TAOM is published as a growing, versioned and traceable body of knowledge. The aim is to gradually support organisations, project teams, architects, process owners, managers, staff and AI systems by providing them with a common organisational language and a practical methodology.

The publication is modelled on the concept of established framework portals: the overall structure remains stable, whilst individual chapters, reference models, practical examples, tool mappings and implementation guides are gradually added, reviewed and updated.

TAOM is being developed by Traniva and is being further refined on the basis of practical project experience, scientific insights and existing industry standards.

The introduction explains TAOM’s motivation, objectives, language, scientific approach and positioning.

The TAOM Constitution sets out the binding fundamental principles of the method, including:

• academic focus
• practical applicability
• Human-Centered Organization
• Human before Framework
• organisational reality
• Integration of existing methods
• continuous adaptation
• AI-native Thinking
• Living Documentation
• ethical and responsible development

These include:

• What is an organisation?
• What is value?
• What is work?
• What is knowledge?
• What is intelligence?
• What is a decision?
• What is a capability?
• What is learning?
• What is adaptation?
• What is governance?
• Was ist Artificial Intelligence?
• What is an AI Worker?
• What is an Adaptive Enterprise?

These include, amongst others:

• Enterprise Meta Model
• Enterprise Language
• Enterprise Value System
• Enterprise Intelligence
• Enterprise Knowledge
• Enterprise Decisions
• Enterprise Capabilities
• Enterprise Organization
• Enterprise Execution
• Enterprise Adaptation
• AI Workforce
• Enterprise Digital Twin
• Governance
• Measurement
• Ecosystems
• Feedback und Coordination

These include:

• Strategy Management
• Organization Management
• Capability Management
• Knowledge Management
• Decision Management
• Process Management
• Resource Management
• AI Workforce Management
• Governance Management
• Performance Management
• Change and Transformation Management
• Enterprise Delivery Management

These include:

• Enterprise Architecture
• Business Architecture
• Capability Architecture
• Information Architecture
• Data Architecture
• Application Architecture
• Integration Architecture
• Technology Architecture
• AI Architecture
• Security Architecture
• Digital Twin Architecture
• Solution Architecture
• Reference Architectures
• Architecture Governance
• Architecture Repository

These include:

• Enterprise Analysis
• Enterprise Design
• Enterprise Planning
• Portfolio Engineering
• Roadmap Engineering
• Transformation Engineering
• Simulation
• Optimization
• Innovation
• Resilience
• Sustainability
• Intelligence Engineering
• Evolution Engineering
• Reference Models

The focus is not on individual manufacturers, but on the skills required:

• Process and Architecture Platforms
• Knowledge Platforms
• Delivery Platforms
• Enterprise Applications
• Integration and Automation
• AI Platforms and Agents
• Analytics and Measurement
• Governance, Risk, Security and Compliance
• Enterprise Digital Twin and Context Graph

Typical tools may include SAP Signavio, LeanIX, Jira, Confluence, SAP S/4HANA, Microsoft Teams, Langdock, Make.com, n8n, Power BI, SAP Analytics Cloud, GitHub and other platforms.

TAOM Companion

• A day in the life of a key user
• A day in the life of a process owner
• A day in the life of a project manager
• A day in the purchasing department
• A day in sales
• A day on the production line
• A day in quality management
• A Day in the Life of an AI Worker

Examples of end-to-end processes and repository structures, including:

• L0–L4 process hierarchy
• Roles and RACI
• Systems and Transactions
• Requirements and user stories
• Risks and controls
• Tests and evidence
• KPIs and feedback loops
• TAOM Concept Mapping

Descriptions for shared project agents:

• TAOM Companion
• Method & Orchestration Agent
• Process Agent
• Knowledge Agent
• Delivery Agent
• Agent Collaboration
• Application Agent
• Quality Agent
• Learning Agent

Specific mapping of TAOM capabilities to platforms, integrations, data objects and human-in-the-loop rules.

Every publication should:

• have a unique version
• indicate their status
• Document changes in a way that allows them to be traced
• Distinguishing between TAOM-specific definitions of established knowledge
• list relevant standards and sourceslist relevant standards and sources
• to clarify which statements are still hypotheses or preliminary models
• take into account practical implementation and human adoption

TAOM is currently being set up in a structured manner.

The overall architecture and key components have been defined. Individual chapters, reference models and practical building blocks are being developed and published in stages.

This allows TAOM to grow without having to reinvent its fundamental structure with every expansion.

• What is TAOM?
• TAOM in the project – Human + AI Project Support
• TAOM Introduction
• TAOM Constitution
• Part I — Theory
• Part II — Operating System
• Part III — Enterprise Management
• Part IV — Enterprise Architecture
• Part V — Enterprise Engineering
• Part VI — Enterprise Tooling
• TAOM Companion
• Reference Processes and BPML
• Agent Skill Profiles
• Glossary and Enterprise Ontology
• Scientific References
• Standards and Framework Comparison
• Research Agenda
• Version History

Any subsequent content should therefore answer at least one of the following questions:

• What organisational problem does this solve?
• Which TAOM function is affected?
• What are the roles and responsibilities?
• What processes and artefacts are required?
• Which tools support implementation?
• How does AI help?
• Where does human responsibility lie?
• How is success measured?
• How are results and feedback fed back into the organisation?

TAOM is thus evolving into a comprehensive collection of methods, a practical project model and a navigation system for hybrid organisations.