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How the Agentic AI Operating Model Works

Connect approved enterprise intent to coordinated execution across Strategy, Portfolio, Value Stream, Agentic Networks and Teams.

CONNECT THIS TOPIC TO AI TRANSFORMATION

The AIDIVE Agentic AI Operating Model connects enterprise direction to accountable AI-enabled work across five layers, alongside the maturity journey and six dimensions.

Explore the holistic AIDIVE framework

Why it matters

AI participation creates operating questions about work, decisions, accountability and coordination. The model makes those interfaces explicit so technical capability can become dependable enterprise work.

A federated execution architecture

Enterprise direction and non-negotiable boundaries flow downward. Operational evidence, exceptions, learning and capacity constraints flow upward. Decisions stay at the lowest layer authorized to make them; material exceptions follow approved escalation paths.

Six dimensions retain their source authority

The Operating Model enacts approved requirements through structures, roles, cadences, workflows and controls. It does not replace the definitions, assessment criteria or decision authorities of the dimensions.

  • Alignment: strategic intent, decision architecture and Autonomy Appetite.
  • Impact: outcomes, economics, attribution and benefits realization.
  • Data: information fitness, context, permission, provenance and lifecycle.
  • Integration: effective real-world flow, authority, continuity and traceability.
  • Values: human capability, leadership, work experience and adoption.
  • Ethics: legitimate purpose, responsible-AI assurance, risk and human-impact boundaries.

Keep structures, roles and capabilities distinct

A structure is an organizational forum, office, team or network. A role is an accountable human responsibility. A capability or artifact is something the model uses. Agentic Orchestration, Portfolio Kanban and Decision Points do not automatically become new committees or teams.

Evidence to make visible

  • A layer-and-structure map
  • Named human responsibilities and decision boundaries
  • Evidence and escalation routes between layers

Chapter map

  • 2.1.1 Framework Authority and Document Boundary
  • 2.1.2 AIDIVE Layer and Structure Map
  • 2.1.3 Role and Accountability Design Principles
  • 2.1.4 Cadence and Evidence Design Principles

Framework source

Editorial adaptation from the supplied AIDIVE Version 1 master documents.

  • AIDIVE - Architecture & Rhythm - Agentic AI Operating Model Version-1.docx — §2.1; §§2.1.1–2.1.2

Go a little deeper.

Human-Agent Roles and Accountability ↗Cadence and Evidence Design ↗The Strategy Layer ↗The Portfolio Layer ↗The Value Stream Layer ↗Talk to AIDIVELEARN. CONTRIBUTE. APPLY.

Put AI transformation
into practice.

Build capability through training, contribute your expertise or explore a connected workspace for applying the holistic AIDIVE framework.

TRAINING & CERTIFICATION

Build the capability.

Develop the skills to connect AI transformation strategy, business outcomes, people and governance to your own decisions and responsibilities.

Explore AI Transformation StrategistFind class dates across all providers ↗PARTNER WITH AIDIVE

Grow the practice.

Bring your learning, delivery or research expertise to the holistic AIDIVE approach to enterprise AI transformation.

Explore partnership routesAIDIVE PLATFORM

Bring AIDIVE into your work.

See how the proposed workspace could connect AI transformation learning, maturity evidence and practical artifacts.

Explore the platform conceptCONNECT THE DOTS

There is more to explore.

CONTINUE LEARNINGConnect the three framework componentsCONTINUE LEARNINGDesign accountable human-agent workCONTINUE LEARNINGBegin at the Strategy Layer
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