The five-question AI ownership test

Test decision authority now, before delivery starts to stall.

An AI project can have an executive sponsor, programme director and a steering committee that meets fortnightly on Microsoft Teams.

This project can still have no real business owner. In fact, there might even be an executive name in the “Business Owner” box - yet this person was “voluntold” and will be polite about the project but won’t put their best effort into making it a success.

The gap between a sponsor going through the governance motions and a business owner who cares deeply about achieving the end goal because their reputation is on the line couldn’t be starker.

Transformation projects already carried high stakes before AI began dominating boardroom agendas around the world, so it’s no surprise that CEO-level ownership matters so much.

When I worked in change roles in the corporate world, I often came across well-documented projects with the finest hand-curated governance arrangements. Yet, when I looked under the hood and did the testing myself, I often found a documentation-reality gap.

Well-funded change programmes with “best practice” governance can produce amazing governance documentation while accountability and ownership dilute with every decision and meeting.

There is nothing worse for culture and buy-in to a change agenda than a delivery team waiting for business decisions while no one senior understands why AI projects are surfacing complex issues that block progress. Many AI projects are also surfacing hard-to-reverse, one-way-door decisions that leaders cannot afford to defer.

Silo structures and corporate politics are always fun to navigate, but on AI projects, they can be even more disruptive because of the additional hysteria floating around in relation to job loss and other topics like outsourcing and offshoring.

This requires careful planning and a lot of intensive stakeholder management through regular check-ins and over-communication. All of the different “project roles” can’t afford to be passive when so much is riding on AI projects at many firms.

What are the key warning signs?

• Delayed decisions that keep being rolled over from meeting to meeting

• Steering committee meetings that deviate from required decisions or actions

• No clear business owner with the authority to make decisions

• The gap between formal communication and informal vibes widening quickly

• Constant escalation of problems due to lack of clarity and delegated authority

A theme I’ve written about a lot on Getting AI To Work is that AI projects surface the cans that have been kicked down the road. If you took a shortcut on a data project three years ago and those gaps now undermine your AI project outputs, well, you need to fix that blocker to achieve the desired standard.

A technical team can’t decide a firm’s risk appetite, figure out the entire operating model in isolation, or manage the people consequences of AI change without the right level of executive support.

In the next section, paid subscribers will get further analysis and a short ownership test they can apply to a live AI initiative in their business. If you subscribe now, you’ll get the full ownership test and access to the archive of practical AI transformation and change playbooks.