Glossary
The terms behind AI transformation
Plain definitions of the words that come up when a business starts working with AI, and how each one differs from the terms it gets confused with.
Agentic workflowAn agentic workflow is a business process in which AI agents carry out the steps, use tools and decide what to do next, with people on the exceptions.AI agentAn AI agent is software that uses a language model to pursue a goal: it plans steps, calls tools and systems, and acts on the results.AI evalsAI evals are test sets of real cases with known right answers, run against an AI system before release and after every change to measure its quality.AI governanceAI governance is the set of policies, controls and oversight that decide how a company builds, uses and monitors AI, and who answers for it.AI implementationAI implementation is putting an AI system into production inside a business: building it, connecting it to real systems, testing it and running it.AI orchestrationAI orchestration coordinates AI agents, models and tools so they run as one system: who does each step, in what order, and what happens on failure.AI transformationAI transformation is rebuilding how a company works around AI, process by process and department by department, until its core work runs through agents.AI-nativeAn AI-native company runs its core work through AI agents, with people setting direction and making the calls. How it differs from AI-enabled.Context engineeringContext engineering is designing everything a model sees for a task: instructions, examples, data, tool results and memory, so an agent acts reliably.Forward-deployed engineeringForward-deployed engineering puts software engineers inside a customer's business to build systems on site, around how the work really happens.Human in the loopHuman in the loop means people review, approve or correct an AI system's work at set points, so agents handle the volume and people keep the judgement.Intelligent document processing (IDP)Intelligent document processing (IDP) uses AI to read documents such as invoices, forms and contracts, extract the data and route it into business systems.Large language model (LLM)A large language model (LLM) is an AI model trained on vast amounts of text to read, write and reason in language. It is the engine inside most AI agents.Model Context Protocol (MCP)The Model Context Protocol is an open standard for connecting AI models and agents to tools, data and business systems through one common interface.Retrieval-augmented generation (RAG)Retrieval-augmented generation (RAG) finds relevant passages in your own data and gives them to a language model, so its answers draw on your facts.
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