Can You Prove Your AI Tests Work? Building Trust Through Governance, Traceability & Evidence
Your team is already using AI to generate tests, analyze failures, and accelerate delivery. But as adoption grows, a harder question surfaces: can you trust what it produces, and prove it?
Generating AI outcomes is easy. Explaining them, validating them, and demonstrating compliance when auditors, regulators, or leadership demand evidence is where most teams hit a wall.
This session explores practical strategies for operationalizing trusted AI across the delivery lifecycle. Learn how to reduce hallucinations through governed knowledge, trace requirements to AI-generated tests to execution results, and automate evidence collection so governance strengthens confidence instead of slowing you down.
Andrew Melton
Andrew Melton is a Principal Solutions Consultant at OpenText with over 15 years of experience in AI-driven software delivery, DevOps, cloud technologies, and enterprise software testing. He specializes in helping organizations plan, build, test, deliver, and govern complex applications while enabling the responsible adoption of AI across the software development lifecycle.
With expertise in quality engineering, test automation, continuous testing, and AI governance, Andrew works closely with development and QA teams to design modern testing strategies, integrate AI-driven automation into CI/CD pipelines, and help organizations deliver secure, high-quality software faster and with confidence.