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How to evaluate a business AI pilot before expanding it
A convincing demonstration is the beginning of evaluation. Before expanding an AI assistant or automation, agree what useful performance looks like, what failures matter and how a person can intervene.
Define the business baseline
Choose one workflow and the people responsible for it. Describe how it works today: which records are consulted, where handoffs fail and how much review is required. Use a measurable baseline where possible, such as time spent preparing a brief or the number of unresolved handoffs. Do not attribute every improvement during a pilot to AI without considering process changes and the time spent supervising it.
Test the evidence behind the answer
For an assistant, include questions with clear answers, conflicting records, outdated records and no supported answer. Evaluate whether it identifies the source and acknowledges missing evidence. For an automation, include duplicates, missing fields, late updates and failed connections. These cases reveal more about operational readiness than a collection of successful examples.
Measure review effort alongside output quality
Track errors that matter to the workflow and the effort required to find and correct them. A faster draft may not save time if checking it is difficult. Separate the system's output from a person's final decision. Keep consequential actions behind the agreed approval controls until evaluation supports a change.
Evaluate access and recovery
Check that a user can access only the approved records. Define how permissions change when a person changes roles, how information is kept current and what happens when a connector fails. A workflow should show a clear failure or pending state rather than inventing a value or silently treating a failed operation as complete.
Use a scorecard without hiding hard limits
Score business usefulness, evidence quality, error handling, access controls and human review from zero to four. Zero means untested; one means a major unresolved gap; two means partial evidence; three means the agreed pilot criteria are met; four means those criteria have been met across additional representative conditions. Record evidence beside every score. An average is a discussion aid, not permission to overlook a serious access or safety failure.
Agree the next decision
At review, choose to stop, revise the pilot or expand within a defined boundary. Record unresolved issues and the person responsible. A low score can be a useful outcome if it prevents the team from scaling an unsuitable use case. A high score does not guarantee future performance after data, users or operating conditions change.
This scorecard is Viraya's planning template, informed by general risk-management principles. It is not a NIST certification, a compliance assessment or a substitute for domain-specific review.
Sources and scope
This article explains a review approach; it does not report a customer deployment or guaranteed result.