AI Strategy & Transformation · Advisory

AI Operating Model Design

What stalls AI work is rarely the technology. It is that funding, approval, delivery, operation, and value ownership sit with five people who have never agreed on the handoffs between them.

AI work can stall when nobody knows who can fund, approve, or stop it. We assign those decision rights across sponsorship, delivery, review, operation, and value ownership, and connect them through governance handoffs that hold up under pressure.

When funding, review, or a stop decision is contested, your decision owner can point at the responsibility map and the stress-test report instead of calling a meeting.

Map the operating modelExplore AI strategy consulting
Illustration of AI Operating Model Design: a team charting AI investment decisions on a portfolio board

Some of the 500+ brands we've worked with

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  • Lexus
  • Little Caesars
  • Güven Hastanesi
  • Shiftdelete
  • Canbebe
  • Pozitif Live
  • GS Store

Steps, gates, and who decides

How we work

We design from real decisions, then push on the places where responsibility tends to blur.

  1. Map today's decisions

    Current decision rights, delivery roles, funding routes, governance interfaces, and value owners go into one picture, along with the authority expected to accept the result.

    AI assist
    From org charts and workflow records, the model drafts the current decision-rights and funding map.
    Human gate
    Design work starts after the current decision map is accepted as accurate. Your decision owner must confirm the current model before the team challenges it.

  2. Work through the friction

    With decision owners and representative examples in the room, we dig into the delays, overlaps, missing authority, and dependencies that make AI work hard to fund or deliver.

    AI assist
    Workshop notes give the model the delays and overlaps it needs to build a first friction map.
    Human gate
    Which role or interface owns the stalled decision? Whether a friction point is systemic or a one-off complaint is for the decision owner to settle.

  3. Design the target model

    Decision rights and handoffs get assigned across delivery, governance, operation, and value ownership. Exceptions stay explicit. Burying them in an organization chart is how models fail.

    AI assist
    Using the agreed rights, handoffs, and exceptions, the model drafts the target responsibility map.
    Human gate
    The target model advances when every consequential decision reaches a clear authority. Explicit rights and exceptions enter the target model only with decision-owner approval.

  4. Test and hand over

    Representative and failure cases run against the model. Open exceptions get an owner and a review point before anyone signs.

    AI assist
    In failure-case scenarios, the model tests the operating model and flags handoffs with no owner.
    Human gate
    Handoff requires accepted owners for the exception paths and a date to review the model again. Acceptance belongs to your authority, including the open exceptions and next review date.

Named artifacts you keep

What you get

The artifacts trace how a decision travels through your organization and where responsibility changes hands.

  • Architecture document

    Target AI operating model and responsibility map

    The roles, decision rights, funding paths, governance interfaces, and value owners for the target way of working.

  • Risk register

    Evidence trail behind the target operating model

    The source evidence, design assumptions, dependencies, and unresolved questions behind the operating model.

  • Test evidence

    Handoff stress-test report and open exceptions

    What happened when common paths, failure cases, escalation routes, and ownership exceptions were tested.

  • Decision record

    Acceptance and handoff brief for the target model

    The accepted model, remaining conditions, clear owners, and the next review date.

Scope and honest limits

When to bring us in

The work fits when AI crosses team boundaries but funding, authority, delivery responsibility, or value ownership hasn't kept up.

A good fit when

  • An AI project waits on a decision nobody makes, because the right to fund it, approve it, or stop it sits with three people who each assume another holds it.
  • Delivery and governance review run in parallel, but nothing says what passes between them, who hands it over, or what a review can send back.
  • A business case names the value the work should return, yet once the pilot closes nobody owns that number.
  • Sponsorship, delivery, risk review, operation, and value ownership all touch the same AI work, but no document says which of them decides what.
  • Funding routes and delivery roles were set up project by project, so a new dependency or a shared governance interface has no obvious way through.
  • Escalation and exception paths exist in principle, but nobody has walked an awkward case through them to see where the handoff actually stops.
  • A responsibility map exists somewhere, but the person who would enforce it never accepted it and it carries no date to be looked at again.

Better handled as other work when

  • You want the responsibility map to carry legal or audit weight. Making decision rights binding stays with your legal and audit authorities.
  • You want a reorganization. This work reassigns decision rights inside the structure you already have, and reporting lines stay yours to change.
  • You need someone to run the model after handoff. We test it, hand it over with its open exceptions, and stop there unless ongoing support is scoped separately.

If one of these is closer to your situation, start here instead: Explore AI strategy consulting

Advice from people who build

We've worked with more than 500 brands since Zeo started in 2011. The people helping you decide where AI fits, and where it doesn't yet, are senior engineers and strategists who build and operate production AI systems. The advice stays grounded in work that actually shipped.

Read our AI blog

Tools we use

Tools behind this work

  • Notion

    holds decision rights, escalation rules, and accepted handoff definitions

  • Airtable

    maps each recurring AI decision to its accountable roles

  • Asana

    tests proposed handoffs through real states, owners, and exceptions

Next step

Make the handoffs explicit

One stalled decision is enough to start. The discussion follows it through funding, review, delivery, and escalation until the broken handoff is visible.
Discuss the operating model

Before you decide

Questions we hear a lot

The work maps and tests decision rights and handoffs without reorganizing teams or changing employment responsibilities on your behalf.