AI, SAP & The Future of Quality Testing with Tricentis
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Key Takeaways
⇨ The Tricentis Transform conference addresses the challenges and strategies for modernizing enterprise applications, particularly in the context of AI's impact on software development and quality engineering.
⇨ Automation is essential in today's complex SAP environments, as it ensures comprehensive regression coverage and reduces the risks associated with interconnected business processes.
⇨ AI enhances testing strategies through capabilities like agentic automation, object recognition, and self-healing scripts, allowing for more efficient testing and focusing efforts on critical application areas.
The integration of artificial intelligence (AI) is profoundly transforming software development, particularly for complex enterprise systems such as SAP. This technological shift requires a new approach to quality engineering to ensure stability and performance. The upcoming Tricentis Transform conference is dedicated to exploring these challenges and presenting new strategies for modernizing enterprise applications.
From Theory to Practice
The event, which will take place in London (October 14-15) and Nashville (October 21-22), is designed for professionals involved in developing, testing, and maintaining enterprise applications, including technology leaders, practitioners, and industry innovators. The program will focus on modernizing software engineering, with a significant emphasis on the impact of AI.
According to Kevin Thompson, CEO of Tricentis, “Tricentis Transform is more than a conference — it’s a gathering of the best in quality engineering, serving as a springboard for innovation through automation and intelligence.”
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The conference agenda features sessions addressing key challenges for SAP professionals. Core topics include strategies for de-risking SAP S/4HANA migrations, applying AI-powered solutions to reduce testing timelines, and integrating continuous quality practices into SAP delivery pipelines. Attendees will also learn from customer stories and practical strategies presented by industry peers, demonstrating how AI-powered capabilities are making SAP modernization more efficient and secure.
Testing in an AI-First World
“Our longstanding commitment to quality and leadership in this era of agentic AI make Tricentis Transform the premier event for customers, partners, and the broader quality engineering community to engage in dynamic conversations and examine what’s next for software testing as AI further transforms the business landscape,” Thompson added.
The conference builds on Tricentis’s Remote Model Context Protocol (MCP) servers and Tricentis Agentic Test Automation, which were introduced earlier this year. These advancements have marked a significant leap for organizations seeking flexible and open access to AI to accelerate their enterprise testing workflows.
Moreover, in an AI-driven development landscape, quality engineering serves as a foundational pillar for success and staying ahead in business. Attend Tricentis Transform to explore modernizing SAP systems. Learn more and register today.
What This Means For SAPinsiders
Here’s a closer look at the critical shifts being discussed at Transform and why they matter for your SAP environment:
- Automation is critical in today’s SAP landscape. The complexity of modern SAP environments, combined with accelerated release cycles for SAP S/4HANA, renders manual testing insufficient as a primary method of quality assurance. Therefore, automated testing is essential for providing comprehensive regression coverage. For SAPinsiders, this ensures that modifications do not negatively impact interconnected business processes, thereby minimizing business risk and allowing functional experts to focus on higher-value activities.
- AI is the supercharger for your testing strategy. AI technologies enhance test automation by introducing agentic capabilities. For SAP systems, this includes AI-powered object recognition for more resilient UI testing across SAP Fiori and SAP Enterprise Continuous Testing by Tricentis, as well as self-healing scripts that reduce maintenance overhead. Furthermore, AI facilitates risk-based testing by analyzing code changes to prioritize test cases. This helps in focusing engineering efforts on the most critical application areas to improve efficiency.