AI in software testing – hope, hype, and liability: a look from the perspective of an expert

Artificial intelligence is rapidly changing how software is developed and tested. Test generation, automatic evaluation, self-healing test systems, and so on. Much of this sounds like a liberating breakthrough for quality assurance and engineering.
But what happens when these systems fail?

What does “quality” mean when decisions are no longer made deterministically, but probabilistically?
And how does responsibility change when errors can no longer be clearly attributed to humans or code?
This presentation combines the perspective of a software expert with the question of the future of testing in the age of AI.

The presentation is aimed at anyone who understands testing not only as a process but also as a factor in safety and trust, and who wants to know how quality can remain resilient in an AI-driven world. The lecture will be held in German.

Implementing accessibility strategically and effectively

Digital accessibility is no longer a voluntary additional task, but a legal and organizational obligation for companies and public authorities. In practice, however, accessibility is often only addressed on a selective basis—without a comprehensive approach that has a lasting effect. The presentation shows how a holistic accessibility strategy can be developed and implemented: from inventory (websites, apps, applications) to a clearly defined target state to prioritized action planning. One focus is on treating accessibility not as a one-time project, but as something to be integrated into the processes of design, development, editing, and procurement. In addition, training measures for relevant roles will be presented in order to anchor knowledge and responsibility within the organization. Finally, the presentation will explain how monitoring, reporting, and regular further development (e.g., re-audits, key performance indicators, roadmaps) make progress measurable and ensure long-term quality. The presentation highlights both the requirements of public authorities (e.g., BITV, documentation obligations) and the perspective of private companies (e.g., BFSG, risk minimization) and is aimed at decision-makers, project managers, and specialists who want to establish accessibility in a permanent and structured manner. The lecture will be held in German.

AI-based medical devices. A practical example with its requirements for the software development process and conformity assessment

The development of AI-based medical devices presents manufacturers with complex regulatory and technical challenges. The combination of the EU Medical Device Regulation (MDR), the EU AI Act, and numerous standards—especially the version of the new IEC 62304 ED2 released for comment—defines new requirements for the software development process for AI-supported systems. Different special features and processes must be integrated into the software development lifecycle (SDLC) and specifically planned and documented. The practical example describes the development and regulatory classification of an AI-based alarm system for use in intensive care units. The aim of the system is to detect critical patient conditions, such as sepsis, at an early stage on the basis of continuously recorded physiological measurements and to alert medical staff in good time. Using the above example, this presentation highlights how an AI-based medical device is created, which processes are interlinked, and which steps are taken to assess conformity. The draft of the new IEC 62304 ED2 and other regulatory requirements are also intended to show how manufacturers can adapt the software development process accordingly in order to successfully develop an AI-based medical device. The draft of the new IEC 62304 ED2 and other regulatory requirements are also intended to show how manufacturers can adapt the software development process accordingly in order to successfully develop an AI-based medical device. Among other things, the integration of the AI Development Lifecycle (AIDL) into the existing SDLC will be clearly analyzed and the individual phases of planning, design, and data management for AI-based medical devices will be discussed. The presentation is aimed at software developers, regulatory affairs experts, product managers, and decision-makers in medical technology who are involved in the development, approval, and quality assurance of AI-based medical devices. The lecture will be held in German.

The Era of Private AI: How Local Agents Automate Operations Without Data Exposure

For most enterprises, the barrier to AI adoption isn’t technology — it’s trust. This presentation showcases how local AI agents are transforming „Business as Usual“ by staying behind the corporate firewall. Drawing from Kalmia’s implementation experience, we will cover practical use cases: from an AI Assistant in manufacturing that handles process deviations to automated email agents that draft professional responses based on internal ERP data. We will demonstrate how these agents function as „digital coworkers“ that learn from your private data without compromising security. The session provides a roadmap for companies to achieve „quick wins“ in automation while ensuring 100%data sovereignty. The lecture will be held in English.

Automated benchmarks for an AI agent

At last year’s Net Week, she spoke in general terms about metrics that can be used to measure the quality of the results of generative AI in general and AI agents in particular. This year, she would like to explore the topic in greater technical depth. Which metrics can be recorded automatically and which cannot? What does automated benchmarking look like in practice? What statistical considerations are necessary to account for the non-deterministic nature of generative AI? Answers to these questions, with examples, will be presented in this talk. PS: You don’t need to have heard last year’s talk to understand this one. The lecture will be held in German.

Strengthening collaboration through MB testing at Lufthansa CityLine

This presentation will show you how Lufthansa CityLine was able to strengthen collaboration between requesters, developers, and testers through model-based testing (MBT). This allows you to focus on actions that lead to real improvements in quality. MBT ensures greater transparency and traceability in the testing process. Thanks to tool-supported test case generation, you can create the test cases that are most relevant to the product. The practical insights from Lufthansa CityLine will help you make your testing processes more efficient and sustainable. The lecture will be held in German.

Testing Trends: Shift Left, Shift Right, or AI – Which Path Leads to Optimal Quality?

The testing landscape is changing rapidly: Shift Left promises early error detection, Shift Right delivers production-related insights, and AI is permeating all areas of testing. But which approach is right for your company? Instead of blindly following trends, modern organizations need hybrid testing strategies that fit their individual corporate culture, technology, and specific business goals. This session shows you how to develop a customized quality strategy from the variety of current testing trends – for faster releases without compromising on quality. Learn which combinations of classic and innovative approaches work in practice and how to find the optimal testing mix for your specific challenges. The lecture will be held in German.

Evaluation and selection of AI models that can be integrated via APIs for your own solution scenarios

The informed selection of an AI model to be used via APIs poses massive challenges for current projects. Problems relate, for example, to the immense variety of existing approaches, differentiated quality characteristics, performance statements that are difficult to interpret, ethical and legal aspects, trustworthiness, and, last but not least, economic implications. The presentation analyzes current selection strategies for AI models from science and industry, taking into account benchmarks, cloud security, and the use of generative AI. Theoretical approaches are linked with practical experience and prototypical tests from the TAHAI project. The lecture will be held in German.

Quality engineering is the new testing

Testing is much more than just execution; it is the strategic engine that weaves quality into the product from the outset, rather than laboriously “testing it in” afterwards. In the modern software world, roles are merging into quality engineers who use engineering methods – from architectural design to agentic AI – to take responsibility for the overall result. Especially in non-deterministic systems, testing becomes a complex evaluation that requires a highly specialized infrastructure and a deep understanding of processes. You are leaving the era of pure debugging and entering the age of quality engineering, where you actively develop reliable quality. The lecture will be held in German.

Accessibility: Because the internet should not be an obstacle course

Since traditional accessibility testing is often time-consuming and difficult to scale, this approach combines proven testing methods with AI-powered tools. The focus is on the Descripta tool, which automates the analysis of images and the generation and comparison of alternative texts to ensure consistency and completeness. In addition to technical testing, the article highlights the importance of the legally required accessibility statement, which is substantiated by structured self-tests based on BITV criteria. This process enables organizations to accurately assess the degree of compliance of their websites and document it in a legally compliant manner, even without external certification. Overall, the article shows how AI not only makes quality assurance more efficient, but also allows for continuous and scalable monitoring of accessibility. The lecture will be held in German.

Quo Vadis Quality Assurance: Between Man, Machine, and Magic

AI is everywhere. Even in the testing process. Sometimes, however, AI feels like magic. This presentation will show how MCP Protocol can be used to make the testing process future-proof. The speaker will use practical examples to illustrate the challenges and opportunities presented by the use of AI in the testing process. The presentation will seek to find a balance between humans, machines, and magic in quality assurance. The lecture will be held in German.

Vibe Coding for Skeptics: Between Intuition, Misconceptions, and Real Productivity

Vibe Coding is currently being discussed as a new, intuitive way of software development—often in the context of AI-supported tools and new development workflows. But how does this approach feel when developing, especially when working with different programming languages and learning goals? In this talk, I share my personal experiences with vibe coding from the perspective of a C# developer who has tried the approach in small learning projects with Python as well as in experimental development settings, including with MCP servers. The focus is not on theoretical concepts, but on concrete observations from practice: When does vibe coding actually support learning and rapid experimentation?

Where do misconceptions or a false sense of progress arise? And how is the view of code quality, understanding, and maintainability changing? Using various scenarios - from cross-language work to exploratory mini-projects - the presentation highlights which tasks benefit from an intuitive, vibe-driven approach and where consciously structured approaches remain necessary. The goal is to realistically classify vibe coding: as a tool with potential, but also with clear limitations. The presentation is aimed at developers and quality managers who are curious but critical about new ways of working and who value sustainable productivity and understandable code. This lecture will be held in German.

Partner