How to Catch AI Delegation Drift Before Your Board Does

TL;DR: The AI Delegation Audit Webinar Recording

When AI-assisted output still looks fine, it is tempting to conclude the delegation is fine. In my October 6 webinar with Scrum.org on the AI Delegation Audit, I walked through a fictional case in which that belief held for months, then fell apart in a board meeting, and showed the check that would have caught it.

Thesis: The AI Delegation Audit is a 45- to 60-minute review in the A3 Delegation System, run like a Sprint Retrospective, that checks whether a team’s AI delegations still hold; the post explains its four checks with a fictional case and shares the Scrum.org webinar recording.

Disclaimer: I read Charniak/McDermott’s book on “Artificial Intelligence” decades ago; of course, I use AI for research, translations, proofreading, challenging story arcs and article structures, and summarization. It is a production tool, not a substitute for thinking.

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The Report That Said “No Open Issues”

Let me introduce you to the webinar’s use case: At Brandtner Pumps, a fictional manufacturer, project lead Marta has an AI assistant draft her monthly board report from four sources, one of them an agency’s weekly update. By month 10, her review time has shrunk from 60 minutes to 20, and the agency moves its update to a portal, where the PDF’s defect list turns out to be an image. The report says “no open issues.” In her absence, a month later, her deputy sends it without reading it. The whole issue blows up during the board meeting, when the CFO shows the agency’s invoice for 40 hours of “defect resolution,” while the update lists 17 open defects, 5 blocking the pilot launch.

A stop rule existed, yet nobody triggered it, and the deputy did not know it, so the Handoff Canvas still said Assist while the work ran as Automate. A more expensive model doing a better job would have been a guess, since only the input had changed.

The AI Delegation Audit: Four Questions on a Schedule

Monthly, or every other Sprint, the audit tests the calls a team made with the A3 Framework (Assist, Automate, or Avoid), the Handoff Canvas, and the AI Definition of Done against four questions:

• Output and source drift: Does the output still meet our standard, and are the sources still the ones we started with?
• Model fit: Is this tool still right for the task and its risk?
• Reversibility: Could we stop this tomorrow, and who would do it?
• Category creep: Are we still reviewing what we said we would review?

My pitch to you: Start small in your next Retrospective, pick the AI workflow that would hurt most if it were wrong, ask the four questions in your next Retrospective in 15 minutes, and leave with one decision, one owner, and one date.

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Watch the Recording

📺 Youtube link: The AI Delegation Audit – A Recurring Check for Work You’ve Handed to AI.

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🎓 For the complete A3 Delegation System, join the December pilot workshop: three live-virtual sessions on December 3, 10, and 17, 2:00 to 6:00 pm CET.

Key Questions This Article Answers

What Is the AI Delegation Audit?

The AI Delegation Audit is a recurring team review that checks whether decisions about work handed to AI still hold. In the A3 Delegation System, it runs monthly or every other Sprint, takes 45 to 60 minutes, follows the format of a Sprint Retrospective, and uses the team’s Handoff Canvases, AI Definitions of Done, and records as input. Every finding ends as a decision with one owner and one date.

What Does the AI Delegation Audit Check?

The AI Delegation Audit checks four things: output and source drift (does the output still meet the agreed standard, and are the sources still the original ones?), model fit (is the tool still right for the task and its risk?), reversibility (could the team stop the delegation tomorrow, and who would do it?), and category creep (is the team still reviewing what it agreed to review, or has Assist turned into Automate?).

How Can a Team Start an AI Delegation Audit in 15 Minutes?

A team can run a first AI Delegation Audit in 15 minutes at its next Sprint Retrospective. It picks the AI workflow that would hurt most if it were wrong, asks the four audit questions (output and source drift, model fit, reversibility, and category creep), and makes one decision with one owner and one date. The full audit takes 45 to 60 minutes and runs monthly or every other Sprint.

AI Delegation Audit — Related Posts

AI Transformations And Agile Transformations Rhyme

You Already Have an AI Working Agreement. Write It Down.

If You Can Facilitate a Retrospective, You Can Audit Your AI

The AI Definition of Done: Human in the Loop Is Not a Quality Standard

The AI Delegation Lifecycle: Your Team Has AI Outputs. Where Are the Decisions?

Assist, Automate, Avoid: How Agile Practitioners Stay Irreplaceable with the A3 Framework

The A3 Handoff Canvas: Six Questions That Turn AI Delegation Into a Repeatable Workflow

The A3 Framework: Assist, Automate, Avoid — A Decision System for AI Delegation

👆 Stefan Wolpers: The Scrum Anti-Patterns Guide (Amazon advertisement.)

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