By NMR Infotech · Practical guide · Updated
Start with a repeatable task
Choose a task with a clear input, expected output and named reviewer. Avoid starting with an open-ended mandate to automate a department.
Write down the current process
Record how the work is completed today, including time, errors, review steps and exceptions. A useful comparison needs a baseline.
Choose permitted examples
Use public, synthetic or approved information. Confirm tool access and information-handling requirements before testing.
Define quality before measuring speed
Describe what a correct output looks like. Include factual accuracy, completeness and usability. Track the work required to correct the AI output.
Run a bounded comparison
Use representative examples and review difficult cases, not only ideal inputs. Include licensing, integration and oversight effort in the evaluation.
Decide what happens next
Document what worked, what failed and what needs more evidence. Continue, revise or stop the pilot based on the agreed criteria.
This guide describes a general working approach. It does not claim that a particular tool or AI implementation guarantees a business outcome.