RIGHT ENGINES
Work fails between teams rather than inside them
A practical guide to diagnosing work fails between teams rather than inside them and deciding whether an AI engine is justified.
The problem
Requests arrive without context, acceptance criteria, ownership, or a reliable feedback loop.
Symptoms
Look for recurring delay, correction, escalation, or paid attention around this workflow. Confirm the pattern with representative handoffs, roles, required information, service expectations, exceptions, failure evidence, and escalation paths. rather than relying on anecdotes.
Why it happens
Each team optimizes its own step while the end-to-end operating contract remains implicit.
What it costs
Measure the burden created by work fails between teams rather than inside them: responsible-person hours, elapsed delay, rework, error exposure, outside spend, and decisions deferred. Use a representative baseline; do not invent ROI.
What people usually try
More status meetings, extra forms, or blaming the receiving team without measuring queue and rework.
Where AI helps
For this problem, AI may help by turning representative handoffs, roles, required information, service expectations, exceptions, failure evidence, and escalation paths. into a handoff contract, completeness gate, routing logic, exception ownership, and feedback measures. It should preserve evidence and expose exceptions for review.
Where AI does not help
Do not automate a handoff until responsibility and decision rights are explicitly agreed.
What an engine could do
A handoff contract, completeness gate, routing logic, exception ownership, and feedback measures.
Inputs required
Representative handoffs, roles, required information, service expectations, exceptions, failure evidence, and escalation paths.
Success measures
First-pass acceptance, queue time, rework, ownership clarity, and escalation frequency.
Risks
The specific failure boundary is clear: Do not automate a handoff until responsibility and decision rights are explicitly agreed. Also test provenance, access, false confidence, and the effect of unreliable inputs.
Small / medium / large solution
Start with the smallest validated route. Use an Outcome Kit only where its stated inputs and tests fit work fails between teams rather than inside them; adapt a proven engine where workflow context differs; commission private work only when the evidence, integration, governance, or rights justify it.
Estimate this problem’s burden · Decide whether it is worth building for · Review reusable Outcome Kits
Published 2026-08-31 · Updated 2026-08-31 · Version 1.0