Measuring the business value of AI implementation
By the Lynova.ai team · Published
In short
Measure AI value against a baseline taken before launch, using a small number of measures tied to the original problem: time saved, errors reduced, response speed, conversion or revenue. Review them at set intervals and include adoption and ongoing costs.
Take a baseline first
Record how the work performs today before anything changes: how long it takes, how often it happens, how many errors occur and what it costs. Without a baseline, any improvement is a guess.
Choose measures tied to the original problem
Pick two or three, not twenty:
- Time: hours of manual work per week, or time per task
- Quality: errors, rework or customer complaints
- Speed: time to first response or time to completion
- Revenue: inquiries answered, appointments booked, quotes sent
- Adoption: how often people actually use the new system
Count the full cost
Include licensing, usage fees, setup, integration, training and the time someone spends maintaining it. A tool that saves time but needs constant attention may not be a net gain.
Review on a schedule
Check the measures after the first month and again each quarter. If a measure is not moving, look at adoption and process first. The tool may be fine while the workflow around it has not changed.
Related solution: Business Automation and Process Improvement
Reduce repetitive work, streamline workflows, and improve operational efficiency.