AI Terms in Procurement Explained: ML, GenAI, LLMs, NLP, and AI Agents

AI is the umbrella term for systems designed to perform tasks that normally require human judgment. Machine Learning is one specific technology beneath that umbrella: models that identify statistical patterns in historical data to make predictions or classifications, without being explicitly programmed for each task. Generative AI, NLP, and AI Agents are separate technology classes under the same umbrella, each with its own logic and limitations.

No. Generative AI is the broader category: any system that produces new content based on patterns in its training data. Large Language Models are a specific subset of Generative AI, trained on large volumes of text to generate human-like language. Every LLM is Generative AI, but Generative AI also covers models generating images, audio, or other content types beyond text.

By asking which specific technology sits behind the label – Machine Learning, Generative AI, an LLM, or an AI Agent – since each carries different governance requirements and risk profiles. Vendors should be able to explain what data trains or informs the system, where human oversight is required, and how outputs are validated before they inform a procurement decision.

No. Generative AI and LLM outputs are probabilistic predictions, not verified facts, and can produce hallucinations that sound confident but are factually wrong. Any AI-generated output touching supplier assessments, contract terms, pricing recommendations, or risk thresholds must be validated by a human before it informs a decision.