"We use AI" can mean almost anything: a case officer pasting a paragraph into a chat window, an office suite drafting replies from a mailbox, a coding agent editing a repository, a claims system calling a model through an API, or an agent settling low-value claims overnight without anyone approving each payment. The model underneath may be the same, yet the architecture, risk, controls, legal position, cost and competence required differ by orders of magnitude. This chapter therefore defines six usage modes of large language models, one in which people meet AI without choosing it and five in which they use it actively, compares them, explains how use cases drift between them, and sets a minimum control baseline for each. The rest of the book uses the modes as a taxonomy and links back here.
The properties that Chapter 1 identified hold in every usage mode. What changes between modes is how far the model's output travels before a human looks at it, what the model can see, and what it can do. A wrong sentence in a chat window costs a minute; the same sentence from an agent with write access to a case-management system can become a decision about a citizen. A policy written for chat is therefore too weak for agents and too heavy for spell-checking.
Amazon Web Services orders generative AI scopes by how much of the stack the organisation owns (115, AWS, n.d.). The usage modes add what ownership does not capture, the depth of integration and the autonomy granted to the model's output: ownership tells you who patches the model, whereas integration and autonomy tell you what happens when it is wrong or manipulated. The modes are defined by architecture, not by product, and products are named only as examples, with capabilities stated as of 1 November 2026. Following Architecture as Code (Chapters 1 and 2), which makes architecture governable by declaring its intent under version control (66, Nordqvist, 2025), the usage mode is part of the declared intent of every AI use case.
Primary topics explored
- Why the way a model is used matters more than the model
- Encountering AI and using it
- Mode 0 – Ambient AI
- Mode 1 – Conversational assistants
- Mode 2 – Embedded workplace assistants
- Mode 3 – Agentic work tools
About AI Governance
AI Governance is Book 2 of The Transformed Architecture. It shows how large European enterprises and public authorities decide what artificial intelligence is used for, classify and manage its risks, meet the obligations of the EU AI Act and its neighbours, choose and contract their suppliers, organise the forums that take decisions, and produce the evidence that shows it is all true.
It builds on the conclusions of Architecture as Code.
Chief risk and compliance officers, AI governance boards, CIOs and chief architects, and senior officials in public authorities.
Gunnar Nordqvist
Conceived, directed and published the books of The Transformed Architecture.
Continue with the full chapter
Chapter 2: From Chat to Agents: How Large Language Models Are Used in AI Governance gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “Foundations” and is one of 32 drawn from the manuscript.