AI Business Operating Model Design

Who it helps and why

Transformation sponsors, operating leaders, enterprise architects and delivery teams.

Adding AI without changing responsibilities often moves work rather than improving it. Operating-model design starts with the work, decisions and controls the organization needs.

Implementation starts where the business decision is sufficiently clear. Define the workflow, accountable people, permitted data and measurable conditions before choosing a delivery approach. These offers cover a bounded pilot through enterprise operating-model change and continuing improvement.

What is included in the work

1. Target workflow, decision rights and human/AI responsibility map.
2. Evidence, governance and intervention requirements.
3. A staged transition and acceptance design.

How to use or commission this work

1. 1

   Start with your use

   Set the operating boundary and a baseline that can be measured.

   →
2. 2

   Examine the scope

   Name delivery responsibilities, approvals and intervention points.

   →
3. 3

   Agree the continuation

   Review observed results before expansion or continued operation.

What you bring and agree

Bring the current process, constraints, business goals and accountable decision makers.

Bring the decision you need to make and your intended use. Agree the relevant users, product or organisation boundary, permitted evidence and acceptance conditions. Any service or subscription begins on its agreed start date.

What you can work with afterwards

A concrete operating design that can guide implementation without implying that the target system already exists.

Fees are configured for the engagement. Agree delivery partners, integrations, access, acceptance criteria and support. An implementation engagement defines when and where approved work may operate.