Enterprise versions add permissions, retention rules and analytics across teams rather than single meetings.
Why it matters
It changes where knowledge lives, moving decisions and objections out of memory and into searchable text that other systems can query. For marketing and product teams, recorded calls become a reliable source of customer language, which sharpens messaging and content. For buyers, the category is now evaluated through AI assistants, so vendors need clear, accurate descriptions of integrations, security and pricing on their own sites.
How it works
Teams connect the tool to their calendar and conferencing platform, set consent and recording rules, and choose which meetings are captured. Summaries are reviewed and pushed to a CRM or knowledge base, and analytics are used to spot recurring objections or topics. Good practice includes clear notification to participants, retention limits and access controls by team.
When it applies
Applies in any organisation that runs frequent customer or internal calls and needs reliable records, coaching data or shared context without manual notetaking.
Examples
- A sales manager reviews tagged objection clips across the quarter to update the pitch.
- A product team searches every support call for mentions of a specific feature request.
- Meeting summaries are written back to the CRM so the next owner has full context.
How it is measured
- Share of customer calls recorded and summarised
- Accuracy of generated action items checked against a manual sample
- Time saved on post meeting admin per user per week
- Adoption rate and weekly active users across sales, support and product teams
Insights on Meeting intelligence
Related terms in Enterprise AI
- AI agentsAI agents are software systems that use a language model to plan and carry out multi-step tasks, rather than simply returning a block of text. They can call tools, query APIs, browse websites and write to other systems in pursuit of a goal, with varying degrees of human oversight. The term covers everything from a scripted assistant that books a meeting to a research agent that gathers sources and drafts a report.
- AI chipsAI chips are processors designed or optimised to run machine learning workloads, especially the large matrix operations behind training and inference. The category covers GPUs, tensor and neural processing units, and custom ASICs, usually paired with high-bandwidth memory and fast interconnects. They are also called AI accelerators or AI semiconductors.
- AI drug discoveryAI drug discovery is the use of machine learning and computational models to support the early stages of finding and refining new medicines. Models are applied to tasks such as predicting protein structures, identifying candidate molecules, prioritising targets and estimating properties like toxicity or binding affinity. The aim is to narrow a very large search space before expensive laboratory and clinical work begins.
- AI infrastructureAI infrastructure is the stack of hardware, networking, storage and software needed to train, fine-tune and serve AI models at scale. It spans accelerators such as GPUs, the data centres and power that house them, and the orchestration and serving layers that turn raw compute into working model endpoints. For most marketing teams it is a cost and capacity constraint they consume through APIs rather than something they build.
- AI procurementAI procurement is the process of evaluating, buying and contracting artificial intelligence tools and services, from assistants and content platforms to models accessed through an application programming interface. It covers commercial terms alongside security, data protection, accuracy and integration questions that do not arise with ordinary software. Most organisations run it as a structured review with pilots, stakeholder sign off and defined exit conditions.
- AI securityAI security is the practice of protecting AI systems, their data and the applications built on them from misuse, manipulation and leakage. It covers threats such as prompt injection, data exfiltration through model outputs, unsafe tool use by agents and compromised supply chains. It also covers the controls that keep AI features safe once they are live.
Primary research · August 2026
How ChatGPT Shortlists Software Brands
An audit across 10 categories and 60 buying questions. I recorded what ChatGPT reads, throws away and links to when a buyer asks it which software to buy, and what that decides.
- 60
- Questions asked
- 10
- Software markets
- 2,680
- Results read
- 367
- Links shown
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