Plain-English definitions of the terms that come up in the room.
No jargon, no vendor copy. Each entry is a short definition followed by the operating context that makes the term mean something inside a real business.
Agentic Workflows→
Agentic AI
Agentic AI is artificial intelligence designed to observe a queue of work, reason about it under defined rules, take the approved next action, and escalate the unusual cases to a person — operating as a worker rather than as a chat assistant.
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Agentic Workflow
An agentic workflow is a single recurring queue of work — review response, lead intake, document triage — handled end-to-end by an agentic AI system, with human approval gates at every consequential decision and a full audit log of actions taken.
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AI Strategy→
Retrieval-Augmented Generation (RAG)
RAG — retrieval-augmented generation — is the architecture that lets a language model answer questions about a specific business by retrieving relevant documents from that business's own knowledge base before generating the response.
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Knowledge Graph (for Business)
An institutional knowledge graph is a structured, queryable representation of a firm's accumulated documents, decisions, and tacit memory — the layer that turns "ask the longest-tenured person in the room" into a query an LLM can answer with citations.
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AI Audit
An AI audit is a structured, time-boxed review of a firm's operations to identify which queues are good fits for agentic AI workflow design — and which are not — before any build engagement is committed.
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Middle-Market Business
A middle-market business is a firm too large to be served by SMB-class tools and too small to be served by enterprise consulting — typically $10M to $1B in annual revenue, 50 to 1,000 employees, with operating sophistication closer to enterprise but operating budget closer to SMB.
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Predictive ML→
Supervised Machine Learning
Supervised machine learning is the branch of ML where a model learns from historical examples with known outcomes to predict the outcome of new cases — calibrated, repeatable, auditable, and the cleanest fit for most middle-market operating problems.
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Predictive AI vs. Generative AI
Predictive AI predicts the next number — a forecast, a score, a probability. Generative AI generates the next sentence — text, code, images. Same field, different operating shapes, very different ROI patterns inside a business.
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