How the TOGAF standard can be adapted & be applied to AI-driven transformation ?

How the TOGAF standard can be adapted & be applied to AI-driven transformation ?
SIPOC map auto generated by the ProcessHorizon web app

The TOGAF standard, short for The Open Group Architecture Framework, is a framework & methodology for developing, managing and governing enterprise architectures.

TOGAF helps organizations design IT architectures that align with business goals, ensuring that technology, data, applications & business processes work together effectively.

TOGAF provides the governance, structure & architectural coherence to ensure AI initiatives are sustainable, scalable & ethical.

An end-to-end SIPOC model (Suppliers>Inputs>PROCESS>Outputs>Customers) can help clarify how each TOGAF pillar (Business, Data, Application, Technology) contributes operationally to AI-driven transformation.

The resulting SIPOC process map can serve as an operational bridge between enterprise architects, data scientists & process owners.

Benefits of using SIPOC in TOGAF AI Projects

  • Clarity: simplifies architectural concepts for non-technical stakeholders
  • Traceability: connects business goals to data & application flows
  • Governance Alignment: helps identify accountability & ownership for each process step
  • Consistency: provides a repeatable format across different architecture domains
  • Integration with ADM: fits naturally into the Architecture Vision, Business Architecture & Information Systems Architecture phases of TOGAF Architecture Development Method (ADM)

Using the following link you can access this sandbox SIPOC model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/XShCyMx8TeHBpuPe1HEWnfQr/frontend

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Integrated Quality Management within GRC: A Foundation for Responsible Agentic AI

Integrated Quality Management within GRC: A Foundation for Responsible Agentic AI

Governance defines what should be achieved. Risk Management determines what could go wrong. Compliance establishes what must be respected. Quality Management ensures that processes and their outcomes consistently fulfill requirements & intended objectives. Together, they establish an integrated management system for responsible human & AI-driven enterprise operations. Event-driven SIPOC model

By Peter Haenni