AI & Testing/QA: Exploring the Intersection of Artificial Intelligence & QA

Artificial Intelligence (AI) has transformed various industries by automating tasks, enhancing data analysis capabilities, and improving decision-making processes. The intersection of AI and Testing/QA presents both challenges and opportunities.
On the one hand, the complexity of AI systems, data quality, bias, integration issues, and continuous learning pose significant QA and reliability hurdles that need to be tackled and managed.
On the other hand, AI offers immense opportunities for enhanced test automation, improved test coverage and efficiency, and QA predictive analytics such as Quality Gates Verification.
By leveraging AI technologies, QA and DevOps/SRE teams can overcome these challenges and unlock new levels of efficiency and effectiveness in their testing processes. However, testing and QA for such AI systems require new approaches and practices.

Opening: Building, testing, and SRE for agentic systems
Sammer Puran, Lead AI & MLOps Engineer, Swiss Digital Network

TALK 1 - RAG - Real-time knowledge for smart avatars
Tobias Denzler, Cloud Architect and co-founder of EVONATE AG
Retrieval Augmented Generation (RAG) is changing how systems access large knowledge repositories and process complex information in real time. This presentation will explain the basics of RAG and show how digital avatars can use it to provide precise and context-sensitive answers. Practical examples will be used to explain how RAG works and how it can be used to improve the language capabilities and interaction of avatars. The presentation aims to show the audience how RAG can be used as a key technology for interactive systems of the future.

TALK 2 - Innovation live: Applying AI to automate Quality Gates Verification in DevOps pipeline - AI-SQUARE architecture patterns & demo – Olivier Mann, Product Owner AI-SQUARE and Senior Technical Consultant, Swiss Digital Network
Traditional decision-making methods like Change Advisory Boards (CABs) can become bottlenecks in the DevOps flow. To automate the decision-making process within DevOps pipelines, it is important to invest in smart quality gates that operate based on insights generated from machine learning (ML).
This talk will present the design patterns behind AI-SQUARE, an AI-driven solution for assessing software quality and maturity. We will illustrate briefly the concept of knowledge graphs and their use in capturing and storing extra Performance QA context parameters along with standard observability data from various test results and system behavior data sources. The enriched data in such knowledge graphs will be used as input for ML models to analyze anomalies and assess quality gates related to performance and reliability, and functional requirements. A demo will cover the automation of performance quality gates verification within the DevOps pipeline.

TALK 3 – AI-powered test design & management
Kevin Horvath, Lead Product Manager at Tricentis
This talk outlines how generative AI can enhance testing efficiency in IT and quality engineering by accelerating test case generation, scaling test coverage, tailoring test plans, and analyzing and improving test case libraries. Practical examples, like AI-powered Testing for SAP, will illustrate how a concrete implementation of such AI capabilities could improve testing process efficiency.

After the talks, stick around for networking, over bites and drinks!
*** Please arrive 10 minutes early. We will welcome you at the main entrance and accompany you to the auditorium, where the Tech Talks start at 17:00***
Looking forward to welcoming you to our Tech Talks Basel.