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TAOM™ AI Framework

TAOM™ AI Framework

Introducing tools is easy. Changing an organisation is not.

Most organisations start with individual AI tools – assistants, chatbots, automation, agents. That does not yet make an AI-native organisation. Das Framework beantwortet die grössere Frage: how should an organisation work in which people and AI act together?

  • Theory
  • Operating model
  • Management
  • Architecture
  • Engineering
  • Tooling

The difference

From introducing AI to adapting the organisation

What usually happens

  • An assistant is rolled out
  • A chatbot answers enquiries
  • A workflow is automated
  • An agent is piloted

Each initiative makes sense on its own – and yet the organisation works exactly as it did before.

What the question really is

How are decisions made when a machine has a say? Who owns a process an agent works on? How does the AI know what applies in the organisation? Who is accountable for a result nobody wrote?

Questions like these are answered by a body of knowledge, not by a tool.

The structure

Six building blocks, 96 canonical chapters

Each building block has a task of its own – and each chapter a fixed identifier that can be cited permanently.

THY Theory with 13, OS Operating System with 21, MGT Management with 12, ARC Architecture with 15, ENG Engineering with 15 and TOOL Tooling with 20 chapters, 96 in total.

Not a stack – a chain

The building blocks build on one another

Theory explains why organisations work the way they do. The Operating System translates that into an operating model. Management runs that model day to day. The Architecture designs the structure for it. Engineering builds and changes it. And Tooling beschreibt, welche technischen Fähigkeiten das trägt.

Starting with the tool skips five questions – and you only notice when the rollout stalls.

Living documentation

A body of knowledge that changes with you

The framework is not a manual published once. It grows in versions and traceably – with stable chapter IDs, so references do not expire.

Human-centredPeople before frameworks, with emphasis on human accountability in automated workflows.
Methodically integratedCombines scientific foundations with practical applicability and established standards.
VersionedUnambiguous versions, clear status, affected chapters and documented changes.
AI-nativeCovers the collaboration of people, AI workers and agents within governance.

The knowledge can be linked with reference processes, BPML, agent skill profiles, enterprise architecture, tool mapping, use cases and implementation notes – see Resources.

Where to start

Start with the view that matches your work

If you design structure, start with Architecture. If you deliver, with Engineering. If you govern, with Management. And if you want to know why it is all built this way, with Theory.