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WHITEPAPER — AUGUST 2026

The Unit of Work

How enterprise AI earns its way into production

Most enterprise AI programs don't fail because the model wasn't good enough. They fail because nobody defined the work precisely enough to tell whether the model was good enough. This paper is a practical method for choosing, bounding, pricing, and proving enterprise AI work — written for the executive who has to approve the budget and the operator who has to live with the result.

The Unit of Work — EE Solutions whitepaper

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WHAT'S INSIDE

A Practical Method for Getting AI Into Production

The paper covers what to build first, how to know it's working, where the human belongs in the loop, and what it costs to run once the pilot is over. Four decisions you can make before a line of code is written.

01

The Unit of Work Test

Four pass/fail questions to qualify any AI candidate before scoping begins — is it observable, repeatable, countable, and does it have a defined owner downstream?

02

Defining Correct Before You Build

How to measure the baseline, set an explicit acceptance threshold, and get stakeholders to agree on what "right" looks like — before a single model is evaluated.

03

The Build Path and Operating Model

Scope, cost, and the human-in-the-loop decisions that determine whether a system keeps running after launch — and who owns it at the point of use.

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