How to address the Principal– Agent challenge by the Enterprise Action & Delegation Architecture ?

Peter Haenni

05 Sep 2026 — 1 min read

The event-driven SIPOC model on three action layers staged by ProcessHorizon

How does management know what its AI agents are doing, why they are doing it, what information they use, what authority they possess, what they produce, who is affected & who remains accountable?

The Enterprise Action & Delegation Architecture makes delegation governable from strategy to action. > Enterprise Principal Architecture: Strategy defines the purpose of delegation
> Agentic Management Architecture: Management defines the mandate
> Agentic Action Architecture: Operations executes the mandate
> Outcomes provide the evidence for accountability

The following three layers (L1 to L3) form one delegation chain:

L1 Strategy: Design Enterprise Delegation

Ensure delegation of Human & AI authority supports enterprise goals, stakeholder interests & risk appetite. What authority should the enterprise delegate, to whom & toward what objective ?

L2 Management: Govern Delegated Authority

Translate enterprise delegation principles into accountable agent mandates, decision rights and controls. Within what authority & controls may the agent act for the principal ?

L3 Operations: Execute Delegated Action

Ensure each Human or AI agent acts within its mandate & produces a transparent, traceable outcome. Did the agent act as authorized & achieve the intended outcome?

Event-driven SIPOC makes delegated action (Principal-AI Agent challenge) transparent: why an agent acts, on whose authority, with what information, toward what objective & for whose benefit.

Using the following link you can access this sandbox model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne event-driven SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/iiSNCdUQe4QQjHQUr83QuZox/frontend

Dynamic Risk & Capital Safe-State Management

The important architectural shift with the banker's algorithm is to treat capital not as a largely fixed annual constraint that business units subsequently consume, but as a continuously recalculated scarce safety resource attached to risk-taking. 1. Assess Risk Change Determine how a material change like a new transaction,

The AI-era Banker Algorithm for an event-driven Safe-State Architecture

Traditional banking controls generally assume that actions occur at a speed at which limits, escalation processes & humans can intervene. Agentic AI changes that assumption. An action that is safe for an individual agent is not necessarily safe for the bank & an action safe for one bank may still

ISO9001 QMS Governance Reference Architecture

With this event-driven AI-ready QMS Assurance Architecture on three hierarchical levels, the process architecture becomes the audit architecture. Q1 Understand Context & Stakeholders Ensure the QMS remains aligned with organizational context & relevant interested-party requirements. Q2 Set Quality Strategy & Objectives Translate context & stakeholder requirements into measurable quality direction.

AI-driven Professional Services Business Model

This AI-driven Business Model blueprint for professional services represents a transition from the traditional expert-hours business model toward a continuous Human & AI enterprise transformation & trust model. 1. Identify AI Opportunities Convert strategic, operational, regulatory & technological change into prioritized AI-enabled business opportunities. Should AI be applied here at