Keysight Software Test Automation

Generating more tests does not help much if your team still has to prioritize, execute, and investigate all of them. For QA leaders, the question is not just what AI can create. It is which work it could take on, and what oversight that requires. In this Keysight-sponsored analyst brief, IDC explores the potential of agentic AI for adaptive testing, defect analysis, and more autonomous workflows, alongside the integration and governance challenges. Download the IDC report below to inform your QA automation strategy.

How much of your QA team's week goes into proving that yesterday's workflows still work? Every PLM update brings another round of checks across parts, revisions, approvals, and connected systems. That repeated work leaves less time to investigate what has actually changed. Explore the hidden costs of manual PLM testing and why regression effort can become a constraint on engineering delivery. Download the PLM testing report below to see where the pressure builds and what needs to change.

The connection is restored. The operator selects Resume. The platform remains on Hold. A green link status proves connectivity returned, not that commands, application states, and operator expectations are aligned again. This solution brief explores validation across connected A&D systems, including the transitions and recovery behavior that isolated checks can overlook. Download the brief below to explore testing whether the workflow recovers, not just the connection.

Open PLM. Check the quantity. Switch to ERP. Compare the row. Repeat after the next change. Manual reconciliation keeps essential workflows moving, but it also ties experienced testers to repetitive checks across disconnected interfaces. This solution brief explains how Keysight Eggplant Test can follow engineering workflows across applications and validate the data and documents exchanged between them. Download the brief below to explore an alternative to checking every handoff by hand.

The pipeline is green. Then someone asks: “Did we verify order-to-cash after the change?” Test counts and pass rates tell you what ran. They may not tell you whether a critical workflow completed correctly, or recovered when something interrupted it. Explore why enterprise applications can still break after tests pass, and what workflow evidence adds to a release decision. Download the white paper below to bring a clearer basis for confidence to your next sign-off meeting.

When the release window shrinks, which tests do you leave out? Running the familiar suite is easier than deciding what matters most after a change. But new integrations, changed workflows, and limited testing time can make yesterday's priorities a poor fit for today's release. The Ultimate AI Testing Playbook explores AI-assisted prioritization, test maintenance, and the challenges of testing connected applications. Download the playbook below to explore a more risk-focused testing approach.