Swiss Testing Day 2027: Proof, not Promises - 20th Anniversary Edition

Swiss Testing Day is the ultimate conference for testers, test managers, test automation engineers, quality leaders, innovators and enthusiasts. Get ready for an immersive experience with the testing community!

At this one-day conference, practitioners and enthusiasts share insights and best practices, discuss future trends on topics ranging from testing of and with AI to strategy and impact. Swiss Testing Day provides an opportunity to discuss challenges, exchange experiences and share ideas, to network and to leave with practical suggestions to apply when you get back to the office.

We have an open call for speakers, where we invite practitioners to send in their stories. 

Strategic Quality Management - The Reality Check: 

• Facts, Not Hype: What's proven, and what's a sales pitch?
• Outpaced or Replaced? Are the machines taking our work? Both sides, no sugarcoating.
• Reading the Numbers: Telling a study from a marketing chart. That keeps you off every hype train.
• Honest About the Unsolved: The half-solutions too, and what didn't work. That's where you learn most.

Quality Engineering - The Future Tester:

• The Craft Matters More: With autonomous systems or without: test design, risk analysis and a critical mind stay the base.
• The Tester Is Dead. Again: Announced for twenty years. He's still here
• From Tester to Quality Engineer: The job is shifting. Which skills count now, and how do you stay visible?
• AI as a Coworker: The AI writes along. How do we assure quality when part of the team is code?
• Shaping Quality, Not Running Tests: Away from running test cases, toward leading quality. No title needed.
• When Delivery Outruns Understanding: The faster it ships, the more it matters to know what you're building.
• E2E and Integration: In the end the interplay decides, not the single part.

AI TRiSM - Trust, Risk & Security for AI systems:

• Digital Sovereignty: Who owns quality when the code isn't ours anymore?
• Trust in AI: How do you test a system that answers the same question differently twice?
• Ethics in AI: Not everything possible should be built. Who draws the line, and who is accountable
• Security and the New Risks: Security stays a constant. AI adds new attack surfaces.
• Who Are We Testing For? When agents drive the UI and users are simulated, who we test for changes.
• Regulated, and Under AI Pressure: Where mistakes get expensive, AI is arriving too: pharma, finance, critical systems.