Human–AI Operating Design Canvas.

Use six AIDIVE questions to design accountable human–AI work. Connect business outcomes, roles, decision authority, shared controls, human judgment and service ownership within enterprise AI transformation.

A teaching canvas adapted from AIDIVE V1. Complete it with the relevant outcome, delivery and assurance owners.

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Who owns the relevant business or service outcome?

Name the outcome, its boundaries and the person accountable for it.

Which work may be delegated?

Specify the task or decision class. Record what is excluded.

What authority may the agent exercise?

Choose Assist, Recommend or Act for the specified decision seam. Define Escalate / Stop.

Which shared controls must surround that authority?

Identify permissions, trusted context, evaluation and observable control evidence.

Where must human judgment enter?

Choose human involvement separately. Record approval, intervention and safe-stop arrangements.

Who operates and retires the service?

Name operating ownership, monitoring, recovery and retirement responsibilities.

This canvas supports a design conversation. It does not grant authority or replace formal investment, release, risk or assurance decisions. Bounded HOOTL is limited to eligible low-risk, reversible, observable decision classes with named human accountability and tested intervention.

Framework source

Editorial adaptation from the supplied AIDIVE Version 1 master documents.

• AIDIVE Architecture & Rhythm - Maturity Version-1.docx — introduction; §1.1 The Roadmap to AI-Native Organizations – Phases; §1.2 Progression Governance; §1.3 AIDIVE Capabilities; §1.4 360° Integration Across the AIDIVE System.
• AIDIVE - Architecture & Rhythm - Agentic AI Operating Model Version-1.docx — §2.1 How the Operating Model Works; §2.1.3 Human-Agent Operating Model Quick Reference; §2.1.4 Cadence and Evidence Design Principles; §§2.2–2.6 Operating Layers; §2.5.7 Release & Exposure Expansion Gate; §2.7.2 Orchestrator Responsibility Matrix.

Put AI transformation
into practice.

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

Build the capability.

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

Grow the practice.

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

Bring AIDIVE into your work.

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